Maple Questions and Posts

These are Posts and Questions associated with the product, Maple

First time maple user here,

I have a set of equations, as follows

u_o = u-(diff(v(x), x)) . y-(diff(w(x), x)) . z

v__o = v-phi . z

w__o = w+phi . y

 

where u,v,w are all differentiable w.r.t. x,y,z. I want to evaluate the partial derivative of each of these three expressions w.r.t. x,y,z.

For example, epsilon = Diff(u__o,x) (this is supposed to be a partial derivative)

When I try epsilon = diff(uo, x), i get this epsilon = -(diff(v(x), x, x)) . y-(diff(w(x), x, x)) . z

which is evaluating u as a constant but not giving me Diff(u,x)

when I try using convert((D(uo))(x), diff), I get diff(u(x), x)-(diff(diff((v(x))(x), x), x)) . y(x)-(diff((v(x))(x), x)) . (diff(y(x), x))-(diff(diff((w(x))(x), x), x)) . z(x)-(diff((w(x))(x), x)) . (diff(z(x), x))

which doesn't know that Diff(y,x)=0

How can I evaluate these expressions appropriately?

Any help will be greatly appreciated!

 

Dear all,

 

I am saving a logplot as :

plotsetup(jpeg, plotoutput = "/Users/test.jpg", plotoptions = "quality=200,height=1100, width=1500"); display(logplot(x^2-3, x = 0 .. 100), legendstyle = [font = [bold, "TimesNewRoman", 30], location = right], thickness = 4, font = [bold, "TimesNewRoman", 30]); plotsetup("inline", plotoutput = "terminal", plotoptions = "quality=100,height=1000, width=1500")

and the output is the plot attached.

test.jpg

This is my problem: I do not want the y-axis tickmarks to be shown as .1 e2, .1e3, ...

I would like them to be 10^2, 10^3, ...

Please remember that I need them to be saved like this because the quality is much better than when you export the plot directly.

Can someone help me, please?

Hi!

Looking the Maple's help, I see that the command "isolve"  tries to solve an equations   over the integers. Then, given m>1 and t in the interval [0,1], How can used this command to find an integer j>=1 such that (j-1)/m<=t<j/m. That is, fin j such that t belongs to the interval [(j-1)/m,j/m].

 

Thanks in advance for your comments and help.

Hello,

I have to compare a lot of sample pairs with the TwoSampleTTest. I need only the pvalue for a cross table. It is possible to extract the pvalue of the TwoSampleTTest?

Many thanks!

This is an example, the program gave me functions _F as outputs and i want to see what F is.

This is an example.

Thanks.

This is an application of the previous posts
https://www.mapleprimes.com/posts/209057-Procedure-For-Expanding-Tensor-Product

I have a fourth version of the ExpandQop that will expand automaticaly the power of
quantum tensor product. This is just a minor change to the procedure.

Now here is an application for all this that will help understanding a little about
quantum computing. This is the classical concept of quantum teleportation.

You will need to run the above mentionned file and uncomment the save line in the file
before running the example.

LL
 

######################################################################
# NOTICE                                                             #
# Author: Louis Lamarche                                             #
#         Institute of Research of Hydro-Quebec (IREQ)               #
#         Science des données et haute performance                   #
#         2018, March 7                                              #
#                                                                    #
# Function name: ExpandQop (x)                                       #
#       Purpose: Compute the tensor product of two quantum           #
#                operators in Dirac notations                        #
#      Argument: x: a quantum operator                               #
#  Improvements: Manage all +, -, *, /, ^, mod  operations           #
#                in the argument. Manages multiple tensor products   #
#                like A*B*C*F                                        #
#       Version: 3                                                   #
#                                                                    #
#  Copyrigth(c) Hydro-Quebec.                                        #
#        Note 1: Permission to use this softwate is granted if you   #
#                acknowledge its author and copyright                #
#        Note 2: Permission to copy this softwate is granted if you  #
#                leave this 21 lines notice intact. Thank you.       #
######################################################################
restart;

with(Physics):
interface(imaginaryunit=i):
Setup(mathematicalnotation=true);

[mathematicalnotation = true]

(1)

Setup(unitaryoperators={I,U,X,Y,Z,H,HI,CNOT,CnotI});
Setup(noncommutativeprefix={q,beta,psi});

[unitaryoperators = {CNOT, CnotI, H, HI, I, U, X, Y, Z}]

 

[noncommutativeprefix = {beta, psi, q}]

(2)

Setup(bracketrules= { %Bracket(%Bra(q0), %Ket(q0))=1,
                      %Bracket(%Bra(q1), %Ket(q1))=1,
                      %Bracket(%Bra(q1), %Ket(q0))=0,
                      %Bracket(%Bra(q0), %Ket(q1))=0
                    });

[bracketrules = {%Bracket(%Bra(q0), %Ket(q0)) = 1, %Bracket(%Bra(q0), %Ket(q1)) = 0, %Bracket(%Bra(q1), %Ket(q0)) = 0, %Bracket(%Bra(q1), %Ket(q1)) = 1}]

(3)

####################################################################################
# Load the procedure and set the required global variables
#
read "ExpandQop.m": optp:=op(0,Ket(q0)*Ket(q1)): optpx:= op(0,(Ket(q0)+Ket(q1))^2):
#
####################################################################################

#
# Pauli operators
#
print("Pauli gates");
I:=Ket(q0)*Bra(q0)+Ket(q1)*Bra(q1);        # = sigma[0]
X:=Ket(q1)*Bra(q0)+Ket(q0)*Bra(q1);        # = sigma[1] = sigma[x]
Y:=-i*Ket(q1)*Bra(q0)+i*Ket(q0)*Bra(q1);   # = sigma[2] = sigma[y]
Z:=Ket(q0)*Bra(q0)-Ket(q1)*Bra(q1);        # = sigma[3] = sigma[z]

"Pauli gates"

 

Physics:-`*`(Physics:-Ket(q0), Physics:-Bra(q0))+Physics:-`*`(Physics:-Ket(q1), Physics:-Bra(q1))

 

Physics:-`*`(Physics:-Ket(q1), Physics:-Bra(q0))+Physics:-`*`(Physics:-Ket(q0), Physics:-Bra(q1))

 

-I*Physics:-`*`(Physics:-Ket(q1), Physics:-Bra(q0))+I*Physics:-`*`(Physics:-Ket(q0), Physics:-Bra(q1))

 

Physics:-`*`(Physics:-Ket(q0), Physics:-Bra(q0))-Physics:-`*`(Physics:-Ket(q1), Physics:-Bra(q1))

(4)

##############################
# Defining the Hadamard gate #
##############################
print("Hadamard gate");
H:= Ket(q0)*Bra(q0)/sqrt(2)+Ket(q0)*Bra(q1)/sqrt(2)+Ket(q1)*Bra(q0)/sqrt(2)-Ket(q1)*Bra(q1)/sqrt(2);

"Hadamard gate"

 

(1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(q0), Physics:-Bra(q0))+(1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(q0), Physics:-Bra(q1))+(1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(q1), Physics:-Bra(q0))-(1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(q1), Physics:-Bra(q1))

(5)

# This is usefull to represent a 2 qubits system
# A more general approach is needed for a n qubit system.
DefineStates:=proc()
    Ket(q00):=Ket(q0)*Ket(q0);  Ket(q01):=Ket(q0)*Ket(q1);
    Ket(q10):=Ket(q1)*Ket(q0);  Ket(q11):=Ket(q1)*Ket(q1);
    Bra(q00):=Dagger(Ket(q00)); Bra(q01):=Dagger(Ket(q01));
    Bra(q10):=Dagger(Ket(q10)); Bra(q11):=Dagger(Ket(q11));
    return;
    end proc:
UndefineStates:=proc()
    Ket(q00):='Ket(q00)'; Ket(q01):='Ket(q01)';
    Ket(q10):='Ket(q10)'; Ket(q11):='Ket(q11)';
    Bra(q00):='Bra(q00)'; Bra(q01):='Bra(q01)';
    Bra(q10):='Bra(q10)'; Bra(q11):='Bra(q11)';
    return;
    end proc:

####################################
# Defining the CNOT gate (2 qubits)
####################################
print("CNOT gate");
CNOT:=Ket(q00)*Bra(q00)+ Ket(q01)*Bra(q01)+ Ket(q11)*Bra(q10)+Ket(q10)*Bra(q11);
DefineStates();
'CNOT'=CNOT;

"CNOT gate"

 

Physics:-`*`(Physics:-Ket(q00), Physics:-Bra(q00))+Physics:-`*`(Physics:-Ket(q01), Physics:-Bra(q01))+Physics:-`*`(Physics:-Ket(q11), Physics:-Bra(q10))+Physics:-`*`(Physics:-Ket(q10), Physics:-Bra(q11))

 

CNOT = Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0), Physics:-Bra(q0), Physics:-Bra(q0))+Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1), Physics:-Bra(q1), Physics:-Bra(q0))+Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1), Physics:-Bra(q0), Physics:-Bra(q1))+Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0), Physics:-Bra(q1), Physics:-Bra(q1))

(6)

###########################
# Defining the Bell states
###########################
Ket(beta,x,y)='CNOT.(((H.Ket(x)))*Ket(y))';
Ket(beta00):=CNOT.(Expand((H.Ket(q0)))*Ket(q0));
Ket(beta01):=CNOT.(Expand((H.Ket(q0)))*Ket(q1));
Ket(beta10):=CNOT.(Expand((H.Ket(q1)))*Ket(q0));
Ket(beta11):=CNOT.(Expand((H.Ket(q1)))*Ket(q1));

Physics:-Ket(beta, x, y) = Physics:-`.`(CNOT, Physics:-`*`(Physics:-`.`(H, Physics:-Ket(x)), Physics:-Ket(y)))

 

(1/2)*2^(1/2)*(Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0))+Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1)))

 

(1/2)*2^(1/2)*(Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1))+Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0)))

 

-(1/2)*2^(1/2)*(-Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0))+Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1)))

 

(1/2)*2^(1/2)*(Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1))-Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0)))

(7)

##########################################################
# Quantum teleportation
# Reference: Quantum Computation and Quantum Information
#            10th Anniversary Edition
#            Michael A. Nielsen & Isaac L. Chuang
#            Cambridge University Press, Cambridge 2010
#            pp 25-28
##########################################################
print("State to be teleported");
Ket(psi) := a*Ket(q0)+b*Ket(q1);
print("Step 1: Compute the tensor product of the state to be teleported with ", 'Ket(beta00)');
Ket(psi[0])='Ket(psi)'*'Ket(beta00)';
Ket(psi[0]):=Expand(Ket(psi)*Ket(beta00));
print("This is a 3 qubits state");
#######
print("Step 2: Pass these 3 qubits through a  CNOT*I  operator");
'CnotI'='CNOT*I';
CnotI:=ExpandQop(Expand(CNOT*I)):
#
# To see what the CNOTI operator looks like
#
# print("CNOTI=");
# print(op(1,CNOTI)+op(2,CNOTI)+op(3,CNOTI)+op(4,CNOTI));
# print(op(5,CNOTI)+op(6,CNOTI)+op(7,CNOTI)+op(8,CNOTI));
'Ket(psi[1])'='CnotI.Ket(psi[0])';
Ket(psi[1]):=Expand(CnotI.Ket(psi[0]));
#######
print("Step 3: Pass these 3 qubits through an Haldamard*I  operator");
'HalI'='H*I';
HalI:=ExpandQop(Expand(H*I)):
#
# To see what the Haldamard*I operator looks like
#
# print("HalI=");
# print(op(1,HalI)+op(2,HalI)+op(3,HalI)+op(4,HalI));
# print(op(5,HalI)+op(6,HalI)+op(7,HalI)+op(8,HalI));
'Ket(psi[2])'='HalI.Ket(psi[1])';
Ket(psi[2]):=Expand(HalI.Ket(psi[1]));
 

"State to be teleported"

 

a*Physics:-Ket(q0)+b*Physics:-Ket(q1)

 

"Step 1: Compute the tensor product of the state to be teleported with ", Physics:-Ket(beta00)

 

Physics:-Ket(psi[0]) = Physics:-`*`(Physics:-Ket(psi), Physics:-Ket(beta00))

 

(1/2)*2^(1/2)*a*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0), Physics:-Ket(q0))+(1/2)*2^(1/2)*a*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1), Physics:-Ket(q1))+(1/2)*2^(1/2)*b*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0), Physics:-Ket(q0))+(1/2)*2^(1/2)*b*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1), Physics:-Ket(q1))

 

"This is a 3 qubits state"

 

"Step 2: Pass these 3 qubits through a  CNOT*I  operator"

 

CnotI = Physics:-`*`(CNOT, I)

 

Physics:-Ket(psi[1]) = Physics:-`.`(CnotI, Physics:-Ket(psi[0]))

 

(1/2)*2^(1/2)*a*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0), Physics:-Ket(q0))+(1/2)*2^(1/2)*a*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1), Physics:-Ket(q1))+(1/2)*2^(1/2)*b*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1), Physics:-Ket(q0))+(1/2)*2^(1/2)*b*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0), Physics:-Ket(q1))

 

"Step 3: Pass these 3 qubits through an Haldamard*I  operator"

 

HalI = Physics:-`*`(H, I)

 

Physics:-Ket(psi[2]) = Physics:-`.`(HalI, Physics:-Ket(psi[1]))

 

(1/2)*a*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0), Physics:-Ket(q0))+(1/2)*a*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1), Physics:-Ket(q1))+(1/2)*b*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q0), Physics:-Ket(q1))+(1/2)*b*Physics:-`*`(Physics:-Ket(q0), Physics:-Ket(q1), Physics:-Ket(q0))+(1/2)*a*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0), Physics:-Ket(q0))+(1/2)*a*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1), Physics:-Ket(q1))-(1/2)*b*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q0), Physics:-Ket(q1))-(1/2)*b*Physics:-`*`(Physics:-Ket(q1), Physics:-Ket(q1), Physics:-Ket(q0))

(8)

UndefineStates();
print("Using contracted names for the first two qubits");
Ket(q00)*Bra(q0)*Bra(q0)='I';
Ket(q01)*Bra(q0)*Bra(q1)='I';
Ket(q10)*Bra(q1)*Bra(q0)='I';
Ket(q11)*Bra(q1)*Bra(q1)='I';
'Ket(psi[2])'=Ket(q00)*Bra(q0)*Bra(q0).Ket(psi[2])+
              Ket(q01)*Bra(q0)*Bra(q1).Ket(psi[2])+
              Ket(q10)*Bra(q1)*Bra(q0).Ket(psi[2])+
              Ket(q11)*Bra(q1)*Bra(q1).Ket(psi[2]);

"Using contracted names for the first two qubits"

 

Physics:-`*`(Physics:-Ket(q00), Physics:-Bra(q0), Physics:-Bra(q0)) = I

 

Physics:-`*`(Physics:-Ket(q01), Physics:-Bra(q0), Physics:-Bra(q1)) = I

 

Physics:-`*`(Physics:-Ket(q10), Physics:-Bra(q1), Physics:-Bra(q0)) = I

 

Physics:-`*`(Physics:-Ket(q11), Physics:-Bra(q1), Physics:-Bra(q1)) = I

 

Physics:-Ket(psi[2]) = (1/2)*a*Physics:-`*`(Physics:-Ket(q00), Physics:-Ket(q0))+(1/2)*b*Physics:-`*`(Physics:-Ket(q00), Physics:-Ket(q1))+(1/2)*a*Physics:-`*`(Physics:-Ket(q01), Physics:-Ket(q0))-(1/2)*b*Physics:-`*`(Physics:-Ket(q01), Physics:-Ket(q1))+(1/2)*a*Physics:-`*`(Physics:-Ket(q10), Physics:-Ket(q1))+(1/2)*b*Physics:-`*`(Physics:-Ket(q10), Physics:-Ket(q0))+(1/2)*a*Physics:-`*`(Physics:-Ket(q11), Physics:-Ket(q1))-(1/2)*b*Physics:-`*`(Physics:-Ket(q11), Physics:-Ket(q0))

(9)

print("Rewriting this result by hand");
'Ket(psi[2])'=(Ket(q00)*(a*Ket(q0)+b*Ket(q1))+
               Ket(q01)*(a*Ket(q0)-b*Ket(q1))+
               Ket(q10)*(a*Ket(q1)+b*Ket(q0))+
               Ket(q11)*(a*Ket(q1)-b*Ket(q0)))/2;

"Rewriting this result by hand"

 

Physics:-Ket(psi[2]) = (1/2)*Physics:-`*`(Physics:-Ket(q00), a*Physics:-Ket(q0)+b*Physics:-Ket(q1))+(1/2)*Physics:-`*`(Physics:-Ket(q01), a*Physics:-Ket(q0)-b*Physics:-Ket(q1))+(1/2)*Physics:-`*`(Physics:-Ket(q10), a*Physics:-Ket(q1)+b*Physics:-Ket(q0))+(1/2)*Physics:-`*`(Physics:-Ket(q11), a*Physics:-Ket(q1)-b*Physics:-Ket(q0))

(10)

DefineStates();
print("If Alice measures 00 Bob does noting");
''I'.   '2*Bra(q00).Ket(psi[2])'' =  I.   2*Bra(q00).Ket(psi[2]);
print("If Alice measures 01 Bob applies the X gate");
''X'.   '2*Bra(q01).Ket(psi[2])'' =  X.   2*Bra(q01).Ket(psi[2]);
print("If Alice measures 10 Bob applies the Z gate");
''Z'.   '2*Bra(q10).Ket(psi[2])'' =  Z.   2*Bra(q10).Ket(psi[2]);
print("If Alice measures 11 Bob applies the X gate and then the Z gate");
''Z'.'X'. '2*Bra(q11).Ket(psi[2])'' =  Z.X. 2*Bra(q11).Ket(psi[2]);

"If Alice measures 00 Bob does noting"

 

Physics:-`.`('I', 'Physics:-`.`(Physics:-`*`(2, Physics:-Bra(q00)), Physics:-Ket(psi[2]))') = a*Physics:-Ket(q0)+b*Physics:-Ket(q1)

 

"If Alice measures 01 Bob applies the X gate"

 

Physics:-`.`('X', 'Physics:-`.`(Physics:-`*`(2, Physics:-Bra(q01)), Physics:-Ket(psi[2]))') = a*Physics:-Ket(q0)+b*Physics:-Ket(q1)

 

"If Alice measures 10 Bob applies the Z gate"

 

Physics:-`.`('Z', 'Physics:-`.`(Physics:-`*`(2, Physics:-Bra(q10)), Physics:-Ket(psi[2]))') = a*Physics:-Ket(q0)+b*Physics:-Ket(q1)

 

"If Alice measures 11 Bob applies the X gate and then the Z gate"

 

Physics:-`.`('Z', 'X', 'Physics:-`.`(Physics:-`*`(2, Physics:-Bra(q11)), Physics:-Ket(psi[2]))') = a*Physics:-Ket(q0)+b*Physics:-Ket(q1)

(11)

 


 

Download QuantumTeleportation.mw

 

 


 

restart

with(LinearAlgebra):

with(orthopoly):

with(student):

interface(rtablesize = 100)

10

(1)

alpha := 1; 1; beta := 1; 1; N := 2; 1; M := 2; 1; L := 1; 1; X := 2*x/L-1; 1; T := 2*t/L-1; 1; `&varkappa;` := 3; 1; epsilon := 4; 1; delta := 2; 1; tau := 5; 1; B := 1; 1; c := 1; 1; sigma := 1

1

 

1

 

2

 

2

 

1

 

2*x-1

 

2*t-1

 

3

 

4

 

2

 

5

 

1

 

1

 

1

(2)

``

u := expand(sum(sum(a[s, k]*P(s, T)*P(k, X), k = 0 .. M), s = 0 .. N));

4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t

(3)

v := expand(sum(sum(b[s, k]*P(s, T)*P(k, X), k = 0 .. M), s = 0 .. N));

4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x

(4)

eq := diff(u, t)-v*(1-v)+c*u*v/(v+u)-`&varkappa;`*(diff(u, x, x))

-(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)*(1-4*b[1, 1]*t*x-12*b[1, 2]*t*x^2-2*b[0, 1]*x-6*b[0, 2]*x^2+6*b[0, 2]*x-2*b[1, 0]*t+2*b[1, 1]*t+2*b[1, 1]*x-2*b[1, 2]*t+6*b[1, 2]*x^2-6*b[1, 2]*x-6*b[2, 0]*t^2+6*b[2, 0]*t-2*b[2, 1]*x+6*b[2, 1]*t^2-6*b[2, 1]*t-6*b[2, 2]*x^2+6*b[2, 2]*x-6*b[2, 2]*t^2+6*b[2, 2]*t-b[0, 0]+b[0, 1]-b[0, 2]+b[1, 0]-b[1, 1]+b[1, 2]-b[2, 0]+b[2, 1]-b[2, 2]-36*b[2, 2]*t^2*x^2+12*b[1, 2]*t*x-12*b[2, 1]*t^2*x-36*b[2, 2]*t*x+36*b[2, 2]*t*x^2+36*b[2, 2]*t^2*x+12*b[2, 1]*t*x)+(4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t)*(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)/(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x+4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x-12*b[2, 1]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t)+24*a[2, 1]*t*x+72*a[2, 2]*t*x^2-72*a[2, 2]*t*x-36*a[0, 2]+2*a[1, 0]-2*a[1, 1]+38*a[1, 2]-6*a[2, 0]+6*a[2, 1]-42*a[2, 2]+4*a[1, 1]*x-72*a[1, 2]*t+12*a[1, 2]*x^2-12*a[1, 2]*x+12*a[2, 0]*t-12*a[2, 1]*x-12*a[2, 1]*t-36*a[2, 2]*x^2+36*a[2, 2]*x-216*a[2, 2]*t^2+228*a[2, 2]*t

(5)

eq2 := diff(v, t)-epsilon*v*(-(tau+delta*B*v)/(1+B*v)+u/(v+u))-sigma*(diff(v, x, x))

-4*(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)*(-(5+8*b[1, 1]*t*x+24*b[1, 2]*t*x^2+4*b[0, 1]*x+12*b[0, 2]*x^2-12*b[0, 2]*x+4*b[1, 0]*t-4*b[1, 1]*t-4*b[1, 1]*x+4*b[1, 2]*t-12*b[1, 2]*x^2+12*b[1, 2]*x+12*b[2, 0]*t^2-12*b[2, 0]*t+4*b[2, 1]*x-12*b[2, 1]*t^2+12*b[2, 1]*t+12*b[2, 2]*x^2-12*b[2, 2]*x+12*b[2, 2]*t^2-12*b[2, 2]*t+2*b[0, 0]-2*b[0, 1]+2*b[0, 2]-2*b[1, 0]+2*b[1, 1]-2*b[1, 2]+2*b[2, 0]-2*b[2, 1]+2*b[2, 2]+72*b[2, 2]*t^2*x^2-24*b[1, 2]*t*x+24*b[2, 1]*t^2*x+72*b[2, 2]*t*x-72*b[2, 2]*t*x^2-72*b[2, 2]*t^2*x-24*b[2, 1]*t*x)/(1+4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x-12*b[2, 1]*t*x)+(4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t)/(4*b[1, 1]*t*x+12*b[1, 2]*t*x^2+2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x+2*b[1, 0]*t-2*b[1, 1]*t-2*b[1, 1]*x+2*b[1, 2]*t-6*b[1, 2]*x^2+6*b[1, 2]*x+6*b[2, 0]*t^2-6*b[2, 0]*t+2*b[2, 1]*x-6*b[2, 1]*t^2+6*b[2, 1]*t+6*b[2, 2]*x^2-6*b[2, 2]*x+6*b[2, 2]*t^2-6*b[2, 2]*t+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t^2*x^2-12*b[1, 2]*t*x+12*b[2, 1]*t^2*x+36*b[2, 2]*t*x-36*b[2, 2]*t*x^2-36*b[2, 2]*t^2*x+4*a[1, 1]*t*x+12*a[1, 2]*t*x^2-12*a[1, 2]*t*x+12*a[2, 1]*t^2*x-12*a[2, 1]*t*x+36*a[2, 2]*t^2*x^2-36*a[2, 2]*t^2*x-36*a[2, 2]*t*x^2+36*a[2, 2]*t*x-12*b[2, 1]*t*x+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x+2*a[1, 0]*t-2*a[1, 1]*t-2*a[1, 1]*x+2*a[1, 2]*t-6*a[1, 2]*x^2+6*a[1, 2]*x+6*a[2, 0]*t^2-6*a[2, 0]*t+2*a[2, 1]*x-6*a[2, 1]*t^2+6*a[2, 1]*t+6*a[2, 2]*x^2-6*a[2, 2]*x+6*a[2, 2]*t^2-6*a[2, 2]*t))+4*b[1, 1]*x-24*b[1, 2]*t+12*b[1, 2]*x^2-12*b[1, 2]*x+12*b[2, 0]*t-12*b[2, 1]*x-12*b[2, 1]*t-36*b[2, 2]*x^2+36*b[2, 2]*x-72*b[2, 2]*t^2+84*b[2, 2]*t-12*b[0, 2]+2*b[1, 0]-2*b[1, 1]+14*b[1, 2]-6*b[2, 0]+6*b[2, 1]-18*b[2, 2]-72*b[2, 2]*t*x+72*b[2, 2]*t*x^2+24*b[2, 1]*t*x

(6)

eq3 := subs({x = 0}, diff(u, x))

4*a[1, 1]*t-12*a[1, 2]*t+12*a[2, 1]*t^2-12*a[2, 1]*t-36*a[2, 2]*t^2+36*a[2, 2]*t+2*a[0, 1]-6*a[0, 2]-2*a[1, 1]+6*a[1, 2]+2*a[2, 1]-6*a[2, 2]

(7)

eq4 := subs({x = L}, diff(u, x))

4*a[1, 1]*t+12*a[1, 2]*t+12*a[2, 1]*t^2-12*a[2, 1]*t+36*a[2, 2]*t^2-36*a[2, 2]*t+2*a[0, 1]+6*a[0, 2]-2*a[1, 1]-6*a[1, 2]+2*a[2, 1]+6*a[2, 2]

(8)

eq5 := subs({x = 0}, diff(v, x))

4*b[1, 1]*t+2*b[0, 1]-6*b[0, 2]-2*b[1, 1]+6*b[1, 2]+2*b[2, 1]-6*b[2, 2]-12*b[1, 2]*t+12*b[2, 1]*t^2+36*b[2, 2]*t-36*b[2, 2]*t^2-12*b[2, 1]*t

(9)

eq6 := subs({x = L}, diff(v, x))

4*b[1, 1]*t+12*b[1, 2]*t+2*b[0, 1]+6*b[0, 2]-2*b[1, 1]-6*b[1, 2]+2*b[2, 1]+6*b[2, 2]+36*b[2, 2]*t^2+12*b[2, 1]*t^2-36*b[2, 2]*t-12*b[2, 1]*t

(10)

eq7 := subs({t = 0}, u)

a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x+6*a[0, 2]*x^2-6*a[0, 2]*x-2*a[1, 1]*x-6*a[1, 2]*x^2+6*a[1, 2]*x+2*a[2, 1]*x+6*a[2, 2]*x^2-6*a[2, 2]*x

(11)

eq8 := subs({t = 0}, v)

2*b[0, 1]*x+6*b[0, 2]*x^2-6*b[0, 2]*x-2*b[1, 1]*x-6*b[1, 2]*x^2+6*b[1, 2]*x+2*b[2, 1]*x+6*b[2, 2]*x^2-6*b[2, 2]*x+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]

(12)

eq11 := subs({t = t[j], x = x[i]}, eq)

-(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])*(1-2*b[0, 1]*x[i]-6*b[0, 2]*x[i]^2+6*b[0, 2]*x[i]-2*b[1, 0]*t[j]+2*b[1, 1]*t[j]+2*b[1, 1]*x[i]-2*b[1, 2]*t[j]+6*b[1, 2]*x[i]^2-6*b[1, 2]*x[i]-6*b[2, 0]*t[j]^2+6*b[2, 0]*t[j]-2*b[2, 1]*x[i]+6*b[2, 1]*t[j]^2-6*b[2, 1]*t[j]-6*b[2, 2]*x[i]^2+6*b[2, 2]*x[i]-6*b[2, 2]*t[j]^2+6*b[2, 2]*t[j]-b[0, 0]+b[0, 1]-b[0, 2]+b[1, 0]-b[1, 1]+b[1, 2]-b[2, 0]+b[2, 1]-b[2, 2]-36*b[2, 2]*t[j]*x[i]-36*b[2, 2]*t[j]^2*x[i]^2+36*b[2, 2]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]*x[i]+36*b[2, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]-4*b[1, 1]*t[j]*x[i])+(2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+12*a[1, 2]*t[j]*x[i]^2-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]-36*a[2, 2]*t[j]^2*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2)*(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])/(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2+12*a[1, 2]*t[j]*x[i]^2-36*b[2, 2]*t[j]^2*x[i]-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-36*a[2, 2]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2+4*b[1, 1]*t[j]*x[i])+24*a[2, 1]*t[j]*x[i]+72*a[2, 2]*t[j]*x[i]^2-72*a[2, 2]*t[j]*x[i]-36*a[0, 2]+2*a[1, 0]-2*a[1, 1]+38*a[1, 2]-6*a[2, 0]+6*a[2, 1]-42*a[2, 2]+4*a[1, 1]*x[i]-72*a[1, 2]*t[j]+12*a[1, 2]*x[i]^2-12*a[1, 2]*x[i]+12*a[2, 0]*t[j]-12*a[2, 1]*x[i]-12*a[2, 1]*t[j]-36*a[2, 2]*x[i]^2+36*a[2, 2]*x[i]-216*a[2, 2]*t[j]^2+228*a[2, 2]*t[j]

(13)

eq22 := subs({t = t[j], x = x[i]}, eq2)

-4*(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])*(-(5+4*b[0, 1]*x[i]+12*b[0, 2]*x[i]^2-12*b[0, 2]*x[i]+4*b[1, 0]*t[j]-4*b[1, 1]*t[j]-4*b[1, 1]*x[i]+4*b[1, 2]*t[j]-12*b[1, 2]*x[i]^2+12*b[1, 2]*x[i]+12*b[2, 0]*t[j]^2-12*b[2, 0]*t[j]+4*b[2, 1]*x[i]-12*b[2, 1]*t[j]^2+12*b[2, 1]*t[j]+12*b[2, 2]*x[i]^2-12*b[2, 2]*x[i]+12*b[2, 2]*t[j]^2-12*b[2, 2]*t[j]+2*b[0, 0]-2*b[0, 1]+2*b[0, 2]-2*b[1, 0]+2*b[1, 1]-2*b[1, 2]+2*b[2, 0]-2*b[2, 1]+2*b[2, 2]+72*b[2, 2]*t[j]*x[i]+72*b[2, 2]*t[j]^2*x[i]^2-72*b[2, 2]*t[j]^2*x[i]+24*b[1, 2]*t[j]*x[i]^2-24*b[2, 1]*t[j]*x[i]-72*b[2, 2]*t[j]*x[i]^2+24*b[2, 1]*t[j]^2*x[i]-24*b[1, 2]*t[j]*x[i]+8*b[1, 1]*t[j]*x[i])/(1+2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2-36*b[2, 2]*t[j]^2*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+4*b[1, 1]*t[j]*x[i])+(2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+12*a[1, 2]*t[j]*x[i]^2-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]-36*a[2, 2]*t[j]^2*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2)/(2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]+2*b[1, 0]*t[j]-2*b[1, 1]*t[j]-2*b[1, 1]*x[i]+2*b[1, 2]*t[j]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+6*b[2, 0]*t[j]^2-6*b[2, 0]*t[j]+2*b[2, 1]*x[i]-6*b[2, 1]*t[j]^2+6*b[2, 1]*t[j]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+6*b[2, 2]*t[j]^2-6*b[2, 2]*t[j]+2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]+2*a[1, 0]*t[j]-2*a[1, 1]*t[j]-2*a[1, 1]*x[i]+2*a[1, 2]*t[j]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+6*a[2, 0]*t[j]^2-6*a[2, 0]*t[j]+2*a[2, 1]*x[i]-6*a[2, 1]*t[j]^2+6*a[2, 1]*t[j]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]+6*a[2, 2]*t[j]^2-6*a[2, 2]*t[j]+4*a[1, 1]*t[j]*x[i]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]+a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+36*a[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]*x[i]+36*b[2, 2]*t[j]^2*x[i]^2+12*a[1, 2]*t[j]*x[i]^2-36*b[2, 2]*t[j]^2*x[i]-36*a[2, 2]*t[j]*x[i]^2-12*a[1, 2]*t[j]*x[i]+12*b[1, 2]*t[j]*x[i]^2-12*b[2, 1]*t[j]*x[i]-36*b[2, 2]*t[j]*x[i]^2+12*b[2, 1]*t[j]^2*x[i]-36*a[2, 2]*t[j]^2*x[i]-12*b[1, 2]*t[j]*x[i]+12*a[2, 1]*t[j]^2*x[i]-12*a[2, 1]*t[j]*x[i]+36*a[2, 2]*t[j]^2*x[i]^2+4*b[1, 1]*t[j]*x[i]))+4*b[1, 1]*x[i]-24*b[1, 2]*t[j]+12*b[1, 2]*x[i]^2-12*b[1, 2]*x[i]+12*b[2, 0]*t[j]-12*b[2, 1]*x[i]-12*b[2, 1]*t[j]-36*b[2, 2]*x[i]^2+36*b[2, 2]*x[i]-72*b[2, 2]*t[j]^2+84*b[2, 2]*t[j]-12*b[0, 2]+2*b[1, 0]-2*b[1, 1]+14*b[1, 2]-6*b[2, 0]+6*b[2, 1]-18*b[2, 2]-72*b[2, 2]*t[j]*x[i]+72*b[2, 2]*t[j]*x[i]^2+24*b[2, 1]*t[j]*x[i]

(14)

eq33 := subs({t = t[j], x = x[i]}, eq3)

4*a[1, 1]*t[j]-12*a[1, 2]*t[j]+12*a[2, 1]*t[j]^2-12*a[2, 1]*t[j]-36*a[2, 2]*t[j]^2+36*a[2, 2]*t[j]+2*a[0, 1]-6*a[0, 2]-2*a[1, 1]+6*a[1, 2]+2*a[2, 1]-6*a[2, 2]

(15)

eq44 := subs({t = t[j], x = x[i]}, eq4)

4*a[1, 1]*t[j]+12*a[1, 2]*t[j]+12*a[2, 1]*t[j]^2-12*a[2, 1]*t[j]+36*a[2, 2]*t[j]^2-36*a[2, 2]*t[j]+2*a[0, 1]+6*a[0, 2]-2*a[1, 1]-6*a[1, 2]+2*a[2, 1]+6*a[2, 2]

(16)

eq55 := subs({t = t[j], x = x[i]}, eq5)

4*b[1, 1]*t[j]+2*b[0, 1]-6*b[0, 2]-2*b[1, 1]+6*b[1, 2]+2*b[2, 1]-6*b[2, 2]-12*b[1, 2]*t[j]+12*b[2, 1]*t[j]^2+36*b[2, 2]*t[j]-36*b[2, 2]*t[j]^2-12*b[2, 1]*t[j]

(17)

eq66 := subs({t = t[j], x = x[i]}, eq6)

4*b[1, 1]*t[j]+12*b[1, 2]*t[j]+2*b[0, 1]+6*b[0, 2]-2*b[1, 1]-6*b[1, 2]+2*b[2, 1]+6*b[2, 2]+36*b[2, 2]*t[j]^2+12*b[2, 1]*t[j]^2-36*b[2, 2]*t[j]-12*b[2, 1]*t[j]

(18)

eq77 := subs({t = t[j], x = x[i]}, eq7)

a[0, 0]-a[0, 1]+a[0, 2]-a[1, 0]+a[1, 1]-a[1, 2]+a[2, 0]-a[2, 1]+a[2, 2]+2*a[0, 1]*x[i]+6*a[0, 2]*x[i]^2-6*a[0, 2]*x[i]-2*a[1, 1]*x[i]-6*a[1, 2]*x[i]^2+6*a[1, 2]*x[i]+2*a[2, 1]*x[i]+6*a[2, 2]*x[i]^2-6*a[2, 2]*x[i]

(19)

eq88 := subs({t = t[j], x = x[i]}, eq8)

2*b[0, 1]*x[i]+6*b[0, 2]*x[i]^2-6*b[0, 2]*x[i]-2*b[1, 1]*x[i]-6*b[1, 2]*x[i]^2+6*b[1, 2]*x[i]+2*b[2, 1]*x[i]+6*b[2, 2]*x[i]^2-6*b[2, 2]*x[i]+b[0, 0]-b[0, 1]+b[0, 2]-b[1, 0]+b[1, 1]-b[1, 2]+b[2, 0]-b[2, 1]+b[2, 2]

(20)

``

X1 := evalf(fsolve((1-(2*x-1)^2)*(diff(P(N, X), x)))):

0.

 

.5000000000

 

1.

(21)

T1 := evalf(fsolve(P(M, T))):

.2113248654

 

.7886751346

(22)

printlevel := 4;

4

(23)

``

(24)

for i to M-1 do for j from 0 to N-1 do s[i, j] := simplify(evalf(eq11)) end do end do;

-0.4000000000e-19*(0.8333333339e29*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e21*b[0, 0]*b[1, 0]*a[2, 0]+0.2500000000e30*b[0, 0]^2-0.2500000000e30*b[0, 0]*b[0, 2]-0.2886751346e30*b[0, 0]*b[1, 0]+0.1443375675e30*b[0, 0]*b[1, 2]+0.2000000000e21*b[0, 0]*b[2, 0]+0.1000000000e21*b[0, 0]*b[2, 1]-0.3750000000e21*b[0, 0]*b[2, 2]+0.6250000000e29*b[0, 2]^2+0.1443375673e30*b[0, 2]*b[1, 0]-0.7216878375e29*b[0, 2]*b[1, 2]-0.1000000000e21*b[0, 2]*b[2, 0]-0.5000000000e20*b[0, 2]*b[2, 1]+0.1875000000e21*b[0, 2]*b[2, 2]+0.8333333334e29*b[1, 0]^2-0.8333333345e29*b[1, 0]*b[1, 2]-0.1154700538e21*b[1, 0]*b[2, 0]-0.5773502692e20*b[1, 0]*b[2, 1]+0.2165063510e21*b[1, 0]*b[2, 2]+0.2083333339e29*b[1, 2]^2+0.5773502700e20*b[1, 2]*b[2, 0]+0.2886751350e20*b[1, 2]*b[2, 1]-0.1082531756e21*b[1, 2]*b[2, 2]+0.4000000000e11*b[2, 0]^2+0.4000000000e11*b[2, 0]*b[2, 1]-0.1500000000e12*b[2, 0]*b[2, 2]-0.5000000000e11*b[2, 1]*b[2, 2]+0.1250000000e12*b[2, 2]^2+0.9000000000e31*b[0, 0]*a[0, 2]-0.5000000000e30*b[0, 0]*a[1, 0]-0.4946152423e31*b[0, 0]*a[1, 2]+0.8660254038e30*b[0, 0]*a[2, 0]-0.4500000000e31*b[0, 2]*a[0, 2]+0.2500000000e30*b[0, 2]*a[1, 0]+0.2473076211e31*b[0, 2]*a[1, 2]-0.4330127019e30*b[0, 2]*a[2, 0]-0.5196152423e31*b[1, 0]*a[0, 2]+0.2886751346e30*b[1, 0]*a[1, 0]-0.5000000000e30*b[1, 0]*a[2, 0]+0.2598076215e31*b[1, 2]*a[0, 2]-0.1443375675e30*b[1, 2]*a[1, 0]-0.1427831218e31*b[1, 2]*a[1, 2]+0.2500000004e30*b[1, 2]*a[2, 0]+0.3600000000e22*b[2, 0]*a[0, 2]-0.2000000000e21*b[2, 0]*a[1, 0]-0.1978460969e22*b[2, 0]*a[1, 2]+0.3464101615e21*b[2, 0]*a[2, 0]-0.2000000000e11*b[2, 1]*a[1, 2]+0.4000000000e11*b[2, 1]*a[2, 0]-0.4500000000e22*b[2, 2]*a[0, 2]+0.2500000000e21*b[2, 2]*a[1, 0]+0.2473076211e22*b[2, 2]*a[1, 2]-0.4330127020e21*b[2, 2]*a[2, 0]+0.3750000000e30*b[0, 0]^2*b[0, 2]+0.4330127019e30*b[0, 0]^2*b[1, 0]-0.2165063512e30*b[0, 0]^2*b[1, 2]-0.3000000000e21*b[0, 0]^2*b[2, 0]+0.6250000000e21*b[0, 0]^2*b[2, 2]-0.2500000000e30*b[0, 0]^2*a[0, 0]+0.1250000000e30*b[0, 0]^2*a[0, 2]+0.1443375673e30*b[0, 0]^2*a[1, 0]-0.7216878370e29*b[0, 0]^2*a[1, 2]-0.1000000000e21*b[0, 0]^2*a[2, 0]-0.1875000000e30*b[0, 0]*b[0, 2]^2-0.2500000000e30*b[0, 0]*b[1, 0]^2-0.6250000018e29*b[0, 0]*b[1, 2]^2-0.1200000000e12*b[0, 0]*b[2, 0]^2-0.2000000000e21*b[0, 0]^2*b[2, 1]-0.5000000000e12*b[0, 0]*b[2, 2]^2+0.1082531755e30*b[0, 2]^2*b[1, 0]-0.5412658781e29*b[0, 2]^2*b[1, 2]-0.7500000000e20*b[0, 2]^2*b[2, 0]+0.1562500000e21*b[0, 2]^2*b[2, 2]-0.6250000000e29*b[0, 2]^2*a[0, 0]+0.3125000000e29*b[0, 2]^2*a[0, 2]+0.3608439182e29*b[0, 2]^2*a[1, 0]-0.1804219592e29*b[0, 2]^2*a[1, 2]-0.2500000000e20*b[0, 2]^2*a[2, 0]+0.1250000000e30*b[0, 2]*b[1, 0]^2+0.3125000009e29*b[0, 2]*b[1, 2]^2+0.6000000000e11*b[0, 2]*b[2, 0]^2-0.5000000000e20*b[0, 2]^2*b[2, 1]+0.2500000000e12*b[0, 2]*b[2, 2]^2-0.7216878375e29*b[1, 0]^2*b[1, 2]-0.1000000000e21*b[1, 0]^2*b[2, 0]+0.2083333333e21*b[1, 0]^2*b[2, 2]-0.8333333334e29*b[1, 0]^2*a[0, 0]+0.4166666667e29*b[1, 0]^2*a[0, 2]+0.4811252244e29*b[1, 0]^2*a[1, 0]-0.2405626123e29*b[1, 0]^2*a[1, 2]-0.3333333333e20*b[1, 0]^2*a[2, 0]+0.3608439193e29*b[1, 0]*b[1, 2]^2+0.6928203230e11*b[1, 0]*b[2, 0]^2-0.6666666667e20*b[1, 0]^2*b[2, 1]+0.2886751346e12*b[1, 0]*b[2, 2]^2-0.2500000007e20*b[1, 2]^2*b[2, 0]+0.5208333348e20*b[1, 2]^2*b[2, 2]-0.2083333339e29*b[1, 2]^2*a[0, 0]+0.1041666670e29*b[1, 2]^2*a[0, 2]+0.1202813064e29*b[1, 2]^2*a[1, 0]-0.6014065325e28*b[1, 2]^2*a[1, 2]-0.8333333357e19*b[1, 2]^2*a[2, 0]-0.3464101620e11*b[1, 2]*b[2, 0]^2-0.1666666671e20*b[1, 2]^2*b[2, 1]-0.1443375675e12*b[1, 2]*b[2, 2]^2+100.*b[2, 0]^2*b[2, 2]-0.4000000000e11*b[2, 0]^2*a[0, 0]+0.2000000000e11*b[2, 0]^2*a[0, 2]+0.2309401077e11*b[2, 0]^2*a[1, 0]-0.1154700539e11*b[2, 0]^2*a[1, 2]-16.*b[2, 0]^2*a[2, 0]-32.*b[2, 0]^2*b[2, 1]-200.*b[2, 0]*b[2, 2]^2-0.4000000000e11*b[2, 1]^2*b[0, 0]+0.2000000000e11*b[2, 1]^2*b[0, 2]+0.2309401077e11*b[2, 1]^2*b[1, 0]-0.1154700540e11*b[2, 1]^2*b[1, 2]-16.*b[2, 1]^2*b[2, 0]+20.*b[2, 1]^2*b[2, 2]-0.4000000000e11*b[2, 1]^2*a[0, 0]+0.2000000000e11*b[2, 1]^2*a[0, 2]+0.2309401077e11*b[2, 1]^2*a[1, 0]-0.1154700539e11*b[2, 1]^2*a[1, 2]-16.*b[2, 1]^2*a[2, 0]-100.*b[2, 1]*b[2, 2]^2-0.2500000000e30*b[0, 0]^3+0.3125000000e29*b[0, 2]^3+0.4811252244e29*b[1, 0]^3-0.6014065329e28*b[1, 2]^3-16.*b[2, 0]^3+125.*b[2, 2]^3+0.2855662433e31*b[1, 0]*a[1, 2]-0.1732050810e21*b[0, 0]*b[1, 2]*b[2, 0]+0.3608439188e21*b[0, 0]*b[1, 2]*b[2, 2]-0.1443375675e30*b[0, 0]*b[1, 2]*a[0, 0]+0.7216878375e29*b[0, 0]*b[1, 2]*a[0, 2]+0.8333333345e29*b[0, 0]*b[1, 2]*a[1, 0]-0.4166666675e29*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502700e20*b[0, 0]*b[1, 2]*a[2, 0]+0.5000000000e12*b[0, 0]*b[2, 0]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 0]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 0]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 0]*a[2, 0]+0.2000000000e21*b[0, 0]*b[2, 1]*b[0, 2]+0.2309401077e21*b[0, 0]*b[2, 1]*b[1, 0]-0.1154700540e21*b[0, 0]*b[2, 1]*b[1, 2]-0.1600000000e12*b[0, 0]*b[2, 1]*b[2, 0]+0.3000000000e12*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 1]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 1]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 1]*a[2, 0]+0.5000000000e21*b[0, 0]*b[2, 2]*a[0, 0]-0.2500000000e21*b[0, 0]*b[2, 2]*a[0, 2]-0.2886751346e21*b[0, 0]*b[2, 2]*a[1, 0]+0.1443375674e21*b[0, 0]*b[2, 2]*a[1, 2]+0.2000000000e12*b[0, 0]*b[2, 2]*a[2, 0]-0.1250000002e30*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050808e21*b[0, 2]*b[1, 0]*b[2, 0]+0.3608439182e21*b[0, 2]*b[1, 0]*b[2, 2]-0.1443375673e30*b[0, 2]*b[1, 0]*a[0, 0]+0.7216878365e29*b[0, 2]*b[1, 0]*a[0, 2]+0.8333333334e29*b[0, 2]*b[1, 0]*a[1, 0]-0.4166666670e29*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502692e20*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254050e20*b[0, 2]*b[1, 2]*b[2, 0]-0.1804219594e21*b[0, 2]*b[1, 2]*b[2, 2]+0.7216878375e29*b[0, 2]*b[1, 2]*a[0, 0]-0.3608439188e29*b[0, 2]*b[1, 2]*a[0, 2]-0.4166666673e29*b[0, 2]*b[1, 2]*a[1, 0]+0.2083333338e29*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751350e20*b[0, 2]*b[1, 2]*a[2, 0]-0.2500000000e12*b[0, 2]*b[2, 0]*b[2, 2]+0.1000000000e21*b[0, 2]*b[2, 0]*a[0, 0]-0.5000000000e20*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502692e20*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751348e20*b[0, 2]*b[2, 0]*a[1, 2]+0.4000000000e11*b[0, 2]*b[2, 0]*a[2, 0]-0.1154700538e21*b[0, 2]*b[2, 1]*b[1, 0]+0.5773502700e20*b[0, 2]*b[2, 1]*b[1, 2]+0.8000000000e11*b[0, 2]*b[2, 1]*b[2, 0]-0.1500000000e12*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e21*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e20*b[0, 2]*b[2, 1]*a[0, 2]-0.5773502692e20*b[0, 2]*b[2, 1]*a[1, 0]+0.2886751348e20*b[0, 2]*b[2, 1]*a[1, 2]+0.4000000000e11*b[0, 2]*b[2, 1]*a[2, 0]-0.2500000000e21*b[0, 2]*b[2, 2]*a[0, 0]+0.1250000000e21*b[0, 2]*b[2, 2]*a[0, 2]+0.1443375673e21*b[0, 2]*b[2, 2]*a[1, 0]-0.7216878370e20*b[0, 2]*b[2, 2]*a[1, 2]-0.1000000000e12*b[0, 2]*b[2, 2]*a[2, 0]+0.1000000001e21*b[1, 0]*b[1, 2]*b[2, 0]-0.2083333336e21*b[1, 0]*b[1, 2]*b[2, 2]+0.8333333345e29*b[1, 0]*b[1, 2]*a[0, 0]-0.4166666673e29*b[1, 0]*b[1, 2]*a[0, 2]-0.4811252250e29*b[1, 0]*b[1, 2]*a[1, 0]+0.2405626127e29*b[1, 0]*b[1, 2]*a[1, 2]+0.3333333338e20*b[1, 0]*b[1, 2]*a[2, 0]-0.2886751346e12*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e21*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502692e20*b[1, 0]*b[2, 0]*a[0, 2]-0.6666666667e20*b[1, 0]*b[2, 0]*a[1, 0]+0.3333333336e20*b[1, 0]*b[2, 0]*a[1, 2]+0.4618802154e11*b[1, 0]*b[2, 0]*a[2, 0]+0.6666666676e20*b[1, 0]*b[2, 1]*b[1, 2]+0.9237604307e11*b[1, 0]*b[2, 1]*b[2, 0]-0.1732050808e12*b[1, 0]*b[2, 1]*b[2, 2]+0.1154700538e21*b[1, 0]*b[2, 1]*a[0, 0]-0.5773502692e20*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666667e20*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333336e20*b[1, 0]*b[2, 1]*a[1, 2]+0.4618802154e11*b[1, 0]*b[2, 1]*a[2, 0]-0.2886751346e21*b[1, 0]*b[2, 2]*a[0, 0]+0.1443375673e21*b[1, 0]*b[2, 2]*a[0, 2]+0.1666666667e21*b[1, 0]*b[2, 2]*a[1, 0]-0.8333333339e20*b[1, 0]*b[2, 2]*a[1, 2]-0.1154700538e12*b[1, 0]*b[2, 2]*a[2, 0]+0.1443375675e12*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502700e20*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751350e20*b[1, 2]*b[2, 0]*a[0, 2]+0.3333333338e20*b[1, 2]*b[2, 0]*a[1, 0]-0.1666666670e20*b[1, 2]*b[2, 0]*a[1, 2]-0.2309401080e11*b[1, 2]*b[2, 0]*a[2, 0]-0.4618802160e11*b[1, 2]*b[2, 1]*b[2, 0]+0.8660254050e11*b[1, 2]*b[2, 1]*b[2, 2]-0.5773502700e20*b[1, 2]*b[2, 1]*a[0, 0]+0.2886751350e20*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333338e20*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666670e20*b[1, 2]*b[2, 1]*a[1, 2]-0.2309401080e11*b[1, 2]*b[2, 1]*a[2, 0]+0.1443375675e21*b[1, 2]*b[2, 2]*a[0, 0]-0.7216878375e20*b[1, 2]*b[2, 2]*a[0, 2]-0.8333333345e20*b[1, 2]*b[2, 2]*a[1, 0]+0.4166666675e20*b[1, 2]*b[2, 2]*a[1, 2]+0.5773502700e11*b[1, 2]*b[2, 2]*a[2, 0]+120.*b[2, 0]*b[2, 1]*b[2, 2]-0.8000000000e11*b[2, 0]*b[2, 1]*a[0, 0]+0.4000000000e11*b[2, 0]*b[2, 1]*a[0, 2]+0.4618802154e11*b[2, 0]*b[2, 1]*a[1, 0]-0.2309401078e11*b[2, 0]*b[2, 1]*a[1, 2]-32.*b[2, 0]*b[2, 1]*a[2, 0]+0.2000000000e12*b[2, 0]*b[2, 2]*a[0, 0]-0.1000000000e12*b[2, 0]*b[2, 2]*a[0, 2]-0.1154700538e12*b[2, 0]*b[2, 2]*a[1, 0]+0.5773502696e11*b[2, 0]*b[2, 2]*a[1, 2]+80.*b[2, 0]*b[2, 2]*a[2, 0]+0.2000000000e12*b[2, 1]*b[2, 2]*a[0, 0]-0.1000000000e12*b[2, 1]*b[2, 2]*a[0, 2]-0.1154700538e12*b[2, 1]*b[2, 2]*a[1, 0]+0.5773502696e11*b[2, 1]*b[2, 2]*a[1, 2]+80.*b[2, 1]*b[2, 2]*a[2, 0]-0.2500000000e12*b[2, 2]^2*a[0, 0]+0.1250000000e12*b[2, 2]^2*a[0, 2]+0.1443375673e12*b[2, 2]^2*a[1, 0]-0.7216878370e11*b[2, 2]^2*a[1, 2]-100.*b[2, 2]^2*a[2, 0]+0.5000000000e20*a[1, 1]*b[0, 0]-0.2500000000e20*a[1, 1]*b[0, 2]-0.2886751346e20*a[1, 1]*b[1, 0]+0.1443375675e20*a[1, 1]*b[1, 2]+0.2000000000e11*a[1, 1]*b[2, 0]+0.2000000000e11*a[1, 1]*b[2, 1]-0.5000000000e11*a[1, 1]*b[2, 2]-0.4330127014e30*a[2, 2]*b[0, 0]+0.2165063507e30*a[2, 2]*b[0, 2]+0.2499999997e30*a[2, 2]*b[1, 0]-0.1250000000e30*a[2, 2]*b[1, 2]-0.1732050806e21*a[2, 2]*b[2, 0]+0.5000000000e11*a[2, 2]*b[2, 1]+0.2165063506e21*a[2, 2]*b[2, 2]-0.4330127015e30*a[2, 2]*a[0, 0]+0.2165063508e30*a[2, 2]*a[0, 2]+0.2499999998e30*a[2, 2]*a[1, 0]-0.1250000000e30*a[2, 2]*a[1, 2]-0.1732050806e21*a[2, 2]*a[2, 0]+0.9000000000e31*a[0, 2]*a[0, 0]-0.4500000000e31*a[0, 2]^2-0.4946152423e31*a[0, 2]*a[1, 0]+0.5071152424e31*a[0, 2]*a[1, 2]-0.4330126983e30*a[0, 2]*a[2, 0]-0.5000000000e30*a[1, 0]*a[0, 0]+0.2886751346e30*a[1, 0]^2+0.2711324865e31*a[1, 0]*a[1, 2]-0.5000000002e30*a[1, 0]*a[2, 0]-0.4946152422e31*a[1, 2]*a[0, 0]-0.1427831217e31*a[1, 2]^2+0.2499999982e30*a[1, 2]*a[2, 0]+0.8660254038e30*a[2, 0]*a[0, 0]+0.3464101615e21*a[2, 0]^2-0.4330127019e30*b[0, 0]*b[0, 2]*b[1, 0]+0.2165063512e30*b[0, 0]*b[0, 2]*b[1, 2]+0.3000000000e21*b[0, 0]*b[0, 2]*b[2, 0]-0.6250000000e21*b[0, 0]*b[0, 2]*b[2, 2]+0.2500000000e30*b[0, 0]*b[0, 2]*a[0, 0]-0.1250000000e30*b[0, 0]*b[0, 2]*a[0, 2]-0.1443375673e30*b[0, 0]*b[0, 2]*a[1, 0]+0.7216878370e29*b[0, 0]*b[0, 2]*a[1, 2]+0.1000000000e21*b[0, 0]*b[0, 2]*a[2, 0]+0.2500000004e30*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101615e21*b[0, 0]*b[1, 0]*b[2, 0]-0.7216878365e21*b[0, 0]*b[1, 0]*b[2, 2]+0.2886751346e30*b[0, 0]*b[1, 0]*a[0, 0]-0.1443375673e30*b[0, 0]*b[1, 0]*a[0, 2]-0.1666666667e30*b[0, 0]*b[1, 0]*a[1, 0])/(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0])

 

-0.1000000000e-17*(0.3333333348e27*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 0]+0.1000000000e28*b[0, 0]^2-0.1000000000e28*b[0, 0]*b[0, 2]+0.1154700538e28*b[0, 0]*b[1, 0]-0.5773502720e27*b[0, 0]*b[1, 2]-0.2000000000e19*b[0, 0]*b[2, 0]+0.2000000000e19*b[0, 0]*b[2, 1]+0.2000000000e19*b[0, 0]*b[2, 2]+0.2500000000e27*b[0, 2]^2-0.5773502690e27*b[0, 2]*b[1, 0]+0.2886751360e27*b[0, 2]*b[1, 2]+0.1000000000e19*b[0, 2]*b[2, 0]-0.1000000000e19*b[0, 2]*b[2, 1]-0.1000000000e19*b[0, 2]*b[2, 2]+0.3333333331e27*b[1, 0]^2-0.3333333348e27*b[1, 0]*b[1, 2]-0.1154700538e19*b[1, 0]*b[2, 0]+0.1154700538e19*b[1, 0]*b[2, 1]+0.1154700538e19*b[1, 0]*b[2, 2]+0.8333333414e26*b[1, 2]^2+0.5773502720e18*b[1, 2]*b[2, 0]-0.5773502720e18*b[1, 2]*b[2, 1]-0.5773502720e18*b[1, 2]*b[2, 2]+1000000000.*b[2, 0]^2-2000000000.*b[2, 0]*b[2, 1]-2000000000.*b[2, 0]*b[2, 2]+1000000000.*b[2, 1]^2+2000000000.*b[2, 1]*b[2, 2]+0.3600000000e29*b[0, 0]*a[0, 2]-0.2000000000e28*b[0, 0]*a[1, 0]+0.2178460969e29*b[0, 0]*a[1, 2]-0.3464101615e28*b[0, 0]*a[2, 0]-0.1800000000e29*b[0, 2]*a[0, 2]+0.1000000000e28*b[0, 2]*a[1, 0]-0.1089230484e29*b[0, 2]*a[1, 2]+0.1732050808e28*b[0, 2]*a[2, 0]+0.2078460968e29*b[1, 0]*a[0, 2]-0.1154700538e28*b[1, 0]*a[1, 0]-0.1999999999e28*b[1, 0]*a[2, 0]-0.1039230490e29*b[1, 2]*a[0, 2]+0.5773502720e27*b[1, 2]*a[1, 0]-0.6288675165e28*b[1, 2]*a[1, 2]+0.1000000005e28*b[1, 2]*a[2, 0]-0.3600000000e20*b[2, 0]*a[0, 2]+0.2000000000e19*b[2, 0]*a[1, 0]-0.2178460969e20*b[2, 0]*a[1, 2]+0.3464101615e19*b[2, 0]*a[2, 0]+0.3600000000e20*b[2, 1]*a[0, 2]-0.2000000000e19*b[2, 1]*a[1, 0]+0.2178460969e20*b[2, 1]*a[1, 2]-0.3464101615e19*b[2, 1]*a[2, 0]+0.7200000000e20*b[2, 2]*a[0, 2]-0.4000000000e19*b[2, 2]*a[1, 0]+0.4356921938e20*b[2, 2]*a[1, 2]-0.6928203230e19*b[2, 2]*a[2, 0]+0.1500000000e28*b[0, 0]^2*b[0, 2]-0.1732050807e28*b[0, 0]^2*b[1, 0]+0.8660254080e27*b[0, 0]^2*b[1, 2]+0.3000000000e19*b[0, 0]^2*b[2, 0]-0.2000000000e19*b[0, 0]^2*b[2, 2]-0.1000000000e28*b[0, 0]^2*a[0, 0]+0.5000000000e27*b[0, 0]^2*a[0, 2]-0.5773502690e27*b[0, 0]^2*a[1, 0]+0.2886751360e27*b[0, 0]^2*a[1, 2]+0.1000000000e19*b[0, 0]^2*a[2, 0]-0.7500000000e27*b[0, 0]*b[0, 2]^2-0.9999999993e27*b[0, 0]*b[1, 0]^2-0.2500000024e27*b[0, 0]*b[1, 2]^2-3000000000.*b[0, 0]*b[2, 0]^2-0.3000000000e19*b[0, 0]^2*b[2, 1]-0.4330127018e27*b[0, 2]^2*b[1, 0]+0.2165063520e27*b[0, 2]^2*b[1, 2]+0.7500000000e18*b[0, 2]^2*b[2, 0]-0.5000000000e18*b[0, 2]^2*b[2, 2]-0.2500000000e27*b[0, 2]^2*a[0, 0]+0.1250000000e27*b[0, 2]^2*a[0, 2]-0.1443375672e27*b[0, 2]^2*a[1, 0]+0.7216878400e26*b[0, 2]^2*a[1, 2]+0.2500000000e18*b[0, 2]^2*a[2, 0]+0.4999999997e27*b[0, 2]*b[1, 0]^2+0.1250000012e27*b[0, 2]*b[1, 2]^2+1500000000.*b[0, 2]*b[2, 0]^2-0.7500000000e18*b[0, 2]^2*b[2, 1]+0.2886751358e27*b[1, 0]^2*b[1, 2]+0.9999999993e18*b[1, 0]^2*b[2, 0]-0.6666666662e18*b[1, 0]^2*b[2, 2]-0.3333333331e27*b[1, 0]^2*a[0, 0]+0.1666666666e27*b[1, 0]^2*a[0, 2]-0.1924500895e27*b[1, 0]^2*a[1, 0]+0.9622504527e26*b[1, 0]^2*a[1, 2]+0.3333333331e18*b[1, 0]^2*a[2, 0]-0.1443375687e27*b[1, 0]*b[1, 2]^2-1732050807.*b[1, 0]*b[2, 0]^2-0.9999999993e18*b[1, 0]^2*b[2, 1]+0.2500000024e18*b[1, 2]^2*b[2, 0]-0.1666666683e18*b[1, 2]^2*b[2, 2]-0.8333333414e26*b[1, 2]^2*a[0, 0]+0.4166666707e26*b[1, 2]^2*a[0, 2]-0.4811252289e26*b[1, 2]^2*a[1, 0]+0.2405626157e26*b[1, 2]^2*a[1, 2]+0.8333333414e17*b[1, 2]^2*a[2, 0]+866025408.*b[1, 2]*b[2, 0]^2-0.2500000024e18*b[1, 2]^2*b[2, 1]-2.*b[2, 0]^2*b[2, 2]-1000000000.*b[2, 0]^2*a[0, 0]+500000000.*b[2, 0]^2*a[0, 2]-577350269.*b[2, 0]^2*a[1, 0]+288675136.*b[2, 0]^2*a[1, 2]+b[2, 0]^2*a[2, 0]-3.*b[2, 0]^2*b[2, 1]-3000000000.*b[2, 1]^2*b[0, 0]+1500000000.*b[2, 1]^2*b[0, 2]-1732050807.*b[2, 1]^2*b[1, 0]+866025408.*b[2, 1]^2*b[1, 2]+3.*b[2, 1]^2*b[2, 0]-2.*b[2, 1]^2*b[2, 2]-1000000000.*b[2, 1]^2*a[0, 0]+500000000.*b[2, 1]^2*a[0, 2]-577350269.*b[2, 1]^2*a[1, 0]+288675136.*b[2, 1]^2*a[1, 2]+b[2, 1]^2*a[2, 0]-0.1000000000e28*b[0, 0]^3+0.1250000000e27*b[0, 2]^3-0.1924500895e27*b[1, 0]^3+0.2405626157e26*b[1, 2]^3+b[2, 0]^3+0.1257735026e29*b[1, 0]*a[1, 2]-0.1732050816e19*b[0, 0]*b[1, 2]*b[2, 0]+0.1154700544e19*b[0, 0]*b[1, 2]*b[2, 2]+0.5773502720e27*b[0, 0]*b[1, 2]*a[0, 0]-0.2886751360e27*b[0, 0]*b[1, 2]*a[0, 2]+0.3333333348e27*b[0, 0]*b[1, 2]*a[1, 0]-0.1666666683e27*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 0]+4000000000.*b[0, 0]*b[2, 0]*b[2, 2]+0.2000000000e19*b[0, 0]*b[2, 0]*a[0, 0]-0.1000000000e19*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e19*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502720e18*b[0, 0]*b[2, 0]*a[1, 2]-2000000000.*b[0, 0]*b[2, 0]*a[2, 0]+0.3000000000e19*b[0, 0]*b[2, 1]*b[0, 2]-0.3464101614e19*b[0, 0]*b[2, 1]*b[1, 0]+0.1732050816e19*b[0, 0]*b[2, 1]*b[1, 2]+6000000000.*b[0, 0]*b[2, 1]*b[2, 0]-4000000000.*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e19*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e19*b[0, 0]*b[2, 1]*a[0, 2]-0.1154700538e19*b[0, 0]*b[2, 1]*a[1, 0]+0.5773502720e18*b[0, 0]*b[2, 1]*a[1, 2]+2000000000.*b[0, 0]*b[2, 1]*a[2, 0]-0.5000000023e27*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050807e19*b[0, 2]*b[1, 0]*b[2, 0]+0.1154700538e19*b[0, 2]*b[1, 0]*b[2, 2]+0.5773502690e27*b[0, 2]*b[1, 0]*a[0, 0]-0.2886751345e27*b[0, 2]*b[1, 0]*a[0, 2]+0.3333333331e27*b[0, 2]*b[1, 0]*a[1, 0]-0.1666666674e27*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254080e18*b[0, 2]*b[1, 2]*b[2, 0]-0.5773502720e18*b[0, 2]*b[1, 2]*b[2, 2]-0.2886751360e27*b[0, 2]*b[1, 2]*a[0, 0]+0.1443375680e27*b[0, 2]*b[1, 2]*a[0, 2]-0.1666666674e27*b[0, 2]*b[1, 2]*a[1, 0]+0.8333333414e26*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 0]-2000000000.*b[0, 2]*b[2, 0]*b[2, 2]-0.1000000000e19*b[0, 2]*b[2, 0]*a[0, 0]+0.5000000000e18*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502690e18*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751360e18*b[0, 2]*b[2, 0]*a[1, 2]+1000000000.*b[0, 2]*b[2, 0]*a[2, 0]+0.1732050807e19*b[0, 2]*b[2, 1]*b[1, 0]-0.8660254080e18*b[0, 2]*b[2, 1]*b[1, 2]-3000000000.*b[0, 2]*b[2, 1]*b[2, 0]+2000000000.*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e19*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e18*b[0, 2]*b[2, 1]*a[0, 2]+0.5773502690e18*b[0, 2]*b[2, 1]*a[1, 0]-0.2886751360e18*b[0, 2]*b[2, 1]*a[1, 2]-1000000000.*b[0, 2]*b[2, 1]*a[2, 0]-0.1000000005e19*b[1, 0]*b[1, 2]*b[2, 0]+0.6666666697e18*b[1, 0]*b[1, 2]*b[2, 2]+0.3333333348e27*b[1, 0]*b[1, 2]*a[0, 0]-0.1666666674e27*b[1, 0]*b[1, 2]*a[0, 2]+0.1924500905e27*b[1, 0]*b[1, 2]*a[1, 0]-0.9622504577e26*b[1, 0]*b[1, 2]*a[1, 2]-0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 0]+2309401076.*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e19*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502690e18*b[1, 0]*b[2, 0]*a[0, 2]+0.6666666662e18*b[1, 0]*b[2, 0]*a[1, 0]-0.3333333348e18*b[1, 0]*b[2, 0]*a[1, 2]-1154700538.*b[1, 0]*b[2, 0]*a[2, 0]+0.1000000005e19*b[1, 0]*b[2, 1]*b[1, 2]+3464101614.*b[1, 0]*b[2, 1]*b[2, 0]-2309401076.*b[1, 0]*b[2, 1]*b[2, 2]-0.1154700538e19*b[1, 0]*b[2, 1]*a[0, 0]+0.5773502690e18*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666662e18*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333348e18*b[1, 0]*b[2, 1]*a[1, 2]+1154700538.*b[1, 0]*b[2, 1]*a[2, 0]-1154700544.*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502720e18*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751360e18*b[1, 2]*b[2, 0]*a[0, 2]-0.3333333348e18*b[1, 2]*b[2, 0]*a[1, 0]+0.1666666683e18*b[1, 2]*b[2, 0]*a[1, 2]+577350272.*b[1, 2]*b[2, 0]*a[2, 0]-1732050816.*b[1, 2]*b[2, 1]*b[2, 0]+1154700544.*b[1, 2]*b[2, 1]*b[2, 2]+0.5773502720e18*b[1, 2]*b[2, 1]*a[0, 0]-0.2886751360e18*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333348e18*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666683e18*b[1, 2]*b[2, 1]*a[1, 2]-577350272.*b[1, 2]*b[2, 1]*a[2, 0]+4.*b[2, 0]*b[2, 1]*b[2, 2]+2000000000.*b[2, 0]*b[2, 1]*a[0, 0]-1000000000.*b[2, 0]*b[2, 1]*a[0, 2]+1154700538.*b[2, 0]*b[2, 1]*a[1, 0]-577350272.*b[2, 0]*b[2, 1]*a[1, 2]-2.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050853e28*a[2, 2]*b[0, 0]-0.8660254265e27*a[2, 2]*b[0, 2]+0.1000000026e28*a[2, 2]*b[1, 0]-0.5000000155e27*a[2, 2]*b[1, 2]-0.1732050853e19*a[2, 2]*b[2, 0]+0.1732050853e19*a[2, 2]*b[2, 1]+0.3464101700e19*a[2, 2]*b[2, 2]+0.1732050850e28*a[2, 2]*a[0, 0]-0.8660252810e27*a[2, 2]*a[0, 2]+0.1000000016e28*a[2, 2]*a[1, 0]-0.4999999275e27*a[2, 2]*a[1, 2]-0.1558845731e20*a[2, 2]*a[2, 0]+0.3600000000e29*a[0, 2]*a[0, 0]-0.1800000000e29*a[0, 2]^2+0.2178460968e29*a[0, 2]*a[1, 0]-0.2128460974e29*a[0, 2]*a[1, 2]+0.1732050772e28*a[0, 2]*a[2, 0]-0.2000000000e28*a[1, 0]*a[0, 0]-0.1154700538e28*a[1, 0]^2+0.1315470054e29*a[1, 0]*a[1, 2]-0.1999999997e28*a[1, 0]*a[2, 0]+0.2178460969e29*a[1, 2]*a[0, 0]-0.6288675165e28*a[1, 2]^2+0.9999999830e27*a[1, 2]*a[2, 0]-0.3464101615e28*a[2, 0]*a[0, 0]+0.3464101615e19*a[2, 0]^2-0.1000000000e19*b[0, 0]^2*a[2, 1]-0.4000000000e19*b[0, 0]^2*a[2, 2]+0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 1]+0.4000000000e19*b[0, 0]*b[0, 2]*a[2, 2]-0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 1]-0.4618802152e19*b[0, 0]*b[1, 0]*a[2, 2]+0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 1]+0.2309401088e19*b[0, 0]*b[1, 2]*a[2, 2]+2000000000.*b[0, 0]*b[2, 0]*a[2, 1]+8000000000.*b[0, 0]*b[2, 0]*a[2, 2]-2000000000.*b[0, 0]*b[2, 1]*a[2, 1]-8000000000.*b[0, 0]*b[2, 1]*a[2, 2]+0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 1]+0.2309401076e19*b[0, 2]*b[1, 0]*a[2, 2]-0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 1]-0.1154700544e19*b[0, 2]*b[1, 2]*a[2, 2]-1000000000.*b[0, 2]*b[2, 0]*a[2, 1]-4000000000.*b[0, 2]*b[2, 0]*a[2, 2]+1000000000.*b[0, 2]*b[2, 1]*a[2, 1]+4000000000.*b[0, 2]*b[2, 1]*a[2, 2]+0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 1]+0.1333333339e19*b[1, 0]*b[1, 2]*a[2, 2]+1154700538.*b[1, 0]*b[2, 0]*a[2, 1]+4618802152.*b[1, 0]*b[2, 0]*a[2, 2]-1154700538.*b[1, 0]*b[2, 1]*a[2, 1]-4618802152.*b[1, 0]*b[2, 1]*a[2, 2]-577350272.*b[1, 2]*b[2, 0]*a[2, 1]-2309401088.*b[1, 2]*b[2, 0]*a[2, 2]+577350272.*b[1, 2]*b[2, 1]*a[2, 1]+2309401088.*b[1, 2]*b[2, 1]*a[2, 2]+2.*b[2, 0]*b[2, 1]*a[2, 1]+8.*b[2, 0]*b[2, 1]*a[2, 2]-1.*b[2, 1]^3-0.2500000000e18*b[0, 2]^2*a[2, 1]-0.1000000000e19*b[0, 2]^2*a[2, 2]-0.3333333331e18*b[1, 0]^2*a[2, 1]-0.1333333332e19*b[1, 0]^2*a[2, 2]-0.8333333414e17*b[1, 2]^2*a[2, 1]-0.3333333366e18*b[1, 2]^2*a[2, 2]-1.*b[2, 0]^2*a[2, 1]-4.*b[2, 0]^2*a[2, 2]-1.*b[2, 1]^2*a[2, 1]-4.*b[2, 1]^2*a[2, 2]+0.1732050850e19*a[2, 2]*a[2, 1]+0.6928203400e19*a[2, 2]^2+0.3600000000e20*a[0, 2]*a[2, 1]-0.2000000000e19*a[1, 0]*a[2, 1]+0.2178460969e20*a[1, 2]*a[2, 1]-0.3464101615e19*a[2, 0]*a[2, 1]+0.1732050807e28*b[0, 0]*b[0, 2]*b[1, 0]-0.8660254080e27*b[0, 0]*b[0, 2]*b[1, 2]-0.3000000000e19*b[0, 0]*b[0, 2]*b[2, 0]+0.2000000000e19*b[0, 0]*b[0, 2]*b[2, 2]+0.1000000000e28*b[0, 0]*b[0, 2]*a[0, 0]-0.5000000000e27*b[0, 0]*b[0, 2]*a[0, 2]+0.5773502690e27*b[0, 0]*b[0, 2]*a[1, 0]-0.2886751360e27*b[0, 0]*b[0, 2]*a[1, 2]-0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 0]+0.1000000005e28*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101614e19*b[0, 0]*b[1, 0]*b[2, 0]-0.2309401076e19*b[0, 0]*b[1, 0]*b[2, 2]-0.1154700538e28*b[0, 0]*b[1, 0]*a[0, 0]+0.5773502690e27*b[0, 0]*b[1, 0]*a[0, 2]-0.6666666662e27*b[0, 0]*b[1, 0]*a[1, 0])/(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2])

(25)

s[2, 2]

(26)

for i to M-1 do for j from 0 to N-1 do w[i, j] := simplify(evalf(eq22)) end do end do;

0.2000000000e-9*(-0.1889957658e30*b[0, 0]*b[1, 0]*a[1, 2]-0.7237604306e21*b[0, 0]*b[1, 0]*a[2, 0]+0.5000000000e31*b[0, 0]^2-0.8000000000e31*b[0, 0]*b[0, 2]-0.5273502692e31*b[0, 0]*b[1, 0]+0.4368802158e31*b[0, 0]*b[1, 2]-0.8660253998e30*b[0, 0]*b[2, 0]+0.2000000000e22*b[0, 0]*b[2, 1]+0.4330126925e30*b[0, 0]*b[2, 2]+0.2750000000e31*b[0, 2]^2+0.4368802154e31*b[0, 2]*b[1, 0]-0.3050426484e31*b[0, 2]*b[1, 2]+0.4330126987e30*b[0, 2]*b[2, 0]-0.1000000000e22*b[0, 2]*b[2, 1]-0.2165063448e30*b[0, 2]*b[2, 2]+0.1377991532e31*b[1, 0]^2-0.2377991534e31*b[1, 0]*b[1, 2]+0.4999999979e30*b[1, 0]*b[2, 0]-0.1154700538e22*b[1, 0]*b[2, 1]-0.2499999948e30*b[1, 0]*b[2, 2]+0.8444978848e30*b[1, 2]^2-0.2499999986e30*b[1, 2]*b[2, 0]+0.5773502700e21*b[1, 2]*b[2, 1]+0.1249999967e30*b[1, 2]*b[2, 2]-0.3464101607e21*b[2, 0]^2+0.8000000000e12*b[2, 0]*b[2, 1]+0.6062177789e21*b[2, 0]*b[2, 2]-0.1000000000e13*b[2, 1]*b[2, 2]-0.2165063475e21*b[2, 2]^2+0.4000000000e31*b[0, 0]*a[0, 0]-0.2000000000e31*b[0, 0]*a[0, 2]-0.2309401077e31*b[0, 0]*a[1, 0]+0.1154700539e31*b[0, 0]*a[1, 2]+0.2000000000e22*b[0, 0]*a[2, 0]-0.5000000000e31*b[0, 2]*a[0, 0]+0.2500000000e31*b[0, 2]*a[0, 2]+0.2886751346e31*b[0, 2]*a[1, 0]-0.1443375674e31*b[0, 2]*a[1, 2]-0.2200000000e22*b[0, 2]*a[2, 0]-0.1809401077e31*b[1, 0]*a[0, 0]+0.9047005384e30*b[1, 0]*a[0, 2]+0.1044658199e31*b[1, 0]*a[1, 0]-0.9547005384e21*b[1, 0]*a[2, 0]+0.2636751348e31*b[1, 2]*a[0, 0]-0.1318375674e31*b[1, 2]*a[0, 2]-0.1522329100e31*b[1, 2]*a[1, 0]+0.7611645506e30*b[1, 2]*a[1, 2]+0.1170170593e22*b[1, 2]*a[2, 0]-0.8660254022e30*b[2, 0]*a[0, 0]+0.4330127011e30*b[2, 0]*a[0, 2]+0.4999999991e30*b[2, 0]*a[1, 0]-0.2499999997e30*b[2, 0]*a[1, 2]-0.3464101607e21*b[2, 0]*a[2, 0]+0.1600000000e22*b[2, 1]*a[0, 0]-0.8000000000e21*b[2, 1]*a[0, 2]-0.9237604307e21*b[2, 1]*a[1, 0]+0.4618802156e21*b[2, 1]*a[1, 2]+0.8000000000e12*b[2, 1]*a[2, 0]+0.4330126960e30*b[2, 2]*a[0, 0]-0.2165063480e30*b[2, 2]*a[0, 2]-0.2499999966e30*b[2, 2]*a[1, 0]+0.1249999984e30*b[2, 2]*a[1, 2]+0.1732050780e21*b[2, 2]*a[2, 0]-0.6000000000e31*b[0, 0]^2*b[0, 2]-0.2964101615e31*b[0, 0]^2*b[1, 0]+0.3214101616e31*b[0, 0]^2*b[1, 2]-0.8660254022e30*b[0, 0]^2*b[2, 0]+0.4330126960e30*b[0, 0]^2*b[2, 2]+0.1000000000e31*b[0, 0]^2*a[0, 0]-0.5000000000e30*b[0, 0]^2*a[0, 2]-0.5773502692e30*b[0, 0]^2*a[1, 0]+0.2886751346e30*b[0, 0]^2*a[1, 2]+0.8000000000e21*b[0, 0]^2*a[2, 0]+0.4500000000e31*b[0, 0]*b[0, 2]^2+0.1422649730e31*b[0, 0]*b[1, 0]^2+0.1355662435e31*b[0, 0]*b[1, 2]^2-0.6928203228e21*b[0, 0]*b[2, 0]^2+0.7000000000e21*b[0, 0]^2*b[2, 1]-0.6495190475e21*b[0, 0]*b[2, 2]^2-0.2473076211e31*b[0, 2]^2*b[1, 0]+0.1669550809e31*b[0, 2]^2*b[1, 2]-0.2165063494e30*b[0, 2]^2*b[2, 0]+0.1082531718e30*b[0, 2]^2*b[2, 2]+0.1750000000e31*b[0, 2]^2*a[0, 0]-0.8750000000e30*b[0, 2]^2*a[0, 2]-0.1010362971e31*b[0, 2]^2*a[1, 0]+0.5051814858e30*b[0, 2]^2*a[1, 2]+0.8000000000e21*b[0, 2]^2*a[2, 0]-0.1711324865e31*b[0, 2]*b[1, 0]^2-0.9278312180e30*b[0, 2]*b[1, 2]^2+0.3464101609e21*b[0, 2]*b[2, 0]^2+0.7750000000e21*b[0, 2]^2*b[2, 1]+0.3247595222e21*b[0, 2]*b[2, 2]^2+0.9047005385e30*b[1, 0]^2*b[1, 2]-0.2886751343e30*b[1, 0]^2*b[2, 0]+0.1443375658e30*b[1, 0]^2*b[2, 2]+0.4465819851e29*b[1, 0]^2*a[0, 0]-0.2232909926e29*b[1, 0]^2*a[0, 2]-0.2578342293e29*b[1, 0]^2*a[1, 0]+0.1289171141e29*b[1, 0]^2*a[1, 2]+0.1511966127e21*b[1, 0]^2*a[2, 0]-0.7410254048e30*b[1, 0]*b[1, 2]^2+0.3999999999e21*b[1, 0]*b[2, 0]^2+0.1178632794e21*b[1, 0]^2*b[2, 1]+0.3749999972e21*b[1, 0]*b[2, 2]^2-0.7216878338e29*b[1, 2]^2*b[2, 0]+0.3608439079e29*b[1, 2]^2*b[2, 2]+0.5111645502e30*b[1, 2]^2*a[0, 0]-0.2555822751e30*b[1, 2]^2*a[0, 2]-0.2951209907e30*b[1, 2]^2*a[1, 0]+0.1475604954e30*b[1, 2]^2*a[1, 2]+0.2377991535e21*b[1, 2]^2*a[2, 0]-0.2000000000e21*b[1, 2]*b[2, 0]^2+0.2294658202e21*b[1, 2]^2*b[2, 1]-0.1874999980e21*b[1, 2]*b[2, 2]^2+0.5888972742e12*b[2, 0]^2*b[2, 2]-0.3464101617e21*b[2, 0]^2*a[0, 0]+0.1732050808e21*b[2, 0]^2*a[0, 2]+0.2000000001e21*b[2, 0]^2*a[1, 0]-0.1000000001e21*b[2, 0]^2*a[1, 2]-0.1385640646e12*b[2, 0]^2*a[2, 0]-0.1385640646e12*b[2, 0]^2*b[2, 1]-0.6928203213e12*b[2, 0]*b[2, 2]^2-0.4000000000e11*b[2, 1]^2*b[0, 0]+0.2000000000e11*b[2, 1]^2*b[0, 2]+0.2309401077e11*b[2, 1]^2*b[1, 0]-0.1154700540e11*b[2, 1]^2*b[1, 2]-16.*b[2, 1]^2*b[2, 0]+20.*b[2, 1]^2*b[2, 2]-0.2000000000e12*b[2, 1]^2*a[0, 0]+0.1000000000e12*b[2, 1]^2*a[0, 2]+0.1154700538e12*b[2, 1]^2*a[1, 0]-0.5773502699e11*b[2, 1]^2*a[1, 2]-16.*b[2, 1]^2*a[2, 0]-0.8660253985e11*b[2, 1]*b[2, 2]^2+0.2000000000e31*b[0, 0]^3-0.1000000000e31*b[0, 2]^3-0.2182335127e30*b[1, 0]^3+0.1716167569e30*b[1, 2]^3-0.1385640646e12*b[2, 0]^3+0.2165063495e12*b[2, 2]^3-0.5223290996e30*b[1, 0]*a[1, 2]-0.4999999986e30*b[0, 0]*b[1, 2]*b[2, 0]+0.2499999947e30*b[0, 0]*b[1, 2]*b[2, 2]+0.2059401076e31*b[0, 0]*b[1, 2]*a[0, 0]-0.1029700538e31*b[0, 0]*b[1, 2]*a[0, 2]-0.1188995766e31*b[0, 0]*b[1, 2]*a[1, 0]+0.5944978833e30*b[0, 0]*b[1, 2]*a[1, 2]+0.1054700539e22*b[0, 0]*b[1, 2]*a[2, 0]+0.1645448264e22*b[0, 0]*b[2, 0]*b[2, 2]-0.8660254038e30*b[0, 0]*b[2, 0]*a[0, 0]+0.4330127019e30*b[0, 0]*b[2, 0]*a[0, 2]+0.5000000000e30*b[0, 0]*b[2, 0]*a[1, 0]-0.2500000002e30*b[0, 0]*b[2, 0]*a[1, 2]-0.3464101612e21*b[0, 0]*b[2, 0]*a[2, 0]-0.1900000000e22*b[0, 0]*b[2, 1]*b[0, 2]-0.6082903767e21*b[0, 0]*b[2, 1]*b[1, 0]+0.9969655116e21*b[0, 0]*b[2, 1]*b[1, 2]-0.3464101613e21*b[0, 0]*b[2, 1]*b[2, 0]+0.1732050794e21*b[0, 0]*b[2, 1]*b[2, 2]-0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.5000000000e20*b[0, 0]*b[2, 1]*a[0, 2]+0.5773502692e20*b[0, 0]*b[2, 1]*a[1, 0]-0.2886751364e20*b[0, 0]*b[2, 1]*a[1, 2]+0.2800000000e12*b[0, 0]*b[2, 1]*a[2, 0]+0.4330126990e30*b[0, 0]*b[2, 2]*a[0, 0]-0.2165063495e30*b[0, 0]*b[2, 2]*a[0, 2]-0.2499999983e30*b[0, 0]*b[2, 2]*a[1, 0]+0.1249999993e30*b[0, 0]*b[2, 2]*a[1, 2]+0.1732050788e21*b[0, 0]*b[2, 2]*a[2, 0]+0.2711324867e31*b[0, 2]*b[1, 0]*b[1, 2]-0.4999999979e30*b[0, 2]*b[1, 0]*b[2, 0]+0.2499999944e30*b[0, 2]*b[1, 0]*b[2, 2]+0.2059401077e31*b[0, 2]*b[1, 0]*a[0, 0]-0.1029700538e31*b[0, 2]*b[1, 0]*a[0, 2]-0.1188995766e31*b[0, 2]*b[1, 0]*a[1, 0]+0.5944978833e30*b[0, 2]*b[1, 0]*a[1, 2]+0.1054700538e22*b[0, 2]*b[1, 0]*a[2, 0]+0.2499999986e30*b[0, 2]*b[1, 2]*b[2, 0]-0.1249999961e30*b[0, 2]*b[1, 2]*b[2, 2]-0.1895725943e31*b[0, 2]*b[1, 2]*a[0, 0]+0.9478629716e30*b[0, 2]*b[1, 2]*a[0, 2]+0.1094497884e31*b[0, 2]*b[1, 2]*a[1, 0]-0.5472489422e30*b[0, 2]*b[1, 2]*a[1, 2]-0.8737604313e21*b[0, 2]*b[1, 2]*a[2, 0]-0.8227241301e21*b[0, 2]*b[2, 0]*b[2, 2]+0.4330127007e30*b[0, 2]*b[2, 0]*a[0, 0]-0.2165063504e30*b[0, 2]*b[2, 0]*a[0, 2]-0.2499999993e30*b[0, 2]*b[2, 0]*a[1, 0]+0.1249999998e30*b[0, 2]*b[2, 0]*a[1, 2]+0.1732050801e21*b[0, 2]*b[2, 0]*a[2, 0]+0.9969655114e21*b[0, 2]*b[2, 1]*b[1, 0]-0.8448929178e21*b[0, 2]*b[2, 1]*b[1, 2]+0.1732050802e21*b[0, 2]*b[2, 1]*b[2, 0]-0.8660253908e20*b[0, 2]*b[2, 1]*b[2, 2]-0.1150000000e22*b[0, 2]*b[2, 1]*a[0, 0]+0.5750000000e21*b[0, 2]*b[2, 1]*a[0, 2]+0.6639528096e21*b[0, 2]*b[2, 1]*a[1, 0]-0.3319764049e21*b[0, 2]*b[2, 1]*a[1, 2]-0.6200000000e12*b[0, 2]*b[2, 1]*a[2, 0]-0.2165063465e30*b[0, 2]*b[2, 2]*a[0, 0]+0.1082531732e30*b[0, 2]*b[2, 2]*a[0, 2]+0.1249999974e30*b[0, 2]*b[2, 2]*a[1, 0]-0.6249999876e29*b[0, 2]*b[2, 2]*a[1, 2]-0.8660253820e20*b[0, 2]*b[2, 2]*a[2, 0]+0.2886751339e30*b[1, 0]*b[1, 2]*b[2, 0]-0.1443375645e30*b[1, 0]*b[1, 2]*b[2, 2]-0.1044658198e31*b[1, 0]*b[1, 2]*a[0, 0]+0.5223290991e30*b[1, 0]*b[1, 2]*a[0, 2]+0.6031336920e30*b[1, 0]*b[1, 2]*a[1, 0]-0.3015668461e30*b[1, 0]*b[1, 2]*a[1, 2]-0.5511966128e21*b[1, 0]*b[1, 2]*a[2, 0]-0.9499999983e21*b[1, 0]*b[2, 0]*b[2, 2]+0.5000000002e30*b[1, 0]*b[2, 0]*a[0, 0]-0.2500000001e30*b[1, 0]*b[2, 0]*a[0, 2]-0.2886751347e30*b[1, 0]*b[2, 0]*a[1, 0]+0.1443375675e30*b[1, 0]*b[2, 0]*a[1, 2]+0.1999999999e21*b[1, 0]*b[2, 0]*a[2, 0]-0.5178632795e21*b[1, 0]*b[2, 1]*b[1, 2]+0.2000000000e21*b[1, 0]*b[2, 1]*b[2, 0]-0.9999999929e20*b[1, 0]*b[2, 1]*b[2, 2]+0.2577350271e21*b[1, 0]*b[2, 1]*a[0, 0]-0.1288675135e21*b[1, 0]*b[2, 1]*a[0, 2]-0.1488033873e21*b[1, 0]*b[2, 1]*a[1, 0]+0.7440169378e20*b[1, 0]*b[2, 1]*a[1, 2]-0.8165807531e11*b[1, 0]*b[2, 1]*a[2, 0]-0.2499999988e30*b[1, 0]*b[2, 2]*a[0, 0]+0.1249999994e30*b[1, 0]*b[2, 2]*a[0, 2]+0.1443375666e30*b[1, 0]*b[2, 2]*a[1, 0]-0.7216878336e29*b[1, 0]*b[2, 2]*a[1, 2]-0.9999999907e20*b[1, 0]*b[2, 2]*a[2, 0]+0.4749999988e21*b[1, 2]*b[2, 0]*b[2, 2]-0.2499999998e30*b[1, 2]*b[2, 0]*a[0, 0]+0.1249999999e30*b[1, 2]*b[2, 0]*a[0, 2]+0.1443375672e30*b[1, 2]*b[2, 0]*a[1, 0]-0.7216878364e29*b[1, 2]*b[2, 0]*a[1, 2]-0.9999999982e20*b[1, 2]*b[2, 0]*a[2, 0]-0.9999999984e20*b[1, 2]*b[2, 1]*b[2, 0]+0.4999999937e20*b[1, 2]*b[2, 1]*b[2, 2]+0.5639528091e21*b[1, 2]*b[2, 1]*a[0, 0]-0.2819764046e21*b[1, 2]*b[2, 1]*a[0, 2]-0.3255983061e21*b[1, 2]*b[2, 1]*a[1, 0]+0.1627991531e21*b[1, 2]*b[2, 1]*a[1, 2]+0.3179571668e12*b[1, 2]*b[2, 1]*a[2, 0]+0.1249999979e30*b[1, 2]*b[2, 2]*a[0, 0]-0.6249999893e29*b[1, 2]*b[2, 2]*a[0, 2]-0.7216878241e29*b[1, 2]*b[2, 2]*a[1, 0]+0.3608439123e29*b[1, 2]*b[2, 2]*a[1, 2]+0.4999999891e20*b[1, 2]*b[2, 2]*a[2, 0]+0.2424871127e12*b[2, 0]*b[2, 1]*b[2, 2]-0.3464101619e21*b[2, 0]*b[2, 1]*a[0, 0]+0.1732050810e21*b[2, 0]*b[2, 1]*a[0, 2]+0.2000000002e21*b[2, 0]*b[2, 1]*a[1, 0]-0.1000000002e21*b[2, 0]*b[2, 1]*a[1, 2]-0.1385640646e12*b[2, 0]*b[2, 1]*a[2, 0]+0.1039230484e22*b[2, 0]*b[2, 2]*a[0, 0]-0.5196152421e21*b[2, 0]*b[2, 2]*a[0, 2]-0.5999999998e21*b[2, 0]*b[2, 2]*a[1, 0]+0.3000000001e21*b[2, 0]*b[2, 2]*a[1, 2]+0.4156921934e12*b[2, 0]*b[2, 2]*a[2, 0]+0.1732050805e21*b[2, 1]*b[2, 2]*a[0, 0]-0.8660254025e20*b[2, 1]*b[2, 2]*a[0, 2]-0.9999999985e20*b[2, 1]*b[2, 2]*a[1, 0]+0.4999999996e20*b[2, 1]*b[2, 2]*a[1, 2]+0.6928203188e11*b[2, 1]*b[2, 2]*a[2, 0]-0.4330127000e21*b[2, 2]^2*a[0, 0]+0.2165063500e21*b[2, 2]^2*a[0, 2]+0.2499999989e21*b[2, 2]^2*a[1, 0]-0.1249999995e21*b[2, 2]^2*a[1, 2]-0.1732050796e12*b[2, 2]^2*a[2, 0]+0.2000000000e21*a[1, 1]*b[0, 0]-0.1000000000e21*a[1, 1]*b[0, 2]-0.1154700538e21*a[1, 1]*b[1, 0]+0.5773502700e20*a[1, 1]*b[1, 2]+0.8000000000e11*a[1, 1]*b[2, 0]+0.8000000000e11*a[1, 1]*b[2, 1]-0.2000000000e12*a[1, 1]*b[2, 2]+0.5000000000e21*a[2, 2]*b[0, 0]-0.2500000000e21*a[2, 2]*b[0, 2]-0.2886751346e21*a[2, 2]*b[1, 0]+0.1443375675e21*a[2, 2]*b[1, 2]+0.2000000000e12*a[2, 2]*b[2, 0]+0.2000000000e12*a[2, 2]*b[2, 1]-0.5000000000e12*a[2, 2]*b[2, 2]+0.5000000000e21*b[0, 0]^2*a[2, 2]-0.5000000000e21*b[0, 0]*b[0, 2]*a[2, 2]-0.5773502692e21*b[0, 0]*b[1, 0]*a[2, 2]+0.2886751350e21*b[0, 0]*b[1, 2]*a[2, 2]+0.4000000000e12*b[0, 0]*b[2, 0]*a[2, 2]+0.4000000000e12*b[0, 0]*b[2, 1]*a[2, 2]+0.2886751346e21*b[0, 2]*b[1, 0]*a[2, 2]-0.1443375675e21*b[0, 2]*b[1, 2]*a[2, 2]-0.2000000000e12*b[0, 2]*b[2, 0]*a[2, 2]-0.2000000000e12*b[0, 2]*b[2, 1]*a[2, 2]-0.1666666669e21*b[1, 0]*b[1, 2]*a[2, 2]-0.2309401077e12*b[1, 0]*b[2, 0]*a[2, 2]-0.2309401077e12*b[1, 0]*b[2, 1]*a[2, 2]+0.1154700540e12*b[1, 2]*b[2, 0]*a[2, 2]+0.1154700540e12*b[1, 2]*b[2, 1]*a[2, 2]+160.*b[2, 0]*b[2, 1]*a[2, 2]+0.1250000000e21*b[0, 2]^2*a[2, 2]+0.1666666667e21*b[1, 0]^2*a[2, 2]+0.4166666678e20*b[1, 2]^2*a[2, 2]+80.*b[2, 0]^2*a[2, 2]+80.*b[2, 1]^2*a[2, 2]+0.6666666667e20*a[1, 1]*b[1, 0]^2-0.1333333333e21*b[1, 1]*b[1, 0]^2+0.2000000000e21*a[1, 1]*b[0, 0]^2-0.4000000000e21*b[1, 1]*b[0, 0]^2+0.5000000000e20*a[1, 1]*b[0, 2]^2-0.1000000000e21*b[1, 1]*b[0, 2]^2-0.2000000000e21*b[0, 0]*a[1, 1]*b[0, 2]-0.2309401077e21*b[0, 0]*a[1, 1]*b[1, 0]+0.1154700540e21*b[0, 0]*a[1, 1]*b[1, 2]+0.1600000000e12*b[0, 0]*a[1, 1]*b[2, 0]+0.1600000000e12*b[0, 0]*a[1, 1]*b[2, 1]-0.4000000000e12*b[0, 0]*a[1, 1]*b[2, 2]-0.1000000000e13*b[0, 0]*a[2, 2]*b[2, 2]+0.4000000000e21*b[0, 0]*b[1, 1]*b[0, 2]+0.4618802154e21*b[0, 0]*b[1, 1]*b[1, 0]-0.2309401080e21*b[0, 0]*b[1, 1]*b[1, 2]-0.3200000000e12*b[0, 0]*b[1, 1]*b[2, 0]+0.6000000000e12*b[0, 0]*b[1, 1]*b[2, 2]-0.4000000000e21*b[0, 0]*b[1, 1]*a[0, 0]+0.2000000000e21*b[0, 0]*b[1, 1]*a[0, 2]+0.2309401077e21*b[0, 0]*b[1, 1]*a[1, 0]-0.1154700539e21*b[0, 0]*b[1, 1]*a[1, 2]-0.1600000000e12*b[0, 0]*b[1, 1]*a[2, 0]+0.1154700538e21*b[0, 2]*a[1, 1]*b[1, 0]-0.5773502700e20*b[0, 2]*a[1, 1]*b[1, 2]-0.8000000000e11*b[0, 2]*a[1, 1]*b[2, 0]-0.8000000000e11*b[0, 2]*a[1, 1]*b[2, 1]+0.2000000000e12*b[0, 2]*a[1, 1]*b[2, 2]+0.5000000000e12*b[0, 2]*a[2, 2]*b[2, 2]-0.2309401077e21*b[0, 2]*b[1, 1]*b[1, 0]+0.1154700540e21*b[0, 2]*b[1, 1]*b[1, 2]+0.1600000000e12*b[0, 2]*b[1, 1]*b[2, 0]-0.3000000000e12*b[0, 2]*b[1, 1]*b[2, 2]+0.2000000000e21*b[0, 2]*b[1, 1]*a[0, 0]-0.1000000000e21*b[0, 2]*b[1, 1]*a[0, 2]-0.1154700538e21*b[0, 2]*b[1, 1]*a[1, 0]+0.5773502696e20*b[0, 2]*b[1, 1]*a[1, 2]+0.8000000000e11*b[0, 2]*b[1, 1]*a[2, 0]-0.6666666676e20*b[1, 0]*a[1, 1]*b[1, 2]-0.9237604307e11*b[1, 0]*a[1, 1]*b[2, 0]-0.9237604307e11*b[1, 0]*a[1, 1]*b[2, 1]+0.2309401077e12*b[1, 0]*a[1, 1]*b[2, 2]+0.5773502692e12*b[1, 0]*a[2, 2]*b[2, 2]+0.1333333335e21*b[1, 0]*b[1, 1]*b[1, 2]+0.1847520861e12*b[1, 0]*b[1, 1]*b[2, 0]-0.3464101615e12*b[1, 0]*b[1, 1]*b[2, 2]+0.2309401077e21*b[1, 0]*b[1, 1]*a[0, 0]-0.1154700538e21*b[1, 0]*b[1, 1]*a[0, 2]-0.1333333333e21*b[1, 0]*b[1, 1]*a[1, 0]+0.6666666672e20*b[1, 0]*b[1, 1]*a[1, 2]+0.9237604307e11*b[1, 0]*b[1, 1]*a[2, 0]+0.4618802160e11*b[1, 2]*a[1, 1]*b[2, 0]+0.4618802160e11*b[1, 2]*a[1, 1]*b[2, 1]-0.1154700540e12*b[1, 2]*a[1, 1]*b[2, 2]-0.2886751350e12*b[1, 2]*a[2, 2]*b[2, 2]-0.9237604320e11*b[1, 2]*b[1, 1]*b[2, 0]+0.1732050810e12*b[1, 2]*b[1, 1]*b[2, 2]-0.1154700540e21*b[1, 2]*b[1, 1]*a[0, 0]+0.5773502700e20*b[1, 2]*b[1, 1]*a[0, 2]+0.6666666676e20*b[1, 2]*b[1, 1]*a[1, 0]-0.3333333340e20*b[1, 2]*b[1, 1]*a[1, 2]-0.4618802160e11*b[1, 2]*b[1, 1]*a[2, 0]+64.*b[2, 0]*a[1, 1]*b[2, 1]-160.*b[2, 0]*a[1, 1]*b[2, 2]-400.*b[2, 0]*a[2, 2]*b[2, 2]+240.*b[2, 0]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 0]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 0]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 0]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 0]*b[1, 1]*a[1, 2]-64.*b[2, 0]*b[1, 1]*a[2, 0]-160.*b[2, 1]*a[1, 1]*b[2, 2]-400.*b[2, 1]*a[2, 2]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*b[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*b[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*b[1, 0]-0.4618802160e11*b[2, 1]*b[1, 1]*b[1, 2]-64.*b[2, 1]*b[1, 1]*b[2, 0]+80.*b[2, 1]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 1]*b[1, 1]*a[1, 2]-64.*b[2, 1]*b[1, 1]*a[2, 0]+0.4000000000e12*b[2, 2]*b[1, 1]*a[0, 0]-0.2000000000e12*b[2, 2]*b[1, 1]*a[0, 2]-0.2309401077e12*b[2, 2]*b[1, 1]*a[1, 0]+0.1154700539e12*b[2, 2]*b[1, 1]*a[1, 2]+160.*b[2, 2]*b[1, 1]*a[2, 0]+0.1666666671e20*a[1, 1]*b[1, 2]^2-0.3333333343e20*b[1, 1]*b[1, 2]^2+32.*a[1, 1]*b[2, 0]^2-64.*b[1, 1]*b[2, 0]^2+32.*a[1, 1]*b[2, 1]^2+200.*a[1, 1]*b[2, 2]^2+500.*a[2, 2]*b[2, 2]^2-200.*b[1, 1]*b[2, 2]^2+0.6428203230e31*b[0, 0]*b[0, 2]*b[1, 0]-0.4946152426e31*b[0, 0]*b[0, 2]*b[1, 2]+0.8660253998e30*b[0, 0]*b[0, 2]*b[2, 0]-0.4330126915e30*b[0, 0]*b[0, 2]*b[2, 2]-0.4000000000e31*b[0, 0]*b[0, 2]*a[0, 0]+0.2000000000e31*b[0, 0]*b[0, 2]*a[0, 2]+0.2309401077e31*b[0, 0]*b[0, 2]*a[1, 0]-0.1154700539e31*b[0, 0]*b[0, 2]*a[1, 2]-0.2000000000e22*b[0, 0]*b[0, 2]*a[2, 0]-0.3422649732e31*b[0, 0]*b[1, 0]*b[1, 2]+0.9999999986e30*b[0, 0]*b[1, 0]*b[2, 0]-0.4999999940e30*b[0, 0]*b[1, 0]*b[2, 2]-0.6547005380e30*b[0, 0]*b[1, 0]*a[0, 0]+0.3273502690e30*b[0, 0]*b[1, 0]*a[0, 2]+0.3779915319e30*b[0, 0]*b[1, 0]*a[1, 0])/((5000000000.+5000000000.*b[0, 0]-2500000000.*b[0, 2]-2886751346.*b[1, 0]+1443375675.*b[1, 2]+2.*b[2, 0]+2.*b[2, 1]-5.*b[2, 2])*(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0]))

 

0.1000000000e-8*(-0.1910683611e28*b[0, 0]*b[1, 0]*a[1, 2]-0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 0]+0.2000000000e29*b[0, 0]^2-0.3200000000e29*b[0, 0]*b[0, 2]+0.2509401076e29*b[0, 0]*b[1, 0]-0.1947520867e29*b[0, 0]*b[1, 2]+0.3464101575e28*b[0, 0]*b[2, 0]+0.4000000000e20*b[0, 0]*b[2, 1]-0.1732050770e28*b[0, 0]*b[2, 2]+0.1100000000e29*b[0, 2]^2-0.1947520861e29*b[0, 2]*b[1, 0]+0.1320170597e29*b[0, 2]*b[1, 2]-0.1732050776e28*b[0, 2]*b[2, 0]-0.3200000000e20*b[0, 2]*b[2, 1]+0.8660253610e27*b[0, 2]*b[2, 2]+0.7821367200e28*b[1, 0]^2-0.1182136724e29*b[1, 0]*b[1, 2]+0.1999999974e28*b[1, 0]*b[2, 0]+0.2509401076e20*b[1, 0]*b[2, 1]-0.9999999740e27*b[1, 0]*b[2, 2]+0.3955341829e28*b[1, 2]^2-0.9999999854e27*b[1, 2]*b[2, 0]-0.1947520867e20*b[1, 2]*b[2, 1]+0.4999999757e27*b[1, 2]*b[2, 2]-0.3464101595e19*b[2, 0]^2+0.3464101575e19*b[2, 0]*b[2, 1]+0.8660254000e19*b[2, 0]*b[2, 2]+0.2000000000e11*b[2, 1]^2-0.1732050770e19*b[2, 1]*b[2, 2]-0.3464101620e19*b[2, 2]^2+0.1600000000e29*b[0, 0]*a[0, 0]-0.8000000000e28*b[0, 0]*a[0, 2]+0.9237604304e28*b[0, 0]*a[1, 0]-0.4618802176e28*b[0, 0]*a[1, 2]-0.1600000000e20*b[0, 0]*a[2, 0]-0.2000000000e29*b[0, 2]*a[0, 0]+0.1000000000e29*b[0, 2]*a[0, 2]-0.1154700538e29*b[0, 2]*a[1, 0]+0.5773502720e28*b[0, 2]*a[1, 2]+0.2000000000e20*b[0, 2]*a[2, 0]+0.1123760430e29*b[1, 0]*a[0, 0]-0.5618802152e28*b[1, 0]*a[0, 2]+0.6488033868e28*b[1, 0]*a[1, 0]-0.1123760430e20*b[1, 0]*a[2, 0]-0.1254700541e29*b[1, 2]*a[0, 0]+0.6273502703e28*b[1, 2]*a[0, 2]-0.7244016946e28*b[1, 2]*a[1, 0]+0.3622008492e28*b[1, 2]*a[1, 2]+0.1254700541e20*b[1, 2]*a[2, 0]+0.3464101599e28*b[2, 0]*a[0, 0]-0.1732050800e28*b[2, 0]*a[0, 2]+0.1999999990e28*b[2, 0]*a[1, 0]-0.1000000000e28*b[2, 0]*a[1, 2]-0.3464101599e19*b[2, 0]*a[2, 0]+0.1600000000e20*b[2, 1]*a[0, 0]-0.8000000000e19*b[2, 1]*a[0, 2]+0.9237604304e19*b[2, 1]*a[1, 0]-0.4618802176e19*b[2, 1]*a[1, 2]-0.1600000000e11*b[2, 1]*a[2, 0]-0.1732050810e28*b[2, 2]*a[0, 0]+0.8660254050e27*b[2, 2]*a[0, 2]-0.1000000001e28*b[2, 2]*a[1, 0]+0.5000000031e27*b[2, 2]*a[1, 2]+0.1732050810e19*b[2, 2]*a[2, 0]-0.2400000000e29*b[0, 0]^2*b[0, 2]+0.1585640646e29*b[0, 0]^2*b[1, 0]-0.1485640651e29*b[0, 0]^2*b[1, 2]+0.3464101599e28*b[0, 0]^2*b[2, 0]-0.1732050754e28*b[0, 0]^2*b[2, 2]+0.4000000000e28*b[0, 0]^2*a[0, 0]-0.2000000000e28*b[0, 0]^2*a[0, 2]+0.2309401076e28*b[0, 0]^2*a[1, 0]-0.1154700544e28*b[0, 0]^2*a[1, 2]-0.4000000000e19*b[0, 0]^2*a[2, 0]+0.1800000000e29*b[0, 0]*b[0, 2]^2+0.1030940107e29*b[0, 0]*b[1, 0]^2+0.6577350318e28*b[0, 0]*b[1, 2]^2-0.6928203222e19*b[0, 0]*b[2, 0]^2+0.2000000000e20*b[0, 0]^2*b[2, 1]-0.3464101540e19*b[0, 0]*b[2, 2]^2+0.1089230484e29*b[0, 2]^2*b[1, 0]-0.7178203258e28*b[0, 2]^2*b[1, 2]+0.8660253878e27*b[0, 2]^2*b[2, 0]-0.4330126765e27*b[0, 2]^2*b[2, 2]+0.7000000000e28*b[0, 2]^2*a[0, 0]-0.3500000000e28*b[0, 2]^2*a[0, 2]+0.4041451883e28*b[0, 2]^2*a[1, 0]-0.2020725952e28*b[0, 2]^2*a[1, 2]-0.7000000000e19*b[0, 2]^2*a[2, 0]-0.9154700533e28*b[0, 2]*b[1, 0]^2-0.4288675169e28*b[0, 2]*b[1, 2]^2+0.3464101599e19*b[0, 2]*b[2, 0]^2+0.1700000000e20*b[0, 2]^2*b[2, 1]+0.1732050770e19*b[0, 2]*b[2, 2]^2-0.5618802168e28*b[1, 0]^2*b[1, 2]+0.1154700530e28*b[1, 0]^2*b[2, 0]-0.5773502486e27*b[1, 0]^2*b[2, 2]+0.2488033870e28*b[1, 0]^2*a[0, 0]-0.1244016935e28*b[1, 0]^2*a[0, 2]+0.1436467024e28*b[1, 0]^2*a[1, 0]-0.7182335159e27*b[1, 0]^2*a[1, 2]-0.2488033870e19*b[1, 0]^2*a[2, 0]+0.3964101644e28*b[1, 0]*b[1, 2]^2-0.3999999992e19*b[1, 0]*b[2, 0]^2+0.8976067738e19*b[1, 0]^2*b[2, 1]-0.1999999956e19*b[1, 0]*b[2, 2]^2+0.2886751315e27*b[1, 2]^2*b[2, 0]-0.1443375597e27*b[1, 2]^2*b[2, 2]+0.2622008486e28*b[1, 2]^2*a[0, 0]-0.1311004243e28*b[1, 2]^2*a[0, 2]+0.1513817305e28*b[1, 2]^2*a[1, 0]-0.7569086562e27*b[1, 2]^2*a[1, 2]-0.2622008486e19*b[1, 2]^2*a[2, 0]+0.1999999999e19*b[1, 2]*b[2, 0]^2+0.6244016981e19*b[1, 2]^2*b[2, 1]+0.9999999832e18*b[1, 2]*b[2, 2]^2-8660254000.*b[2, 0]^2*b[2, 2]-0.3464101619e19*b[2, 0]^2*a[0, 0]+0.1732050810e19*b[2, 0]^2*a[0, 2]-0.2000000002e19*b[2, 0]^2*a[1, 0]+0.1000000006e19*b[2, 0]^2*a[1, 2]+3464101619.*b[2, 0]^2*a[2, 0]-6928203226.*b[2, 0]^2*b[2, 1]+3464101540.*b[2, 0]*b[2, 2]^2+0.1600000000e11*b[2, 1]^2*b[0, 0]-0.2000000000e11*b[2, 1]^2*b[0, 2]+0.1123760430e11*b[2, 1]^2*b[1, 0]-0.1254700542e11*b[2, 1]^2*b[1, 2]+3464101607.*b[2, 1]^2*b[2, 0]-1732050762.*b[2, 1]^2*b[2, 2]-3464101540.*b[2, 1]*b[2, 2]^2+0.8000000000e28*b[0, 0]^3-0.4000000000e28*b[0, 2]^3+0.2206267383e28*b[1, 0]^3-0.8531337025e27*b[1, 2]^3+3464101615.*b[2, 0]^3-0.3244016951e28*b[1, 0]*a[1, 2]-0.1999999985e28*b[0, 0]*b[1, 2]*b[2, 0]+0.9999999581e27*b[0, 0]*b[1, 2]*b[2, 2]-0.1023760433e29*b[0, 0]*b[1, 2]*a[0, 0]+0.5118802165e28*b[0, 0]*b[1, 2]*a[0, 2]-0.5910683614e28*b[0, 0]*b[1, 2]*a[1, 0]+0.2955341822e28*b[0, 0]*b[1, 2]*a[1, 2]+0.1023760433e20*b[0, 0]*b[1, 2]*a[2, 0]+0.1039230475e20*b[0, 0]*b[2, 0]*b[2, 2]+0.3464101615e28*b[0, 0]*b[2, 0]*a[0, 0]-0.1732050808e28*b[0, 0]*b[2, 0]*a[0, 2]+0.1999999999e28*b[0, 0]*b[2, 0]*a[1, 0]-0.1000000005e28*b[0, 0]*b[2, 0]*a[1, 2]-0.3464101615e19*b[0, 0]*b[2, 0]*a[2, 0]-0.4400000000e20*b[0, 0]*b[2, 1]*b[0, 2]+0.2709401076e20*b[0, 0]*b[2, 1]*b[1, 0]-0.2740341192e20*b[0, 0]*b[2, 1]*b[1, 2]+0.6928203206e19*b[0, 0]*b[2, 1]*b[2, 0]-0.3464101516e19*b[0, 0]*b[2, 1]*b[2, 2]+0.4000000000e19*b[0, 0]*b[2, 1]*a[0, 0]-0.2000000000e19*b[0, 0]*b[2, 1]*a[0, 2]+0.2309401076e19*b[0, 0]*b[2, 1]*a[1, 0]-0.1154700544e19*b[0, 0]*b[2, 1]*a[1, 2]-4000000000.*b[0, 0]*b[2, 1]*a[2, 0]-0.1732050770e28*b[0, 0]*b[2, 2]*a[0, 0]+0.8660253850e27*b[0, 0]*b[2, 2]*a[0, 2]-0.9999999780e27*b[0, 0]*b[2, 2]*a[1, 0]+0.4999999916e27*b[0, 0]*b[2, 2]*a[1, 2]+0.1732050770e19*b[0, 0]*b[2, 2]*a[2, 0]+0.1315470058e29*b[0, 2]*b[1, 0]*b[1, 2]-0.1999999974e28*b[0, 2]*b[1, 0]*b[2, 0]+0.9999999529e27*b[0, 2]*b[1, 0]*b[2, 2]-0.1023760430e29*b[0, 2]*b[1, 0]*a[0, 0]+0.5118802152e28*b[0, 2]*b[1, 0]*a[0, 2]-0.5910683599e28*b[0, 2]*b[1, 0]*a[1, 0]+0.2955341815e28*b[0, 2]*b[1, 0]*a[1, 2]+0.1023760430e20*b[0, 2]*b[1, 0]*a[2, 0]+0.9999999854e27*b[0, 2]*b[1, 2]*b[2, 0]-0.4999999721e27*b[0, 2]*b[1, 2]*b[2, 2]+0.8582903797e28*b[0, 2]*b[1, 2]*a[0, 0]-0.4291451898e28*b[0, 2]*b[1, 2]*a[0, 2]+0.4955341816e28*b[0, 2]*b[1, 2]*a[1, 0]-0.2477670921e28*b[0, 2]*b[1, 2]*a[1, 2]-0.8582903797e19*b[0, 2]*b[1, 2]*a[2, 0]-0.5196152353e19*b[0, 2]*b[2, 0]*b[2, 2]-0.1732050796e28*b[0, 2]*b[2, 0]*a[0, 0]+0.8660253978e27*b[0, 2]*b[2, 0]*a[0, 2]-0.9999999927e27*b[0, 2]*b[2, 0]*a[1, 0]+0.4999999989e27*b[0, 2]*b[2, 0]*a[1, 2]+0.1732050796e19*b[0, 2]*b[2, 0]*a[2, 0]-0.2740341184e20*b[0, 2]*b[2, 1]*b[1, 0]+0.2062990923e20*b[0, 2]*b[2, 1]*b[1, 2]-0.3464101579e19*b[0, 2]*b[2, 1]*b[2, 0]+0.1732050734e19*b[0, 2]*b[2, 1]*b[2, 2]-0.1400000000e20*b[0, 2]*b[2, 1]*a[0, 0]+0.7000000000e19*b[0, 2]*b[2, 1]*a[0, 2]-0.8082903766e19*b[0, 2]*b[2, 1]*a[1, 0]+0.4041451904e19*b[0, 2]*b[2, 1]*a[1, 2]+0.1400000000e11*b[0, 2]*b[2, 1]*a[2, 0]+0.8660253850e27*b[0, 2]*b[2, 2]*a[0, 0]-0.4330126925e27*b[0, 2]*b[2, 2]*a[0, 2]+0.4999999890e27*b[0, 2]*b[2, 2]*a[1, 0]-0.2499999958e27*b[0, 2]*b[2, 2]*a[1, 2]-0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 0]-0.1154700528e28*b[1, 0]*b[1, 2]*b[2, 0]+0.5773502436e27*b[1, 0]*b[1, 2]*b[2, 2]-0.6488033886e28*b[1, 0]*b[1, 2]*a[0, 0]+0.3244016943e28*b[1, 0]*b[1, 2]*a[0, 2]-0.3745868109e28*b[1, 0]*b[1, 2]*a[1, 0]+0.1872934064e28*b[1, 0]*b[1, 2]*a[1, 2]+0.6488033886e19*b[1, 0]*b[1, 2]*a[2, 0]+0.5999999941e19*b[1, 0]*b[2, 0]*b[2, 2]+0.1999999997e28*b[1, 0]*b[2, 0]*a[0, 0]-0.9999999986e27*b[1, 0]*b[2, 0]*a[0, 2]+0.1154700536e28*b[1, 0]*b[2, 0]*a[1, 0]-0.5773502712e27*b[1, 0]*b[2, 0]*a[1, 2]-0.1999999997e19*b[1, 0]*b[2, 0]*a[2, 0]-0.1697606779e20*b[1, 0]*b[2, 1]*b[1, 2]+0.3999999981e19*b[1, 0]*b[2, 1]*b[2, 0]-0.1999999938e19*b[1, 0]*b[2, 1]*b[2, 2]+0.4309401076e19*b[1, 0]*b[2, 1]*a[0, 0]-0.2154700538e19*b[1, 0]*b[2, 1]*a[0, 2]+0.2488033870e19*b[1, 0]*b[2, 1]*a[1, 0]-0.1244016942e19*b[1, 0]*b[2, 1]*a[1, 2]-4309401076.*b[1, 0]*b[2, 1]*a[2, 0]-0.9999999780e27*b[1, 0]*b[2, 2]*a[0, 0]+0.4999999890e27*b[1, 0]*b[2, 2]*a[0, 2]-0.5773502563e27*b[1, 0]*b[2, 2]*a[1, 0]+0.2886751296e27*b[1, 0]*b[2, 2]*a[1, 2]+0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 0]-0.2999999972e19*b[1, 2]*b[2, 0]*b[2, 2]-0.9999999969e27*b[1, 2]*b[2, 0]*a[0, 0]+0.4999999984e27*b[1, 2]*b[2, 0]*a[0, 2]-0.5773502672e27*b[1, 2]*b[2, 0]*a[1, 0]+0.2886751351e27*b[1, 2]*b[2, 0]*a[1, 2]+0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 0]-0.1999999987e19*b[1, 2]*b[2, 1]*b[2, 0]+0.9999999604e18*b[1, 2]*b[2, 1]*b[2, 2]-0.9082903786e19*b[1, 2]*b[2, 1]*a[0, 0]+0.4541451893e19*b[1, 2]*b[2, 1]*a[0, 2]-0.5244016944e19*b[1, 2]*b[2, 1]*a[1, 0]+0.2622008486e19*b[1, 2]*b[2, 1]*a[1, 2]+9082903786.*b[1, 2]*b[2, 1]*a[2, 0]+0.4999999916e27*b[1, 2]*b[2, 2]*a[0, 0]-0.2499999958e27*b[1, 2]*b[2, 2]*a[0, 2]+0.2886751296e27*b[1, 2]*b[2, 2]*a[1, 0]-0.1443375656e27*b[1, 2]*b[2, 2]*a[1, 2]-0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 0]+0.1039230476e11*b[2, 0]*b[2, 1]*b[2, 2]+0.3464101619e19*b[2, 0]*b[2, 1]*a[0, 0]-0.1732050810e19*b[2, 0]*b[2, 1]*a[0, 2]+0.2000000002e19*b[2, 0]*b[2, 1]*a[1, 0]-0.1000000006e19*b[2, 0]*b[2, 1]*a[1, 2]-3464101619.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050770e19*b[2, 0]*b[2, 2]*a[0, 0]-0.8660253850e18*b[2, 0]*b[2, 2]*a[0, 2]+0.9999999780e18*b[2, 0]*b[2, 2]*a[1, 0]-0.4999999916e18*b[2, 0]*b[2, 2]*a[1, 2]-1732050770.*b[2, 0]*b[2, 2]*a[2, 0]-0.1732050770e19*b[2, 1]*b[2, 2]*a[0, 0]+0.8660253850e18*b[2, 1]*b[2, 2]*a[0, 2]-0.9999999780e18*b[2, 1]*b[2, 2]*a[1, 0]+0.4999999916e18*b[2, 1]*b[2, 2]*a[1, 2]+1732050770.*b[2, 1]*b[2, 2]*a[2, 0]+0.7600000000e20*a[2, 2]*b[0, 0]-0.8600000000e20*a[2, 2]*b[0, 2]+0.5187862044e20*a[2, 2]*b[1, 0]-0.5365212326e20*a[2, 2]*b[1, 2]+0.1385640638e20*a[2, 2]*b[2, 0]+0.7600000000e11*a[2, 2]*b[2, 1]-0.6928203240e19*a[2, 2]*b[2, 2]+0.1600000000e20*b[0, 0]*a[2, 1]-0.2000000000e20*b[0, 2]*a[2, 1]+0.1123760430e20*b[1, 0]*a[2, 1]-0.1254700541e20*b[1, 2]*a[2, 1]+0.3464101599e19*b[2, 0]*a[2, 1]+0.1600000000e11*b[2, 1]*a[2, 1]+0.4000000000e19*b[0, 0]^2*a[2, 1]+0.2800000000e20*b[0, 0]^2*a[2, 2]-0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 1]-0.7600000000e20*b[0, 0]*b[0, 2]*a[2, 2]+0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 1]+0.4033161506e20*b[0, 0]*b[1, 0]*a[2, 2]-0.1023760433e20*b[0, 0]*b[1, 2]*a[2, 1]-0.4787862058e20*b[0, 0]*b[1, 2]*a[2, 2]+0.3464101615e19*b[0, 0]*b[2, 0]*a[2, 1]+0.1385640644e20*b[0, 0]*b[2, 0]*a[2, 2]+4000000000.*b[0, 0]*b[2, 1]*a[2, 1]+0.4000000000e11*b[0, 0]*b[2, 1]*a[2, 2]-0.1023760430e20*b[0, 2]*b[1, 0]*a[2, 1]-0.4787862044e20*b[0, 2]*b[1, 0]*a[2, 2]+0.8582903797e19*b[0, 2]*b[1, 2]*a[2, 1]+0.3779571682e20*b[0, 2]*b[1, 2]*a[2, 2]-0.1732050796e19*b[0, 2]*b[2, 0]*a[2, 1]-0.6928203170e19*b[0, 2]*b[2, 0]*a[2, 2]-0.1400000000e11*b[0, 2]*b[2, 1]*a[2, 1]-0.6800000000e11*b[0, 2]*b[2, 1]*a[2, 2]-0.6488033886e19*b[1, 0]*b[1, 2]*a[2, 1]-0.2995213556e20*b[1, 0]*b[1, 2]*a[2, 2]+0.1999999997e19*b[1, 0]*b[2, 0]*a[2, 1]+0.7999999975e19*b[1, 0]*b[2, 0]*a[2, 2]+4309401076.*b[1, 0]*b[2, 1]*a[2, 1]+0.3109401076e11*b[1, 0]*b[2, 1]*a[2, 2]-0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 1]-0.3999999981e19*b[1, 2]*b[2, 0]*a[2, 2]-9082903786.*b[1, 2]*b[2, 1]*a[2, 1]-0.4325981841e11*b[1, 2]*b[2, 1]*a[2, 2]+3464101619.*b[2, 0]*b[2, 1]*a[2, 1]+0.1385640645e11*b[2, 0]*b[2, 1]*a[2, 2]+4.*b[2, 1]^3+0.7000000000e19*b[0, 2]^2*a[2, 1]+0.3100000000e20*b[0, 2]^2*a[2, 2]+0.2488033870e19*b[1, 0]^2*a[2, 1]+0.1395213548e20*b[1, 0]^2*a[2, 2]+0.2622008486e19*b[1, 2]^2*a[2, 1]+0.1148803395e20*b[1, 2]^2*a[2, 2]-3464101619.*b[2, 0]^2*a[2, 1]-0.1385640646e11*b[2, 0]^2*a[2, 2]+12.*b[2, 1]^2*a[2, 2]-0.6928203080e19*b[0, 0]*a[2, 2]*b[2, 2]+0.3464101540e19*b[0, 2]*a[2, 2]*b[2, 2]-0.3999999912e19*b[1, 0]*a[2, 2]*b[2, 2]+0.1999999966e19*b[1, 2]*a[2, 2]*b[2, 2]+6928203080.*b[2, 0]*a[2, 2]*b[2, 2]-6928203080.*b[2, 1]*a[2, 2]*b[2, 2]-0.1732050810e19*b[2, 2]*a[2, 1]-0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 1]+0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 1]-0.1732050770e19*b[0, 0]*b[2, 2]*a[2, 1]+0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 1]+1732050770.*b[2, 0]*b[2, 2]*a[2, 1]-1732050770.*b[2, 1]*b[2, 2]*a[2, 1]-0.2971281291e29*b[0, 0]*b[0, 2]*b[1, 0]+0.2178460977e29*b[0, 0]*b[0, 2]*b[1, 2]-0.3464101575e28*b[0, 0]*b[0, 2]*b[2, 0]+0.1732050730e28*b[0, 0]*b[0, 2]*b[2, 2]-0.1600000000e29*b[0, 0]*b[0, 2]*a[0, 0]+0.8000000000e28*b[0, 0]*b[0, 2]*a[0, 2]-0.9237604304e28*b[0, 0]*b[0, 2]*a[1, 0]+0.4618802176e28*b[0, 0]*b[0, 2]*a[1, 2]+0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 0]-0.1830940113e29*b[0, 0]*b[1, 0]*b[1, 2]+0.3999999976e28*b[0, 0]*b[1, 0]*b[2, 0]-0.1999999933e28*b[0, 0]*b[1, 0]*b[2, 2]+0.6618802152e28*b[0, 0]*b[1, 0]*a[0, 0]-0.3309401076e28*b[0, 0]*b[1, 0]*a[0, 2]+0.3821367203e28*b[0, 0]*b[1, 0]*a[1, 0])/((1000000000.+1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1])*(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2]))

(27)

for j from 0 to N-1 do s[j] := simplify(evalf(eq33)) end do;

-1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-8*a[2, 2]+2.*a[0, 1]-6.*a[0, 2]

 

1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-7*a[2, 2]+2.*a[0, 1]-6.*a[0, 2]

(28)

for j from 0 to N-1 do w[j] := simplify(evalf(eq44)) end do

-1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-8*a[2, 2]+2.*a[0, 1]+6.*a[0, 2]

 

1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-7*a[2, 2]+2.*a[0, 1]+6.*a[0, 2]

(29)

for j from 0 to N-1 do ww[j] := simplify(evalf(eq55)) end do

-1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]+3.464101615*b[1, 2]-0.1000000000e-9*b[2, 1]-0.1000000000e-8*b[2, 2]

 

1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]-3.464101615*b[1, 2]+0.1000000000e-7*b[2, 2]

(30)

for j from 0 to N-1 do www[j] := simplify(evalf(eq66)) end do

-1.154700538*b[1, 1]-3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-9*b[2, 1]+0.1000000000e-8*b[2, 2]

 

1.154700538*b[1, 1]+3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-7*b[2, 2]

(31)

for i from 0 to M do www1[i] := simplify(evalf(eq77)) end do

a[0, 0]-1.*a[0, 1]+a[0, 2]-1.*a[1, 0]+a[1, 1]-1.*a[1, 2]+a[2, 0]-1.*a[2, 1]+a[2, 2]

 

a[0, 0]-.5000000000*a[0, 2]-1.*a[1, 0]+.5000000000*a[1, 2]+a[2, 0]-.5000000000*a[2, 2]

 

a[0, 0]+a[0, 1]+a[0, 2]-1.*a[1, 0]-1.*a[1, 1]-1.*a[1, 2]+a[2, 0]+a[2, 1]+a[2, 2]

(32)

for i from 0 to M do ww1[i] := simplify(evalf(eq88)) end do

b[0, 0]-1.*b[0, 1]+b[0, 2]-1.*b[1, 0]+b[1, 1]-1.*b[1, 2]+b[2, 0]-1.*b[2, 1]+b[2, 2]

 

-.5000000000*b[0, 2]+.5000000000*b[1, 2]-.5000000000*b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0]

 

b[0, 1]+b[0, 2]-1.*b[1, 1]-1.*b[1, 2]+b[2, 1]+b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0]

(33)

fsolve({s[0] = 0, s[1] = 0, s[1, 0] = 0, s[1, 1] = 0, w[0] = 0, w[1] = 0, w[1, 0] = 0, w[1, 1] = 0, ww[0] = 0, ww[1] = 0, ww1[0] = 0, ww1[1] = 0, ww1[2] = 0, www[0] = 0, www[1] = 0, www1[0] = 0, www1[1] = 0, www1[2] = 0}, {a[0, 0], a[0, 1], a[0, 2], a[1, 0], a[1, 1], a[1, 2], a[2, 0], a[2, 1], a[2, 2], b[0, 0], b[0, 1], b[0, 2], b[1, 0], b[1, 1], b[1, 2], b[2, 0], b[2, 1], b[2, 2]})

fsolve({-0.4000000000e-19*(0.8333333339e29*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e21*b[0, 0]*b[1, 0]*a[2, 0]+0.2500000000e30*b[0, 0]^2-0.2500000000e30*b[0, 0]*b[0, 2]-0.2886751346e30*b[0, 0]*b[1, 0]+0.1443375675e30*b[0, 0]*b[1, 2]+0.2000000000e21*b[0, 0]*b[2, 0]+0.1000000000e21*b[0, 0]*b[2, 1]-0.3750000000e21*b[0, 0]*b[2, 2]+0.6250000000e29*b[0, 2]^2+0.1443375673e30*b[0, 2]*b[1, 0]-0.7216878375e29*b[0, 2]*b[1, 2]-0.1000000000e21*b[0, 2]*b[2, 0]-0.5000000000e20*b[0, 2]*b[2, 1]+0.1875000000e21*b[0, 2]*b[2, 2]+0.8333333334e29*b[1, 0]^2-0.8333333345e29*b[1, 0]*b[1, 2]-0.1154700538e21*b[1, 0]*b[2, 0]-0.5773502692e20*b[1, 0]*b[2, 1]+0.2165063510e21*b[1, 0]*b[2, 2]+0.2083333339e29*b[1, 2]^2+0.5773502700e20*b[1, 2]*b[2, 0]+0.2886751350e20*b[1, 2]*b[2, 1]-0.1082531756e21*b[1, 2]*b[2, 2]+0.4000000000e11*b[2, 0]^2+0.4000000000e11*b[2, 0]*b[2, 1]-0.1500000000e12*b[2, 0]*b[2, 2]-0.5000000000e11*b[2, 1]*b[2, 2]+0.1250000000e12*b[2, 2]^2+0.9000000000e31*b[0, 0]*a[0, 2]-0.5000000000e30*b[0, 0]*a[1, 0]-0.4946152423e31*b[0, 0]*a[1, 2]+0.8660254038e30*b[0, 0]*a[2, 0]-0.4500000000e31*b[0, 2]*a[0, 2]+0.2500000000e30*b[0, 2]*a[1, 0]+0.2473076211e31*b[0, 2]*a[1, 2]-0.4330127019e30*b[0, 2]*a[2, 0]-0.5196152423e31*b[1, 0]*a[0, 2]+0.2886751346e30*b[1, 0]*a[1, 0]-0.5000000000e30*b[1, 0]*a[2, 0]+0.2598076215e31*b[1, 2]*a[0, 2]-0.1443375675e30*b[1, 2]*a[1, 0]-0.1427831218e31*b[1, 2]*a[1, 2]+0.2500000004e30*b[1, 2]*a[2, 0]+0.3600000000e22*b[2, 0]*a[0, 2]-0.2000000000e21*b[2, 0]*a[1, 0]-0.1978460969e22*b[2, 0]*a[1, 2]+0.3464101615e21*b[2, 0]*a[2, 0]-0.2000000000e11*b[2, 1]*a[1, 2]+0.4000000000e11*b[2, 1]*a[2, 0]-0.4500000000e22*b[2, 2]*a[0, 2]+0.2500000000e21*b[2, 2]*a[1, 0]+0.2473076211e22*b[2, 2]*a[1, 2]-0.4330127020e21*b[2, 2]*a[2, 0]+0.3750000000e30*b[0, 0]^2*b[0, 2]+0.4330127019e30*b[0, 0]^2*b[1, 0]-0.2165063512e30*b[0, 0]^2*b[1, 2]-0.3000000000e21*b[0, 0]^2*b[2, 0]+0.6250000000e21*b[0, 0]^2*b[2, 2]-0.2500000000e30*b[0, 0]^2*a[0, 0]+0.1250000000e30*b[0, 0]^2*a[0, 2]+0.1443375673e30*b[0, 0]^2*a[1, 0]-0.7216878370e29*b[0, 0]^2*a[1, 2]-0.1000000000e21*b[0, 0]^2*a[2, 0]-0.1875000000e30*b[0, 0]*b[0, 2]^2-0.2500000000e30*b[0, 0]*b[1, 0]^2-0.6250000018e29*b[0, 0]*b[1, 2]^2-0.1200000000e12*b[0, 0]*b[2, 0]^2-0.2000000000e21*b[0, 0]^2*b[2, 1]-0.5000000000e12*b[0, 0]*b[2, 2]^2+0.1082531755e30*b[0, 2]^2*b[1, 0]-0.5412658781e29*b[0, 2]^2*b[1, 2]-0.7500000000e20*b[0, 2]^2*b[2, 0]+0.1562500000e21*b[0, 2]^2*b[2, 2]-0.6250000000e29*b[0, 2]^2*a[0, 0]+0.3125000000e29*b[0, 2]^2*a[0, 2]+0.3608439182e29*b[0, 2]^2*a[1, 0]-0.1804219592e29*b[0, 2]^2*a[1, 2]-0.2500000000e20*b[0, 2]^2*a[2, 0]+0.1250000000e30*b[0, 2]*b[1, 0]^2+0.3125000009e29*b[0, 2]*b[1, 2]^2+0.6000000000e11*b[0, 2]*b[2, 0]^2-0.5000000000e20*b[0, 2]^2*b[2, 1]+0.2500000000e12*b[0, 2]*b[2, 2]^2-0.7216878375e29*b[1, 0]^2*b[1, 2]-0.1000000000e21*b[1, 0]^2*b[2, 0]+0.2083333333e21*b[1, 0]^2*b[2, 2]-0.8333333334e29*b[1, 0]^2*a[0, 0]+0.4166666667e29*b[1, 0]^2*a[0, 2]+0.4811252244e29*b[1, 0]^2*a[1, 0]-0.2405626123e29*b[1, 0]^2*a[1, 2]-0.3333333333e20*b[1, 0]^2*a[2, 0]+0.3608439193e29*b[1, 0]*b[1, 2]^2+0.6928203230e11*b[1, 0]*b[2, 0]^2-0.6666666667e20*b[1, 0]^2*b[2, 1]+0.2886751346e12*b[1, 0]*b[2, 2]^2-0.2500000007e20*b[1, 2]^2*b[2, 0]+0.5208333348e20*b[1, 2]^2*b[2, 2]-0.2083333339e29*b[1, 2]^2*a[0, 0]+0.1041666670e29*b[1, 2]^2*a[0, 2]+0.1202813064e29*b[1, 2]^2*a[1, 0]-0.6014065325e28*b[1, 2]^2*a[1, 2]-0.8333333357e19*b[1, 2]^2*a[2, 0]-0.3464101620e11*b[1, 2]*b[2, 0]^2-0.1666666671e20*b[1, 2]^2*b[2, 1]-0.1443375675e12*b[1, 2]*b[2, 2]^2+100.*b[2, 0]^2*b[2, 2]-0.4000000000e11*b[2, 0]^2*a[0, 0]+0.2000000000e11*b[2, 0]^2*a[0, 2]+0.2309401077e11*b[2, 0]^2*a[1, 0]-0.1154700539e11*b[2, 0]^2*a[1, 2]-16.*b[2, 0]^2*a[2, 0]-32.*b[2, 0]^2*b[2, 1]-200.*b[2, 0]*b[2, 2]^2-0.4000000000e11*b[2, 1]^2*b[0, 0]+0.2000000000e11*b[2, 1]^2*b[0, 2]+0.2309401077e11*b[2, 1]^2*b[1, 0]-0.1154700540e11*b[2, 1]^2*b[1, 2]-16.*b[2, 1]^2*b[2, 0]+20.*b[2, 1]^2*b[2, 2]-0.4000000000e11*b[2, 1]^2*a[0, 0]+0.2000000000e11*b[2, 1]^2*a[0, 2]+0.2309401077e11*b[2, 1]^2*a[1, 0]-0.1154700539e11*b[2, 1]^2*a[1, 2]-16.*b[2, 1]^2*a[2, 0]-100.*b[2, 1]*b[2, 2]^2-0.2500000000e30*b[0, 0]^3+0.3125000000e29*b[0, 2]^3+0.4811252244e29*b[1, 0]^3-0.6014065329e28*b[1, 2]^3-16.*b[2, 0]^3+125.*b[2, 2]^3+0.2855662433e31*b[1, 0]*a[1, 2]-0.1732050810e21*b[0, 0]*b[1, 2]*b[2, 0]+0.3608439188e21*b[0, 0]*b[1, 2]*b[2, 2]-0.1443375675e30*b[0, 0]*b[1, 2]*a[0, 0]+0.7216878375e29*b[0, 0]*b[1, 2]*a[0, 2]+0.8333333345e29*b[0, 0]*b[1, 2]*a[1, 0]-0.4166666675e29*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502700e20*b[0, 0]*b[1, 2]*a[2, 0]+0.5000000000e12*b[0, 0]*b[2, 0]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 0]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 0]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 0]*a[2, 0]+0.2000000000e21*b[0, 0]*b[2, 1]*b[0, 2]+0.2309401077e21*b[0, 0]*b[2, 1]*b[1, 0]-0.1154700540e21*b[0, 0]*b[2, 1]*b[1, 2]-0.1600000000e12*b[0, 0]*b[2, 1]*b[2, 0]+0.3000000000e12*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 2]+0.1154700538e21*b[0, 0]*b[2, 1]*a[1, 0]-0.5773502696e20*b[0, 0]*b[2, 1]*a[1, 2]-0.8000000000e11*b[0, 0]*b[2, 1]*a[2, 0]+0.5000000000e21*b[0, 0]*b[2, 2]*a[0, 0]-0.2500000000e21*b[0, 0]*b[2, 2]*a[0, 2]-0.2886751346e21*b[0, 0]*b[2, 2]*a[1, 0]+0.1443375674e21*b[0, 0]*b[2, 2]*a[1, 2]+0.2000000000e12*b[0, 0]*b[2, 2]*a[2, 0]-0.1250000002e30*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050808e21*b[0, 2]*b[1, 0]*b[2, 0]+0.3608439182e21*b[0, 2]*b[1, 0]*b[2, 2]-0.1443375673e30*b[0, 2]*b[1, 0]*a[0, 0]+0.7216878365e29*b[0, 2]*b[1, 0]*a[0, 2]+0.8333333334e29*b[0, 2]*b[1, 0]*a[1, 0]-0.4166666670e29*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502692e20*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254050e20*b[0, 2]*b[1, 2]*b[2, 0]-0.1804219594e21*b[0, 2]*b[1, 2]*b[2, 2]+0.7216878375e29*b[0, 2]*b[1, 2]*a[0, 0]-0.3608439188e29*b[0, 2]*b[1, 2]*a[0, 2]-0.4166666673e29*b[0, 2]*b[1, 2]*a[1, 0]+0.2083333338e29*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751350e20*b[0, 2]*b[1, 2]*a[2, 0]-0.2500000000e12*b[0, 2]*b[2, 0]*b[2, 2]+0.1000000000e21*b[0, 2]*b[2, 0]*a[0, 0]-0.5000000000e20*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502692e20*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751348e20*b[0, 2]*b[2, 0]*a[1, 2]+0.4000000000e11*b[0, 2]*b[2, 0]*a[2, 0]-0.1154700538e21*b[0, 2]*b[2, 1]*b[1, 0]+0.5773502700e20*b[0, 2]*b[2, 1]*b[1, 2]+0.8000000000e11*b[0, 2]*b[2, 1]*b[2, 0]-0.1500000000e12*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e21*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e20*b[0, 2]*b[2, 1]*a[0, 2]-0.5773502692e20*b[0, 2]*b[2, 1]*a[1, 0]+0.2886751348e20*b[0, 2]*b[2, 1]*a[1, 2]+0.4000000000e11*b[0, 2]*b[2, 1]*a[2, 0]-0.2500000000e21*b[0, 2]*b[2, 2]*a[0, 0]+0.1250000000e21*b[0, 2]*b[2, 2]*a[0, 2]+0.1443375673e21*b[0, 2]*b[2, 2]*a[1, 0]-0.7216878370e20*b[0, 2]*b[2, 2]*a[1, 2]-0.1000000000e12*b[0, 2]*b[2, 2]*a[2, 0]+0.1000000001e21*b[1, 0]*b[1, 2]*b[2, 0]-0.2083333336e21*b[1, 0]*b[1, 2]*b[2, 2]+0.8333333345e29*b[1, 0]*b[1, 2]*a[0, 0]-0.4166666673e29*b[1, 0]*b[1, 2]*a[0, 2]-0.4811252250e29*b[1, 0]*b[1, 2]*a[1, 0]+0.2405626127e29*b[1, 0]*b[1, 2]*a[1, 2]+0.3333333338e20*b[1, 0]*b[1, 2]*a[2, 0]-0.2886751346e12*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e21*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502692e20*b[1, 0]*b[2, 0]*a[0, 2]-0.6666666667e20*b[1, 0]*b[2, 0]*a[1, 0]+0.3333333336e20*b[1, 0]*b[2, 0]*a[1, 2]+0.4618802154e11*b[1, 0]*b[2, 0]*a[2, 0]+0.6666666676e20*b[1, 0]*b[2, 1]*b[1, 2]+0.9237604307e11*b[1, 0]*b[2, 1]*b[2, 0]-0.1732050808e12*b[1, 0]*b[2, 1]*b[2, 2]+0.1154700538e21*b[1, 0]*b[2, 1]*a[0, 0]-0.5773502692e20*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666667e20*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333336e20*b[1, 0]*b[2, 1]*a[1, 2]+0.4618802154e11*b[1, 0]*b[2, 1]*a[2, 0]-0.2886751346e21*b[1, 0]*b[2, 2]*a[0, 0]+0.1443375673e21*b[1, 0]*b[2, 2]*a[0, 2]+0.1666666667e21*b[1, 0]*b[2, 2]*a[1, 0]-0.8333333339e20*b[1, 0]*b[2, 2]*a[1, 2]-0.1154700538e12*b[1, 0]*b[2, 2]*a[2, 0]+0.1443375675e12*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502700e20*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751350e20*b[1, 2]*b[2, 0]*a[0, 2]+0.3333333338e20*b[1, 2]*b[2, 0]*a[1, 0]-0.1666666670e20*b[1, 2]*b[2, 0]*a[1, 2]-0.2309401080e11*b[1, 2]*b[2, 0]*a[2, 0]-0.4618802160e11*b[1, 2]*b[2, 1]*b[2, 0]+0.8660254050e11*b[1, 2]*b[2, 1]*b[2, 2]-0.5773502700e20*b[1, 2]*b[2, 1]*a[0, 0]+0.2886751350e20*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333338e20*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666670e20*b[1, 2]*b[2, 1]*a[1, 2]-0.2309401080e11*b[1, 2]*b[2, 1]*a[2, 0]+0.1443375675e21*b[1, 2]*b[2, 2]*a[0, 0]-0.7216878375e20*b[1, 2]*b[2, 2]*a[0, 2]-0.8333333345e20*b[1, 2]*b[2, 2]*a[1, 0]+0.4166666675e20*b[1, 2]*b[2, 2]*a[1, 2]+0.5773502700e11*b[1, 2]*b[2, 2]*a[2, 0]+120.*b[2, 0]*b[2, 1]*b[2, 2]-0.8000000000e11*b[2, 0]*b[2, 1]*a[0, 0]+0.4000000000e11*b[2, 0]*b[2, 1]*a[0, 2]+0.4618802154e11*b[2, 0]*b[2, 1]*a[1, 0]-0.2309401078e11*b[2, 0]*b[2, 1]*a[1, 2]-32.*b[2, 0]*b[2, 1]*a[2, 0]+0.2000000000e12*b[2, 0]*b[2, 2]*a[0, 0]-0.1000000000e12*b[2, 0]*b[2, 2]*a[0, 2]-0.1154700538e12*b[2, 0]*b[2, 2]*a[1, 0]+0.5773502696e11*b[2, 0]*b[2, 2]*a[1, 2]+80.*b[2, 0]*b[2, 2]*a[2, 0]+0.2000000000e12*b[2, 1]*b[2, 2]*a[0, 0]-0.1000000000e12*b[2, 1]*b[2, 2]*a[0, 2]-0.1154700538e12*b[2, 1]*b[2, 2]*a[1, 0]+0.5773502696e11*b[2, 1]*b[2, 2]*a[1, 2]+80.*b[2, 1]*b[2, 2]*a[2, 0]-0.2500000000e12*b[2, 2]^2*a[0, 0]+0.1250000000e12*b[2, 2]^2*a[0, 2]+0.1443375673e12*b[2, 2]^2*a[1, 0]-0.7216878370e11*b[2, 2]^2*a[1, 2]-100.*b[2, 2]^2*a[2, 0]+0.5000000000e20*a[1, 1]*b[0, 0]-0.2500000000e20*a[1, 1]*b[0, 2]-0.2886751346e20*a[1, 1]*b[1, 0]+0.1443375675e20*a[1, 1]*b[1, 2]+0.2000000000e11*a[1, 1]*b[2, 0]+0.2000000000e11*a[1, 1]*b[2, 1]-0.5000000000e11*a[1, 1]*b[2, 2]-0.4330127014e30*a[2, 2]*b[0, 0]+0.2165063507e30*a[2, 2]*b[0, 2]+0.2499999997e30*a[2, 2]*b[1, 0]-0.1250000000e30*a[2, 2]*b[1, 2]-0.1732050806e21*a[2, 2]*b[2, 0]+0.5000000000e11*a[2, 2]*b[2, 1]+0.2165063506e21*a[2, 2]*b[2, 2]-0.4330127015e30*a[2, 2]*a[0, 0]+0.2165063508e30*a[2, 2]*a[0, 2]+0.2499999998e30*a[2, 2]*a[1, 0]-0.1250000000e30*a[2, 2]*a[1, 2]-0.1732050806e21*a[2, 2]*a[2, 0]+0.9000000000e31*a[0, 2]*a[0, 0]-0.4500000000e31*a[0, 2]^2-0.4946152423e31*a[0, 2]*a[1, 0]+0.5071152424e31*a[0, 2]*a[1, 2]-0.4330126983e30*a[0, 2]*a[2, 0]-0.5000000000e30*a[1, 0]*a[0, 0]+0.2886751346e30*a[1, 0]^2+0.2711324865e31*a[1, 0]*a[1, 2]-0.5000000002e30*a[1, 0]*a[2, 0]-0.4946152422e31*a[1, 2]*a[0, 0]-0.1427831217e31*a[1, 2]^2+0.2499999982e30*a[1, 2]*a[2, 0]+0.8660254038e30*a[2, 0]*a[0, 0]+0.3464101615e21*a[2, 0]^2-0.4330127019e30*b[0, 0]*b[0, 2]*b[1, 0]+0.2165063512e30*b[0, 0]*b[0, 2]*b[1, 2]+0.3000000000e21*b[0, 0]*b[0, 2]*b[2, 0]-0.6250000000e21*b[0, 0]*b[0, 2]*b[2, 2]+0.2500000000e30*b[0, 0]*b[0, 2]*a[0, 0]-0.1250000000e30*b[0, 0]*b[0, 2]*a[0, 2]-0.1443375673e30*b[0, 0]*b[0, 2]*a[1, 0]+0.7216878370e29*b[0, 0]*b[0, 2]*a[1, 2]+0.1000000000e21*b[0, 0]*b[0, 2]*a[2, 0]+0.2500000004e30*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101615e21*b[0, 0]*b[1, 0]*b[2, 0]-0.7216878365e21*b[0, 0]*b[1, 0]*b[2, 2]+0.2886751346e30*b[0, 0]*b[1, 0]*a[0, 0]-0.1443375673e30*b[0, 0]*b[1, 0]*a[0, 2]-0.1666666667e30*b[0, 0]*b[1, 0]*a[1, 0])/(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0]) = 0, -0.1000000000e-17*(0.3333333348e27*b[0, 0]*b[1, 0]*a[1, 2]+0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 0]+0.1000000000e28*b[0, 0]^2-0.1000000000e28*b[0, 0]*b[0, 2]+0.1154700538e28*b[0, 0]*b[1, 0]-0.5773502720e27*b[0, 0]*b[1, 2]-0.2000000000e19*b[0, 0]*b[2, 0]+0.2000000000e19*b[0, 0]*b[2, 1]+0.2000000000e19*b[0, 0]*b[2, 2]+0.2500000000e27*b[0, 2]^2-0.5773502690e27*b[0, 2]*b[1, 0]+0.2886751360e27*b[0, 2]*b[1, 2]+0.1000000000e19*b[0, 2]*b[2, 0]-0.1000000000e19*b[0, 2]*b[2, 1]-0.1000000000e19*b[0, 2]*b[2, 2]+0.3333333331e27*b[1, 0]^2-0.3333333348e27*b[1, 0]*b[1, 2]-0.1154700538e19*b[1, 0]*b[2, 0]+0.1154700538e19*b[1, 0]*b[2, 1]+0.1154700538e19*b[1, 0]*b[2, 2]+0.8333333414e26*b[1, 2]^2+0.5773502720e18*b[1, 2]*b[2, 0]-0.5773502720e18*b[1, 2]*b[2, 1]-0.5773502720e18*b[1, 2]*b[2, 2]+1000000000.*b[2, 0]^2-2000000000.*b[2, 0]*b[2, 1]-2000000000.*b[2, 0]*b[2, 2]+1000000000.*b[2, 1]^2+2000000000.*b[2, 1]*b[2, 2]+0.3600000000e29*b[0, 0]*a[0, 2]-0.2000000000e28*b[0, 0]*a[1, 0]+0.2178460969e29*b[0, 0]*a[1, 2]-0.3464101615e28*b[0, 0]*a[2, 0]-0.1800000000e29*b[0, 2]*a[0, 2]+0.1000000000e28*b[0, 2]*a[1, 0]-0.1089230484e29*b[0, 2]*a[1, 2]+0.1732050808e28*b[0, 2]*a[2, 0]+0.2078460968e29*b[1, 0]*a[0, 2]-0.1154700538e28*b[1, 0]*a[1, 0]-0.1999999999e28*b[1, 0]*a[2, 0]-0.1039230490e29*b[1, 2]*a[0, 2]+0.5773502720e27*b[1, 2]*a[1, 0]-0.6288675165e28*b[1, 2]*a[1, 2]+0.1000000005e28*b[1, 2]*a[2, 0]-0.3600000000e20*b[2, 0]*a[0, 2]+0.2000000000e19*b[2, 0]*a[1, 0]-0.2178460969e20*b[2, 0]*a[1, 2]+0.3464101615e19*b[2, 0]*a[2, 0]+0.3600000000e20*b[2, 1]*a[0, 2]-0.2000000000e19*b[2, 1]*a[1, 0]+0.2178460969e20*b[2, 1]*a[1, 2]-0.3464101615e19*b[2, 1]*a[2, 0]+0.7200000000e20*b[2, 2]*a[0, 2]-0.4000000000e19*b[2, 2]*a[1, 0]+0.4356921938e20*b[2, 2]*a[1, 2]-0.6928203230e19*b[2, 2]*a[2, 0]+0.1500000000e28*b[0, 0]^2*b[0, 2]-0.1732050807e28*b[0, 0]^2*b[1, 0]+0.8660254080e27*b[0, 0]^2*b[1, 2]+0.3000000000e19*b[0, 0]^2*b[2, 0]-0.2000000000e19*b[0, 0]^2*b[2, 2]-0.1000000000e28*b[0, 0]^2*a[0, 0]+0.5000000000e27*b[0, 0]^2*a[0, 2]-0.5773502690e27*b[0, 0]^2*a[1, 0]+0.2886751360e27*b[0, 0]^2*a[1, 2]+0.1000000000e19*b[0, 0]^2*a[2, 0]-0.7500000000e27*b[0, 0]*b[0, 2]^2-0.9999999993e27*b[0, 0]*b[1, 0]^2-0.2500000024e27*b[0, 0]*b[1, 2]^2-3000000000.*b[0, 0]*b[2, 0]^2-0.3000000000e19*b[0, 0]^2*b[2, 1]-0.4330127018e27*b[0, 2]^2*b[1, 0]+0.2165063520e27*b[0, 2]^2*b[1, 2]+0.7500000000e18*b[0, 2]^2*b[2, 0]-0.5000000000e18*b[0, 2]^2*b[2, 2]-0.2500000000e27*b[0, 2]^2*a[0, 0]+0.1250000000e27*b[0, 2]^2*a[0, 2]-0.1443375672e27*b[0, 2]^2*a[1, 0]+0.7216878400e26*b[0, 2]^2*a[1, 2]+0.2500000000e18*b[0, 2]^2*a[2, 0]+0.4999999997e27*b[0, 2]*b[1, 0]^2+0.1250000012e27*b[0, 2]*b[1, 2]^2+1500000000.*b[0, 2]*b[2, 0]^2-0.7500000000e18*b[0, 2]^2*b[2, 1]+0.2886751358e27*b[1, 0]^2*b[1, 2]+0.9999999993e18*b[1, 0]^2*b[2, 0]-0.6666666662e18*b[1, 0]^2*b[2, 2]-0.3333333331e27*b[1, 0]^2*a[0, 0]+0.1666666666e27*b[1, 0]^2*a[0, 2]-0.1924500895e27*b[1, 0]^2*a[1, 0]+0.9622504527e26*b[1, 0]^2*a[1, 2]+0.3333333331e18*b[1, 0]^2*a[2, 0]-0.1443375687e27*b[1, 0]*b[1, 2]^2-1732050807.*b[1, 0]*b[2, 0]^2-0.9999999993e18*b[1, 0]^2*b[2, 1]+0.2500000024e18*b[1, 2]^2*b[2, 0]-0.1666666683e18*b[1, 2]^2*b[2, 2]-0.8333333414e26*b[1, 2]^2*a[0, 0]+0.4166666707e26*b[1, 2]^2*a[0, 2]-0.4811252289e26*b[1, 2]^2*a[1, 0]+0.2405626157e26*b[1, 2]^2*a[1, 2]+0.8333333414e17*b[1, 2]^2*a[2, 0]+866025408.*b[1, 2]*b[2, 0]^2-0.2500000024e18*b[1, 2]^2*b[2, 1]-2.*b[2, 0]^2*b[2, 2]-1000000000.*b[2, 0]^2*a[0, 0]+500000000.*b[2, 0]^2*a[0, 2]-577350269.*b[2, 0]^2*a[1, 0]+288675136.*b[2, 0]^2*a[1, 2]+b[2, 0]^2*a[2, 0]-3.*b[2, 0]^2*b[2, 1]-3000000000.*b[2, 1]^2*b[0, 0]+1500000000.*b[2, 1]^2*b[0, 2]-1732050807.*b[2, 1]^2*b[1, 0]+866025408.*b[2, 1]^2*b[1, 2]+3.*b[2, 1]^2*b[2, 0]-2.*b[2, 1]^2*b[2, 2]-1000000000.*b[2, 1]^2*a[0, 0]+500000000.*b[2, 1]^2*a[0, 2]-577350269.*b[2, 1]^2*a[1, 0]+288675136.*b[2, 1]^2*a[1, 2]+b[2, 1]^2*a[2, 0]-0.1000000000e28*b[0, 0]^3+0.1250000000e27*b[0, 2]^3-0.1924500895e27*b[1, 0]^3+0.2405626157e26*b[1, 2]^3+b[2, 0]^3+0.1257735026e29*b[1, 0]*a[1, 2]-0.1732050816e19*b[0, 0]*b[1, 2]*b[2, 0]+0.1154700544e19*b[0, 0]*b[1, 2]*b[2, 2]+0.5773502720e27*b[0, 0]*b[1, 2]*a[0, 0]-0.2886751360e27*b[0, 0]*b[1, 2]*a[0, 2]+0.3333333348e27*b[0, 0]*b[1, 2]*a[1, 0]-0.1666666683e27*b[0, 0]*b[1, 2]*a[1, 2]-0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 0]+4000000000.*b[0, 0]*b[2, 0]*b[2, 2]+0.2000000000e19*b[0, 0]*b[2, 0]*a[0, 0]-0.1000000000e19*b[0, 0]*b[2, 0]*a[0, 2]+0.1154700538e19*b[0, 0]*b[2, 0]*a[1, 0]-0.5773502720e18*b[0, 0]*b[2, 0]*a[1, 2]-2000000000.*b[0, 0]*b[2, 0]*a[2, 0]+0.3000000000e19*b[0, 0]*b[2, 1]*b[0, 2]-0.3464101614e19*b[0, 0]*b[2, 1]*b[1, 0]+0.1732050816e19*b[0, 0]*b[2, 1]*b[1, 2]+6000000000.*b[0, 0]*b[2, 1]*b[2, 0]-4000000000.*b[0, 0]*b[2, 1]*b[2, 2]-0.2000000000e19*b[0, 0]*b[2, 1]*a[0, 0]+0.1000000000e19*b[0, 0]*b[2, 1]*a[0, 2]-0.1154700538e19*b[0, 0]*b[2, 1]*a[1, 0]+0.5773502720e18*b[0, 0]*b[2, 1]*a[1, 2]+2000000000.*b[0, 0]*b[2, 1]*a[2, 0]-0.5000000023e27*b[0, 2]*b[1, 0]*b[1, 2]-0.1732050807e19*b[0, 2]*b[1, 0]*b[2, 0]+0.1154700538e19*b[0, 2]*b[1, 0]*b[2, 2]+0.5773502690e27*b[0, 2]*b[1, 0]*a[0, 0]-0.2886751345e27*b[0, 2]*b[1, 0]*a[0, 2]+0.3333333331e27*b[0, 2]*b[1, 0]*a[1, 0]-0.1666666674e27*b[0, 2]*b[1, 0]*a[1, 2]-0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 0]+0.8660254080e18*b[0, 2]*b[1, 2]*b[2, 0]-0.5773502720e18*b[0, 2]*b[1, 2]*b[2, 2]-0.2886751360e27*b[0, 2]*b[1, 2]*a[0, 0]+0.1443375680e27*b[0, 2]*b[1, 2]*a[0, 2]-0.1666666674e27*b[0, 2]*b[1, 2]*a[1, 0]+0.8333333414e26*b[0, 2]*b[1, 2]*a[1, 2]+0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 0]-2000000000.*b[0, 2]*b[2, 0]*b[2, 2]-0.1000000000e19*b[0, 2]*b[2, 0]*a[0, 0]+0.5000000000e18*b[0, 2]*b[2, 0]*a[0, 2]-0.5773502690e18*b[0, 2]*b[2, 0]*a[1, 0]+0.2886751360e18*b[0, 2]*b[2, 0]*a[1, 2]+1000000000.*b[0, 2]*b[2, 0]*a[2, 0]+0.1732050807e19*b[0, 2]*b[2, 1]*b[1, 0]-0.8660254080e18*b[0, 2]*b[2, 1]*b[1, 2]-3000000000.*b[0, 2]*b[2, 1]*b[2, 0]+2000000000.*b[0, 2]*b[2, 1]*b[2, 2]+0.1000000000e19*b[0, 2]*b[2, 1]*a[0, 0]-0.5000000000e18*b[0, 2]*b[2, 1]*a[0, 2]+0.5773502690e18*b[0, 2]*b[2, 1]*a[1, 0]-0.2886751360e18*b[0, 2]*b[2, 1]*a[1, 2]-1000000000.*b[0, 2]*b[2, 1]*a[2, 0]-0.1000000005e19*b[1, 0]*b[1, 2]*b[2, 0]+0.6666666697e18*b[1, 0]*b[1, 2]*b[2, 2]+0.3333333348e27*b[1, 0]*b[1, 2]*a[0, 0]-0.1666666674e27*b[1, 0]*b[1, 2]*a[0, 2]+0.1924500905e27*b[1, 0]*b[1, 2]*a[1, 0]-0.9622504577e26*b[1, 0]*b[1, 2]*a[1, 2]-0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 0]+2309401076.*b[1, 0]*b[2, 0]*b[2, 2]+0.1154700538e19*b[1, 0]*b[2, 0]*a[0, 0]-0.5773502690e18*b[1, 0]*b[2, 0]*a[0, 2]+0.6666666662e18*b[1, 0]*b[2, 0]*a[1, 0]-0.3333333348e18*b[1, 0]*b[2, 0]*a[1, 2]-1154700538.*b[1, 0]*b[2, 0]*a[2, 0]+0.1000000005e19*b[1, 0]*b[2, 1]*b[1, 2]+3464101614.*b[1, 0]*b[2, 1]*b[2, 0]-2309401076.*b[1, 0]*b[2, 1]*b[2, 2]-0.1154700538e19*b[1, 0]*b[2, 1]*a[0, 0]+0.5773502690e18*b[1, 0]*b[2, 1]*a[0, 2]-0.6666666662e18*b[1, 0]*b[2, 1]*a[1, 0]+0.3333333348e18*b[1, 0]*b[2, 1]*a[1, 2]+1154700538.*b[1, 0]*b[2, 1]*a[2, 0]-1154700544.*b[1, 2]*b[2, 0]*b[2, 2]-0.5773502720e18*b[1, 2]*b[2, 0]*a[0, 0]+0.2886751360e18*b[1, 2]*b[2, 0]*a[0, 2]-0.3333333348e18*b[1, 2]*b[2, 0]*a[1, 0]+0.1666666683e18*b[1, 2]*b[2, 0]*a[1, 2]+577350272.*b[1, 2]*b[2, 0]*a[2, 0]-1732050816.*b[1, 2]*b[2, 1]*b[2, 0]+1154700544.*b[1, 2]*b[2, 1]*b[2, 2]+0.5773502720e18*b[1, 2]*b[2, 1]*a[0, 0]-0.2886751360e18*b[1, 2]*b[2, 1]*a[0, 2]+0.3333333348e18*b[1, 2]*b[2, 1]*a[1, 0]-0.1666666683e18*b[1, 2]*b[2, 1]*a[1, 2]-577350272.*b[1, 2]*b[2, 1]*a[2, 0]+4.*b[2, 0]*b[2, 1]*b[2, 2]+2000000000.*b[2, 0]*b[2, 1]*a[0, 0]-1000000000.*b[2, 0]*b[2, 1]*a[0, 2]+1154700538.*b[2, 0]*b[2, 1]*a[1, 0]-577350272.*b[2, 0]*b[2, 1]*a[1, 2]-2.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050853e28*a[2, 2]*b[0, 0]-0.8660254265e27*a[2, 2]*b[0, 2]+0.1000000026e28*a[2, 2]*b[1, 0]-0.5000000155e27*a[2, 2]*b[1, 2]-0.1732050853e19*a[2, 2]*b[2, 0]+0.1732050853e19*a[2, 2]*b[2, 1]+0.3464101700e19*a[2, 2]*b[2, 2]+0.1732050850e28*a[2, 2]*a[0, 0]-0.8660252810e27*a[2, 2]*a[0, 2]+0.1000000016e28*a[2, 2]*a[1, 0]-0.4999999275e27*a[2, 2]*a[1, 2]-0.1558845731e20*a[2, 2]*a[2, 0]+0.3600000000e29*a[0, 2]*a[0, 0]-0.1800000000e29*a[0, 2]^2+0.2178460968e29*a[0, 2]*a[1, 0]-0.2128460974e29*a[0, 2]*a[1, 2]+0.1732050772e28*a[0, 2]*a[2, 0]-0.2000000000e28*a[1, 0]*a[0, 0]-0.1154700538e28*a[1, 0]^2+0.1315470054e29*a[1, 0]*a[1, 2]-0.1999999997e28*a[1, 0]*a[2, 0]+0.2178460969e29*a[1, 2]*a[0, 0]-0.6288675165e28*a[1, 2]^2+0.9999999830e27*a[1, 2]*a[2, 0]-0.3464101615e28*a[2, 0]*a[0, 0]+0.3464101615e19*a[2, 0]^2-0.1000000000e19*b[0, 0]^2*a[2, 1]-0.4000000000e19*b[0, 0]^2*a[2, 2]+0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 1]+0.4000000000e19*b[0, 0]*b[0, 2]*a[2, 2]-0.1154700538e19*b[0, 0]*b[1, 0]*a[2, 1]-0.4618802152e19*b[0, 0]*b[1, 0]*a[2, 2]+0.5773502720e18*b[0, 0]*b[1, 2]*a[2, 1]+0.2309401088e19*b[0, 0]*b[1, 2]*a[2, 2]+2000000000.*b[0, 0]*b[2, 0]*a[2, 1]+8000000000.*b[0, 0]*b[2, 0]*a[2, 2]-2000000000.*b[0, 0]*b[2, 1]*a[2, 1]-8000000000.*b[0, 0]*b[2, 1]*a[2, 2]+0.5773502690e18*b[0, 2]*b[1, 0]*a[2, 1]+0.2309401076e19*b[0, 2]*b[1, 0]*a[2, 2]-0.2886751360e18*b[0, 2]*b[1, 2]*a[2, 1]-0.1154700544e19*b[0, 2]*b[1, 2]*a[2, 2]-1000000000.*b[0, 2]*b[2, 0]*a[2, 1]-4000000000.*b[0, 2]*b[2, 0]*a[2, 2]+1000000000.*b[0, 2]*b[2, 1]*a[2, 1]+4000000000.*b[0, 2]*b[2, 1]*a[2, 2]+0.3333333348e18*b[1, 0]*b[1, 2]*a[2, 1]+0.1333333339e19*b[1, 0]*b[1, 2]*a[2, 2]+1154700538.*b[1, 0]*b[2, 0]*a[2, 1]+4618802152.*b[1, 0]*b[2, 0]*a[2, 2]-1154700538.*b[1, 0]*b[2, 1]*a[2, 1]-4618802152.*b[1, 0]*b[2, 1]*a[2, 2]-577350272.*b[1, 2]*b[2, 0]*a[2, 1]-2309401088.*b[1, 2]*b[2, 0]*a[2, 2]+577350272.*b[1, 2]*b[2, 1]*a[2, 1]+2309401088.*b[1, 2]*b[2, 1]*a[2, 2]+2.*b[2, 0]*b[2, 1]*a[2, 1]+8.*b[2, 0]*b[2, 1]*a[2, 2]-1.*b[2, 1]^3-0.2500000000e18*b[0, 2]^2*a[2, 1]-0.1000000000e19*b[0, 2]^2*a[2, 2]-0.3333333331e18*b[1, 0]^2*a[2, 1]-0.1333333332e19*b[1, 0]^2*a[2, 2]-0.8333333414e17*b[1, 2]^2*a[2, 1]-0.3333333366e18*b[1, 2]^2*a[2, 2]-1.*b[2, 0]^2*a[2, 1]-4.*b[2, 0]^2*a[2, 2]-1.*b[2, 1]^2*a[2, 1]-4.*b[2, 1]^2*a[2, 2]+0.1732050850e19*a[2, 2]*a[2, 1]+0.6928203400e19*a[2, 2]^2+0.3600000000e20*a[0, 2]*a[2, 1]-0.2000000000e19*a[1, 0]*a[2, 1]+0.2178460969e20*a[1, 2]*a[2, 1]-0.3464101615e19*a[2, 0]*a[2, 1]+0.1732050807e28*b[0, 0]*b[0, 2]*b[1, 0]-0.8660254080e27*b[0, 0]*b[0, 2]*b[1, 2]-0.3000000000e19*b[0, 0]*b[0, 2]*b[2, 0]+0.2000000000e19*b[0, 0]*b[0, 2]*b[2, 2]+0.1000000000e28*b[0, 0]*b[0, 2]*a[0, 0]-0.5000000000e27*b[0, 0]*b[0, 2]*a[0, 2]+0.5773502690e27*b[0, 0]*b[0, 2]*a[1, 0]-0.2886751360e27*b[0, 0]*b[0, 2]*a[1, 2]-0.1000000000e19*b[0, 0]*b[0, 2]*a[2, 0]+0.1000000005e28*b[0, 0]*b[1, 0]*b[1, 2]+0.3464101614e19*b[0, 0]*b[1, 0]*b[2, 0]-0.2309401076e19*b[0, 0]*b[1, 0]*b[2, 2]-0.1154700538e28*b[0, 0]*b[1, 0]*a[0, 0]+0.5773502690e27*b[0, 0]*b[1, 0]*a[0, 2]-0.6666666662e27*b[0, 0]*b[1, 0]*a[1, 0])/(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2]) = 0, 0.1000000000e-8*(-0.1910683611e28*b[0, 0]*b[1, 0]*a[1, 2]-0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 0]+0.2000000000e29*b[0, 0]^2-0.3200000000e29*b[0, 0]*b[0, 2]+0.2509401076e29*b[0, 0]*b[1, 0]-0.1947520867e29*b[0, 0]*b[1, 2]+0.3464101575e28*b[0, 0]*b[2, 0]+0.4000000000e20*b[0, 0]*b[2, 1]-0.1732050770e28*b[0, 0]*b[2, 2]+0.1100000000e29*b[0, 2]^2-0.1947520861e29*b[0, 2]*b[1, 0]+0.1320170597e29*b[0, 2]*b[1, 2]-0.1732050776e28*b[0, 2]*b[2, 0]-0.3200000000e20*b[0, 2]*b[2, 1]+0.8660253610e27*b[0, 2]*b[2, 2]+0.7821367200e28*b[1, 0]^2-0.1182136724e29*b[1, 0]*b[1, 2]+0.1999999974e28*b[1, 0]*b[2, 0]+0.2509401076e20*b[1, 0]*b[2, 1]-0.9999999740e27*b[1, 0]*b[2, 2]+0.3955341829e28*b[1, 2]^2-0.9999999854e27*b[1, 2]*b[2, 0]-0.1947520867e20*b[1, 2]*b[2, 1]+0.4999999757e27*b[1, 2]*b[2, 2]-0.3464101595e19*b[2, 0]^2+0.3464101575e19*b[2, 0]*b[2, 1]+0.8660254000e19*b[2, 0]*b[2, 2]+0.2000000000e11*b[2, 1]^2-0.1732050770e19*b[2, 1]*b[2, 2]-0.3464101620e19*b[2, 2]^2+0.1600000000e29*b[0, 0]*a[0, 0]-0.8000000000e28*b[0, 0]*a[0, 2]+0.9237604304e28*b[0, 0]*a[1, 0]-0.4618802176e28*b[0, 0]*a[1, 2]-0.1600000000e20*b[0, 0]*a[2, 0]-0.2000000000e29*b[0, 2]*a[0, 0]+0.1000000000e29*b[0, 2]*a[0, 2]-0.1154700538e29*b[0, 2]*a[1, 0]+0.5773502720e28*b[0, 2]*a[1, 2]+0.2000000000e20*b[0, 2]*a[2, 0]+0.1123760430e29*b[1, 0]*a[0, 0]-0.5618802152e28*b[1, 0]*a[0, 2]+0.6488033868e28*b[1, 0]*a[1, 0]-0.1123760430e20*b[1, 0]*a[2, 0]-0.1254700541e29*b[1, 2]*a[0, 0]+0.6273502703e28*b[1, 2]*a[0, 2]-0.7244016946e28*b[1, 2]*a[1, 0]+0.3622008492e28*b[1, 2]*a[1, 2]+0.1254700541e20*b[1, 2]*a[2, 0]+0.3464101599e28*b[2, 0]*a[0, 0]-0.1732050800e28*b[2, 0]*a[0, 2]+0.1999999990e28*b[2, 0]*a[1, 0]-0.1000000000e28*b[2, 0]*a[1, 2]-0.3464101599e19*b[2, 0]*a[2, 0]+0.1600000000e20*b[2, 1]*a[0, 0]-0.8000000000e19*b[2, 1]*a[0, 2]+0.9237604304e19*b[2, 1]*a[1, 0]-0.4618802176e19*b[2, 1]*a[1, 2]-0.1600000000e11*b[2, 1]*a[2, 0]-0.1732050810e28*b[2, 2]*a[0, 0]+0.8660254050e27*b[2, 2]*a[0, 2]-0.1000000001e28*b[2, 2]*a[1, 0]+0.5000000031e27*b[2, 2]*a[1, 2]+0.1732050810e19*b[2, 2]*a[2, 0]-0.2400000000e29*b[0, 0]^2*b[0, 2]+0.1585640646e29*b[0, 0]^2*b[1, 0]-0.1485640651e29*b[0, 0]^2*b[1, 2]+0.3464101599e28*b[0, 0]^2*b[2, 0]-0.1732050754e28*b[0, 0]^2*b[2, 2]+0.4000000000e28*b[0, 0]^2*a[0, 0]-0.2000000000e28*b[0, 0]^2*a[0, 2]+0.2309401076e28*b[0, 0]^2*a[1, 0]-0.1154700544e28*b[0, 0]^2*a[1, 2]-0.4000000000e19*b[0, 0]^2*a[2, 0]+0.1800000000e29*b[0, 0]*b[0, 2]^2+0.1030940107e29*b[0, 0]*b[1, 0]^2+0.6577350318e28*b[0, 0]*b[1, 2]^2-0.6928203222e19*b[0, 0]*b[2, 0]^2+0.2000000000e20*b[0, 0]^2*b[2, 1]-0.3464101540e19*b[0, 0]*b[2, 2]^2+0.1089230484e29*b[0, 2]^2*b[1, 0]-0.7178203258e28*b[0, 2]^2*b[1, 2]+0.8660253878e27*b[0, 2]^2*b[2, 0]-0.4330126765e27*b[0, 2]^2*b[2, 2]+0.7000000000e28*b[0, 2]^2*a[0, 0]-0.3500000000e28*b[0, 2]^2*a[0, 2]+0.4041451883e28*b[0, 2]^2*a[1, 0]-0.2020725952e28*b[0, 2]^2*a[1, 2]-0.7000000000e19*b[0, 2]^2*a[2, 0]-0.9154700533e28*b[0, 2]*b[1, 0]^2-0.4288675169e28*b[0, 2]*b[1, 2]^2+0.3464101599e19*b[0, 2]*b[2, 0]^2+0.1700000000e20*b[0, 2]^2*b[2, 1]+0.1732050770e19*b[0, 2]*b[2, 2]^2-0.5618802168e28*b[1, 0]^2*b[1, 2]+0.1154700530e28*b[1, 0]^2*b[2, 0]-0.5773502486e27*b[1, 0]^2*b[2, 2]+0.2488033870e28*b[1, 0]^2*a[0, 0]-0.1244016935e28*b[1, 0]^2*a[0, 2]+0.1436467024e28*b[1, 0]^2*a[1, 0]-0.7182335159e27*b[1, 0]^2*a[1, 2]-0.2488033870e19*b[1, 0]^2*a[2, 0]+0.3964101644e28*b[1, 0]*b[1, 2]^2-0.3999999992e19*b[1, 0]*b[2, 0]^2+0.8976067738e19*b[1, 0]^2*b[2, 1]-0.1999999956e19*b[1, 0]*b[2, 2]^2+0.2886751315e27*b[1, 2]^2*b[2, 0]-0.1443375597e27*b[1, 2]^2*b[2, 2]+0.2622008486e28*b[1, 2]^2*a[0, 0]-0.1311004243e28*b[1, 2]^2*a[0, 2]+0.1513817305e28*b[1, 2]^2*a[1, 0]-0.7569086562e27*b[1, 2]^2*a[1, 2]-0.2622008486e19*b[1, 2]^2*a[2, 0]+0.1999999999e19*b[1, 2]*b[2, 0]^2+0.6244016981e19*b[1, 2]^2*b[2, 1]+0.9999999832e18*b[1, 2]*b[2, 2]^2-8660254000.*b[2, 0]^2*b[2, 2]-0.3464101619e19*b[2, 0]^2*a[0, 0]+0.1732050810e19*b[2, 0]^2*a[0, 2]-0.2000000002e19*b[2, 0]^2*a[1, 0]+0.1000000006e19*b[2, 0]^2*a[1, 2]+3464101619.*b[2, 0]^2*a[2, 0]-6928203226.*b[2, 0]^2*b[2, 1]+3464101540.*b[2, 0]*b[2, 2]^2+0.1600000000e11*b[2, 1]^2*b[0, 0]-0.2000000000e11*b[2, 1]^2*b[0, 2]+0.1123760430e11*b[2, 1]^2*b[1, 0]-0.1254700542e11*b[2, 1]^2*b[1, 2]+3464101607.*b[2, 1]^2*b[2, 0]-1732050762.*b[2, 1]^2*b[2, 2]-3464101540.*b[2, 1]*b[2, 2]^2+0.8000000000e28*b[0, 0]^3-0.4000000000e28*b[0, 2]^3+0.2206267383e28*b[1, 0]^3-0.8531337025e27*b[1, 2]^3+3464101615.*b[2, 0]^3-0.3244016951e28*b[1, 0]*a[1, 2]-0.1999999985e28*b[0, 0]*b[1, 2]*b[2, 0]+0.9999999581e27*b[0, 0]*b[1, 2]*b[2, 2]-0.1023760433e29*b[0, 0]*b[1, 2]*a[0, 0]+0.5118802165e28*b[0, 0]*b[1, 2]*a[0, 2]-0.5910683614e28*b[0, 0]*b[1, 2]*a[1, 0]+0.2955341822e28*b[0, 0]*b[1, 2]*a[1, 2]+0.1023760433e20*b[0, 0]*b[1, 2]*a[2, 0]+0.1039230475e20*b[0, 0]*b[2, 0]*b[2, 2]+0.3464101615e28*b[0, 0]*b[2, 0]*a[0, 0]-0.1732050808e28*b[0, 0]*b[2, 0]*a[0, 2]+0.1999999999e28*b[0, 0]*b[2, 0]*a[1, 0]-0.1000000005e28*b[0, 0]*b[2, 0]*a[1, 2]-0.3464101615e19*b[0, 0]*b[2, 0]*a[2, 0]-0.4400000000e20*b[0, 0]*b[2, 1]*b[0, 2]+0.2709401076e20*b[0, 0]*b[2, 1]*b[1, 0]-0.2740341192e20*b[0, 0]*b[2, 1]*b[1, 2]+0.6928203206e19*b[0, 0]*b[2, 1]*b[2, 0]-0.3464101516e19*b[0, 0]*b[2, 1]*b[2, 2]+0.4000000000e19*b[0, 0]*b[2, 1]*a[0, 0]-0.2000000000e19*b[0, 0]*b[2, 1]*a[0, 2]+0.2309401076e19*b[0, 0]*b[2, 1]*a[1, 0]-0.1154700544e19*b[0, 0]*b[2, 1]*a[1, 2]-4000000000.*b[0, 0]*b[2, 1]*a[2, 0]-0.1732050770e28*b[0, 0]*b[2, 2]*a[0, 0]+0.8660253850e27*b[0, 0]*b[2, 2]*a[0, 2]-0.9999999780e27*b[0, 0]*b[2, 2]*a[1, 0]+0.4999999916e27*b[0, 0]*b[2, 2]*a[1, 2]+0.1732050770e19*b[0, 0]*b[2, 2]*a[2, 0]+0.1315470058e29*b[0, 2]*b[1, 0]*b[1, 2]-0.1999999974e28*b[0, 2]*b[1, 0]*b[2, 0]+0.9999999529e27*b[0, 2]*b[1, 0]*b[2, 2]-0.1023760430e29*b[0, 2]*b[1, 0]*a[0, 0]+0.5118802152e28*b[0, 2]*b[1, 0]*a[0, 2]-0.5910683599e28*b[0, 2]*b[1, 0]*a[1, 0]+0.2955341815e28*b[0, 2]*b[1, 0]*a[1, 2]+0.1023760430e20*b[0, 2]*b[1, 0]*a[2, 0]+0.9999999854e27*b[0, 2]*b[1, 2]*b[2, 0]-0.4999999721e27*b[0, 2]*b[1, 2]*b[2, 2]+0.8582903797e28*b[0, 2]*b[1, 2]*a[0, 0]-0.4291451898e28*b[0, 2]*b[1, 2]*a[0, 2]+0.4955341816e28*b[0, 2]*b[1, 2]*a[1, 0]-0.2477670921e28*b[0, 2]*b[1, 2]*a[1, 2]-0.8582903797e19*b[0, 2]*b[1, 2]*a[2, 0]-0.5196152353e19*b[0, 2]*b[2, 0]*b[2, 2]-0.1732050796e28*b[0, 2]*b[2, 0]*a[0, 0]+0.8660253978e27*b[0, 2]*b[2, 0]*a[0, 2]-0.9999999927e27*b[0, 2]*b[2, 0]*a[1, 0]+0.4999999989e27*b[0, 2]*b[2, 0]*a[1, 2]+0.1732050796e19*b[0, 2]*b[2, 0]*a[2, 0]-0.2740341184e20*b[0, 2]*b[2, 1]*b[1, 0]+0.2062990923e20*b[0, 2]*b[2, 1]*b[1, 2]-0.3464101579e19*b[0, 2]*b[2, 1]*b[2, 0]+0.1732050734e19*b[0, 2]*b[2, 1]*b[2, 2]-0.1400000000e20*b[0, 2]*b[2, 1]*a[0, 0]+0.7000000000e19*b[0, 2]*b[2, 1]*a[0, 2]-0.8082903766e19*b[0, 2]*b[2, 1]*a[1, 0]+0.4041451904e19*b[0, 2]*b[2, 1]*a[1, 2]+0.1400000000e11*b[0, 2]*b[2, 1]*a[2, 0]+0.8660253850e27*b[0, 2]*b[2, 2]*a[0, 0]-0.4330126925e27*b[0, 2]*b[2, 2]*a[0, 2]+0.4999999890e27*b[0, 2]*b[2, 2]*a[1, 0]-0.2499999958e27*b[0, 2]*b[2, 2]*a[1, 2]-0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 0]-0.1154700528e28*b[1, 0]*b[1, 2]*b[2, 0]+0.5773502436e27*b[1, 0]*b[1, 2]*b[2, 2]-0.6488033886e28*b[1, 0]*b[1, 2]*a[0, 0]+0.3244016943e28*b[1, 0]*b[1, 2]*a[0, 2]-0.3745868109e28*b[1, 0]*b[1, 2]*a[1, 0]+0.1872934064e28*b[1, 0]*b[1, 2]*a[1, 2]+0.6488033886e19*b[1, 0]*b[1, 2]*a[2, 0]+0.5999999941e19*b[1, 0]*b[2, 0]*b[2, 2]+0.1999999997e28*b[1, 0]*b[2, 0]*a[0, 0]-0.9999999986e27*b[1, 0]*b[2, 0]*a[0, 2]+0.1154700536e28*b[1, 0]*b[2, 0]*a[1, 0]-0.5773502712e27*b[1, 0]*b[2, 0]*a[1, 2]-0.1999999997e19*b[1, 0]*b[2, 0]*a[2, 0]-0.1697606779e20*b[1, 0]*b[2, 1]*b[1, 2]+0.3999999981e19*b[1, 0]*b[2, 1]*b[2, 0]-0.1999999938e19*b[1, 0]*b[2, 1]*b[2, 2]+0.4309401076e19*b[1, 0]*b[2, 1]*a[0, 0]-0.2154700538e19*b[1, 0]*b[2, 1]*a[0, 2]+0.2488033870e19*b[1, 0]*b[2, 1]*a[1, 0]-0.1244016942e19*b[1, 0]*b[2, 1]*a[1, 2]-4309401076.*b[1, 0]*b[2, 1]*a[2, 0]-0.9999999780e27*b[1, 0]*b[2, 2]*a[0, 0]+0.4999999890e27*b[1, 0]*b[2, 2]*a[0, 2]-0.5773502563e27*b[1, 0]*b[2, 2]*a[1, 0]+0.2886751296e27*b[1, 0]*b[2, 2]*a[1, 2]+0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 0]-0.2999999972e19*b[1, 2]*b[2, 0]*b[2, 2]-0.9999999969e27*b[1, 2]*b[2, 0]*a[0, 0]+0.4999999984e27*b[1, 2]*b[2, 0]*a[0, 2]-0.5773502672e27*b[1, 2]*b[2, 0]*a[1, 0]+0.2886751351e27*b[1, 2]*b[2, 0]*a[1, 2]+0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 0]-0.1999999987e19*b[1, 2]*b[2, 1]*b[2, 0]+0.9999999604e18*b[1, 2]*b[2, 1]*b[2, 2]-0.9082903786e19*b[1, 2]*b[2, 1]*a[0, 0]+0.4541451893e19*b[1, 2]*b[2, 1]*a[0, 2]-0.5244016944e19*b[1, 2]*b[2, 1]*a[1, 0]+0.2622008486e19*b[1, 2]*b[2, 1]*a[1, 2]+9082903786.*b[1, 2]*b[2, 1]*a[2, 0]+0.4999999916e27*b[1, 2]*b[2, 2]*a[0, 0]-0.2499999958e27*b[1, 2]*b[2, 2]*a[0, 2]+0.2886751296e27*b[1, 2]*b[2, 2]*a[1, 0]-0.1443375656e27*b[1, 2]*b[2, 2]*a[1, 2]-0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 0]+0.1039230476e11*b[2, 0]*b[2, 1]*b[2, 2]+0.3464101619e19*b[2, 0]*b[2, 1]*a[0, 0]-0.1732050810e19*b[2, 0]*b[2, 1]*a[0, 2]+0.2000000002e19*b[2, 0]*b[2, 1]*a[1, 0]-0.1000000006e19*b[2, 0]*b[2, 1]*a[1, 2]-3464101619.*b[2, 0]*b[2, 1]*a[2, 0]+0.1732050770e19*b[2, 0]*b[2, 2]*a[0, 0]-0.8660253850e18*b[2, 0]*b[2, 2]*a[0, 2]+0.9999999780e18*b[2, 0]*b[2, 2]*a[1, 0]-0.4999999916e18*b[2, 0]*b[2, 2]*a[1, 2]-1732050770.*b[2, 0]*b[2, 2]*a[2, 0]-0.1732050770e19*b[2, 1]*b[2, 2]*a[0, 0]+0.8660253850e18*b[2, 1]*b[2, 2]*a[0, 2]-0.9999999780e18*b[2, 1]*b[2, 2]*a[1, 0]+0.4999999916e18*b[2, 1]*b[2, 2]*a[1, 2]+1732050770.*b[2, 1]*b[2, 2]*a[2, 0]+0.7600000000e20*a[2, 2]*b[0, 0]-0.8600000000e20*a[2, 2]*b[0, 2]+0.5187862044e20*a[2, 2]*b[1, 0]-0.5365212326e20*a[2, 2]*b[1, 2]+0.1385640638e20*a[2, 2]*b[2, 0]+0.7600000000e11*a[2, 2]*b[2, 1]-0.6928203240e19*a[2, 2]*b[2, 2]+0.1600000000e20*b[0, 0]*a[2, 1]-0.2000000000e20*b[0, 2]*a[2, 1]+0.1123760430e20*b[1, 0]*a[2, 1]-0.1254700541e20*b[1, 2]*a[2, 1]+0.3464101599e19*b[2, 0]*a[2, 1]+0.1600000000e11*b[2, 1]*a[2, 1]+0.4000000000e19*b[0, 0]^2*a[2, 1]+0.2800000000e20*b[0, 0]^2*a[2, 2]-0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 1]-0.7600000000e20*b[0, 0]*b[0, 2]*a[2, 2]+0.6618802152e19*b[0, 0]*b[1, 0]*a[2, 1]+0.4033161506e20*b[0, 0]*b[1, 0]*a[2, 2]-0.1023760433e20*b[0, 0]*b[1, 2]*a[2, 1]-0.4787862058e20*b[0, 0]*b[1, 2]*a[2, 2]+0.3464101615e19*b[0, 0]*b[2, 0]*a[2, 1]+0.1385640644e20*b[0, 0]*b[2, 0]*a[2, 2]+4000000000.*b[0, 0]*b[2, 1]*a[2, 1]+0.4000000000e11*b[0, 0]*b[2, 1]*a[2, 2]-0.1023760430e20*b[0, 2]*b[1, 0]*a[2, 1]-0.4787862044e20*b[0, 2]*b[1, 0]*a[2, 2]+0.8582903797e19*b[0, 2]*b[1, 2]*a[2, 1]+0.3779571682e20*b[0, 2]*b[1, 2]*a[2, 2]-0.1732050796e19*b[0, 2]*b[2, 0]*a[2, 1]-0.6928203170e19*b[0, 2]*b[2, 0]*a[2, 2]-0.1400000000e11*b[0, 2]*b[2, 1]*a[2, 1]-0.6800000000e11*b[0, 2]*b[2, 1]*a[2, 2]-0.6488033886e19*b[1, 0]*b[1, 2]*a[2, 1]-0.2995213556e20*b[1, 0]*b[1, 2]*a[2, 2]+0.1999999997e19*b[1, 0]*b[2, 0]*a[2, 1]+0.7999999975e19*b[1, 0]*b[2, 0]*a[2, 2]+4309401076.*b[1, 0]*b[2, 1]*a[2, 1]+0.3109401076e11*b[1, 0]*b[2, 1]*a[2, 2]-0.9999999969e18*b[1, 2]*b[2, 0]*a[2, 1]-0.3999999981e19*b[1, 2]*b[2, 0]*a[2, 2]-9082903786.*b[1, 2]*b[2, 1]*a[2, 1]-0.4325981841e11*b[1, 2]*b[2, 1]*a[2, 2]+3464101619.*b[2, 0]*b[2, 1]*a[2, 1]+0.1385640645e11*b[2, 0]*b[2, 1]*a[2, 2]+4.*b[2, 1]^3+0.7000000000e19*b[0, 2]^2*a[2, 1]+0.3100000000e20*b[0, 2]^2*a[2, 2]+0.2488033870e19*b[1, 0]^2*a[2, 1]+0.1395213548e20*b[1, 0]^2*a[2, 2]+0.2622008486e19*b[1, 2]^2*a[2, 1]+0.1148803395e20*b[1, 2]^2*a[2, 2]-3464101619.*b[2, 0]^2*a[2, 1]-0.1385640646e11*b[2, 0]^2*a[2, 2]+12.*b[2, 1]^2*a[2, 2]-0.6928203080e19*b[0, 0]*a[2, 2]*b[2, 2]+0.3464101540e19*b[0, 2]*a[2, 2]*b[2, 2]-0.3999999912e19*b[1, 0]*a[2, 2]*b[2, 2]+0.1999999966e19*b[1, 2]*a[2, 2]*b[2, 2]+6928203080.*b[2, 0]*a[2, 2]*b[2, 2]-6928203080.*b[2, 1]*a[2, 2]*b[2, 2]-0.1732050810e19*b[2, 2]*a[2, 1]-0.9999999780e18*b[1, 0]*b[2, 2]*a[2, 1]+0.4999999916e18*b[1, 2]*b[2, 2]*a[2, 1]-0.1732050770e19*b[0, 0]*b[2, 2]*a[2, 1]+0.8660253850e18*b[0, 2]*b[2, 2]*a[2, 1]+1732050770.*b[2, 0]*b[2, 2]*a[2, 1]-1732050770.*b[2, 1]*b[2, 2]*a[2, 1]-0.2971281291e29*b[0, 0]*b[0, 2]*b[1, 0]+0.2178460977e29*b[0, 0]*b[0, 2]*b[1, 2]-0.3464101575e28*b[0, 0]*b[0, 2]*b[2, 0]+0.1732050730e28*b[0, 0]*b[0, 2]*b[2, 2]-0.1600000000e29*b[0, 0]*b[0, 2]*a[0, 0]+0.8000000000e28*b[0, 0]*b[0, 2]*a[0, 2]-0.9237604304e28*b[0, 0]*b[0, 2]*a[1, 0]+0.4618802176e28*b[0, 0]*b[0, 2]*a[1, 2]+0.1600000000e20*b[0, 0]*b[0, 2]*a[2, 0]-0.1830940113e29*b[0, 0]*b[1, 0]*b[1, 2]+0.3999999976e28*b[0, 0]*b[1, 0]*b[2, 0]-0.1999999933e28*b[0, 0]*b[1, 0]*b[2, 2]+0.6618802152e28*b[0, 0]*b[1, 0]*a[0, 0]-0.3309401076e28*b[0, 0]*b[1, 0]*a[0, 2]+0.3821367203e28*b[0, 0]*b[1, 0]*a[1, 0])/((1000000000.+1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1])*(1000000000.*b[0, 0]-500000000.*b[0, 2]+577350269.*b[1, 0]-288675136.*b[1, 2]-1.*b[2, 0]+b[2, 1]+2.*b[2, 2]+1000000000.*a[0, 0]-500000000.*a[0, 2]+577350269.*a[1, 0]-288675136.*a[1, 2]-1.*a[2, 0]+a[2, 1]+4.*a[2, 2])) = 0, 0.2000000000e-9*(-0.1889957658e30*b[0, 0]*b[1, 0]*a[1, 2]-0.7237604306e21*b[0, 0]*b[1, 0]*a[2, 0]+0.5000000000e31*b[0, 0]^2-0.8000000000e31*b[0, 0]*b[0, 2]-0.5273502692e31*b[0, 0]*b[1, 0]+0.4368802158e31*b[0, 0]*b[1, 2]-0.8660253998e30*b[0, 0]*b[2, 0]+0.2000000000e22*b[0, 0]*b[2, 1]+0.4330126925e30*b[0, 0]*b[2, 2]+0.2750000000e31*b[0, 2]^2+0.4368802154e31*b[0, 2]*b[1, 0]-0.3050426484e31*b[0, 2]*b[1, 2]+0.4330126987e30*b[0, 2]*b[2, 0]-0.1000000000e22*b[0, 2]*b[2, 1]-0.2165063448e30*b[0, 2]*b[2, 2]+0.1377991532e31*b[1, 0]^2-0.2377991534e31*b[1, 0]*b[1, 2]+0.4999999979e30*b[1, 0]*b[2, 0]-0.1154700538e22*b[1, 0]*b[2, 1]-0.2499999948e30*b[1, 0]*b[2, 2]+0.8444978848e30*b[1, 2]^2-0.2499999986e30*b[1, 2]*b[2, 0]+0.5773502700e21*b[1, 2]*b[2, 1]+0.1249999967e30*b[1, 2]*b[2, 2]-0.3464101607e21*b[2, 0]^2+0.8000000000e12*b[2, 0]*b[2, 1]+0.6062177789e21*b[2, 0]*b[2, 2]-0.1000000000e13*b[2, 1]*b[2, 2]-0.2165063475e21*b[2, 2]^2+0.4000000000e31*b[0, 0]*a[0, 0]-0.2000000000e31*b[0, 0]*a[0, 2]-0.2309401077e31*b[0, 0]*a[1, 0]+0.1154700539e31*b[0, 0]*a[1, 2]+0.2000000000e22*b[0, 0]*a[2, 0]-0.5000000000e31*b[0, 2]*a[0, 0]+0.2500000000e31*b[0, 2]*a[0, 2]+0.2886751346e31*b[0, 2]*a[1, 0]-0.1443375674e31*b[0, 2]*a[1, 2]-0.2200000000e22*b[0, 2]*a[2, 0]-0.1809401077e31*b[1, 0]*a[0, 0]+0.9047005384e30*b[1, 0]*a[0, 2]+0.1044658199e31*b[1, 0]*a[1, 0]-0.9547005384e21*b[1, 0]*a[2, 0]+0.2636751348e31*b[1, 2]*a[0, 0]-0.1318375674e31*b[1, 2]*a[0, 2]-0.1522329100e31*b[1, 2]*a[1, 0]+0.7611645506e30*b[1, 2]*a[1, 2]+0.1170170593e22*b[1, 2]*a[2, 0]-0.8660254022e30*b[2, 0]*a[0, 0]+0.4330127011e30*b[2, 0]*a[0, 2]+0.4999999991e30*b[2, 0]*a[1, 0]-0.2499999997e30*b[2, 0]*a[1, 2]-0.3464101607e21*b[2, 0]*a[2, 0]+0.1600000000e22*b[2, 1]*a[0, 0]-0.8000000000e21*b[2, 1]*a[0, 2]-0.9237604307e21*b[2, 1]*a[1, 0]+0.4618802156e21*b[2, 1]*a[1, 2]+0.8000000000e12*b[2, 1]*a[2, 0]+0.4330126960e30*b[2, 2]*a[0, 0]-0.2165063480e30*b[2, 2]*a[0, 2]-0.2499999966e30*b[2, 2]*a[1, 0]+0.1249999984e30*b[2, 2]*a[1, 2]+0.1732050780e21*b[2, 2]*a[2, 0]-0.6000000000e31*b[0, 0]^2*b[0, 2]-0.2964101615e31*b[0, 0]^2*b[1, 0]+0.3214101616e31*b[0, 0]^2*b[1, 2]-0.8660254022e30*b[0, 0]^2*b[2, 0]+0.4330126960e30*b[0, 0]^2*b[2, 2]+0.1000000000e31*b[0, 0]^2*a[0, 0]-0.5000000000e30*b[0, 0]^2*a[0, 2]-0.5773502692e30*b[0, 0]^2*a[1, 0]+0.2886751346e30*b[0, 0]^2*a[1, 2]+0.8000000000e21*b[0, 0]^2*a[2, 0]+0.4500000000e31*b[0, 0]*b[0, 2]^2+0.1422649730e31*b[0, 0]*b[1, 0]^2+0.1355662435e31*b[0, 0]*b[1, 2]^2-0.6928203228e21*b[0, 0]*b[2, 0]^2+0.7000000000e21*b[0, 0]^2*b[2, 1]-0.6495190475e21*b[0, 0]*b[2, 2]^2-0.2473076211e31*b[0, 2]^2*b[1, 0]+0.1669550809e31*b[0, 2]^2*b[1, 2]-0.2165063494e30*b[0, 2]^2*b[2, 0]+0.1082531718e30*b[0, 2]^2*b[2, 2]+0.1750000000e31*b[0, 2]^2*a[0, 0]-0.8750000000e30*b[0, 2]^2*a[0, 2]-0.1010362971e31*b[0, 2]^2*a[1, 0]+0.5051814858e30*b[0, 2]^2*a[1, 2]+0.8000000000e21*b[0, 2]^2*a[2, 0]-0.1711324865e31*b[0, 2]*b[1, 0]^2-0.9278312180e30*b[0, 2]*b[1, 2]^2+0.3464101609e21*b[0, 2]*b[2, 0]^2+0.7750000000e21*b[0, 2]^2*b[2, 1]+0.3247595222e21*b[0, 2]*b[2, 2]^2+0.9047005385e30*b[1, 0]^2*b[1, 2]-0.2886751343e30*b[1, 0]^2*b[2, 0]+0.1443375658e30*b[1, 0]^2*b[2, 2]+0.4465819851e29*b[1, 0]^2*a[0, 0]-0.2232909926e29*b[1, 0]^2*a[0, 2]-0.2578342293e29*b[1, 0]^2*a[1, 0]+0.1289171141e29*b[1, 0]^2*a[1, 2]+0.1511966127e21*b[1, 0]^2*a[2, 0]-0.7410254048e30*b[1, 0]*b[1, 2]^2+0.3999999999e21*b[1, 0]*b[2, 0]^2+0.1178632794e21*b[1, 0]^2*b[2, 1]+0.3749999972e21*b[1, 0]*b[2, 2]^2-0.7216878338e29*b[1, 2]^2*b[2, 0]+0.3608439079e29*b[1, 2]^2*b[2, 2]+0.5111645502e30*b[1, 2]^2*a[0, 0]-0.2555822751e30*b[1, 2]^2*a[0, 2]-0.2951209907e30*b[1, 2]^2*a[1, 0]+0.1475604954e30*b[1, 2]^2*a[1, 2]+0.2377991535e21*b[1, 2]^2*a[2, 0]-0.2000000000e21*b[1, 2]*b[2, 0]^2+0.2294658202e21*b[1, 2]^2*b[2, 1]-0.1874999980e21*b[1, 2]*b[2, 2]^2+0.5888972742e12*b[2, 0]^2*b[2, 2]-0.3464101617e21*b[2, 0]^2*a[0, 0]+0.1732050808e21*b[2, 0]^2*a[0, 2]+0.2000000001e21*b[2, 0]^2*a[1, 0]-0.1000000001e21*b[2, 0]^2*a[1, 2]-0.1385640646e12*b[2, 0]^2*a[2, 0]-0.1385640646e12*b[2, 0]^2*b[2, 1]-0.6928203213e12*b[2, 0]*b[2, 2]^2-0.4000000000e11*b[2, 1]^2*b[0, 0]+0.2000000000e11*b[2, 1]^2*b[0, 2]+0.2309401077e11*b[2, 1]^2*b[1, 0]-0.1154700540e11*b[2, 1]^2*b[1, 2]-16.*b[2, 1]^2*b[2, 0]+20.*b[2, 1]^2*b[2, 2]-0.2000000000e12*b[2, 1]^2*a[0, 0]+0.1000000000e12*b[2, 1]^2*a[0, 2]+0.1154700538e12*b[2, 1]^2*a[1, 0]-0.5773502699e11*b[2, 1]^2*a[1, 2]-16.*b[2, 1]^2*a[2, 0]-0.8660253985e11*b[2, 1]*b[2, 2]^2+0.2000000000e31*b[0, 0]^3-0.1000000000e31*b[0, 2]^3-0.2182335127e30*b[1, 0]^3+0.1716167569e30*b[1, 2]^3-0.1385640646e12*b[2, 0]^3+0.2165063495e12*b[2, 2]^3-0.5223290996e30*b[1, 0]*a[1, 2]-0.4999999986e30*b[0, 0]*b[1, 2]*b[2, 0]+0.2499999947e30*b[0, 0]*b[1, 2]*b[2, 2]+0.2059401076e31*b[0, 0]*b[1, 2]*a[0, 0]-0.1029700538e31*b[0, 0]*b[1, 2]*a[0, 2]-0.1188995766e31*b[0, 0]*b[1, 2]*a[1, 0]+0.5944978833e30*b[0, 0]*b[1, 2]*a[1, 2]+0.1054700539e22*b[0, 0]*b[1, 2]*a[2, 0]+0.1645448264e22*b[0, 0]*b[2, 0]*b[2, 2]-0.8660254038e30*b[0, 0]*b[2, 0]*a[0, 0]+0.4330127019e30*b[0, 0]*b[2, 0]*a[0, 2]+0.5000000000e30*b[0, 0]*b[2, 0]*a[1, 0]-0.2500000002e30*b[0, 0]*b[2, 0]*a[1, 2]-0.3464101612e21*b[0, 0]*b[2, 0]*a[2, 0]-0.1900000000e22*b[0, 0]*b[2, 1]*b[0, 2]-0.6082903767e21*b[0, 0]*b[2, 1]*b[1, 0]+0.9969655116e21*b[0, 0]*b[2, 1]*b[1, 2]-0.3464101613e21*b[0, 0]*b[2, 1]*b[2, 0]+0.1732050794e21*b[0, 0]*b[2, 1]*b[2, 2]-0.1000000000e21*b[0, 0]*b[2, 1]*a[0, 0]+0.5000000000e20*b[0, 0]*b[2, 1]*a[0, 2]+0.5773502692e20*b[0, 0]*b[2, 1]*a[1, 0]-0.2886751364e20*b[0, 0]*b[2, 1]*a[1, 2]+0.2800000000e12*b[0, 0]*b[2, 1]*a[2, 0]+0.4330126990e30*b[0, 0]*b[2, 2]*a[0, 0]-0.2165063495e30*b[0, 0]*b[2, 2]*a[0, 2]-0.2499999983e30*b[0, 0]*b[2, 2]*a[1, 0]+0.1249999993e30*b[0, 0]*b[2, 2]*a[1, 2]+0.1732050788e21*b[0, 0]*b[2, 2]*a[2, 0]+0.2711324867e31*b[0, 2]*b[1, 0]*b[1, 2]-0.4999999979e30*b[0, 2]*b[1, 0]*b[2, 0]+0.2499999944e30*b[0, 2]*b[1, 0]*b[2, 2]+0.2059401077e31*b[0, 2]*b[1, 0]*a[0, 0]-0.1029700538e31*b[0, 2]*b[1, 0]*a[0, 2]-0.1188995766e31*b[0, 2]*b[1, 0]*a[1, 0]+0.5944978833e30*b[0, 2]*b[1, 0]*a[1, 2]+0.1054700538e22*b[0, 2]*b[1, 0]*a[2, 0]+0.2499999986e30*b[0, 2]*b[1, 2]*b[2, 0]-0.1249999961e30*b[0, 2]*b[1, 2]*b[2, 2]-0.1895725943e31*b[0, 2]*b[1, 2]*a[0, 0]+0.9478629716e30*b[0, 2]*b[1, 2]*a[0, 2]+0.1094497884e31*b[0, 2]*b[1, 2]*a[1, 0]-0.5472489422e30*b[0, 2]*b[1, 2]*a[1, 2]-0.8737604313e21*b[0, 2]*b[1, 2]*a[2, 0]-0.8227241301e21*b[0, 2]*b[2, 0]*b[2, 2]+0.4330127007e30*b[0, 2]*b[2, 0]*a[0, 0]-0.2165063504e30*b[0, 2]*b[2, 0]*a[0, 2]-0.2499999993e30*b[0, 2]*b[2, 0]*a[1, 0]+0.1249999998e30*b[0, 2]*b[2, 0]*a[1, 2]+0.1732050801e21*b[0, 2]*b[2, 0]*a[2, 0]+0.9969655114e21*b[0, 2]*b[2, 1]*b[1, 0]-0.8448929178e21*b[0, 2]*b[2, 1]*b[1, 2]+0.1732050802e21*b[0, 2]*b[2, 1]*b[2, 0]-0.8660253908e20*b[0, 2]*b[2, 1]*b[2, 2]-0.1150000000e22*b[0, 2]*b[2, 1]*a[0, 0]+0.5750000000e21*b[0, 2]*b[2, 1]*a[0, 2]+0.6639528096e21*b[0, 2]*b[2, 1]*a[1, 0]-0.3319764049e21*b[0, 2]*b[2, 1]*a[1, 2]-0.6200000000e12*b[0, 2]*b[2, 1]*a[2, 0]-0.2165063465e30*b[0, 2]*b[2, 2]*a[0, 0]+0.1082531732e30*b[0, 2]*b[2, 2]*a[0, 2]+0.1249999974e30*b[0, 2]*b[2, 2]*a[1, 0]-0.6249999876e29*b[0, 2]*b[2, 2]*a[1, 2]-0.8660253820e20*b[0, 2]*b[2, 2]*a[2, 0]+0.2886751339e30*b[1, 0]*b[1, 2]*b[2, 0]-0.1443375645e30*b[1, 0]*b[1, 2]*b[2, 2]-0.1044658198e31*b[1, 0]*b[1, 2]*a[0, 0]+0.5223290991e30*b[1, 0]*b[1, 2]*a[0, 2]+0.6031336920e30*b[1, 0]*b[1, 2]*a[1, 0]-0.3015668461e30*b[1, 0]*b[1, 2]*a[1, 2]-0.5511966128e21*b[1, 0]*b[1, 2]*a[2, 0]-0.9499999983e21*b[1, 0]*b[2, 0]*b[2, 2]+0.5000000002e30*b[1, 0]*b[2, 0]*a[0, 0]-0.2500000001e30*b[1, 0]*b[2, 0]*a[0, 2]-0.2886751347e30*b[1, 0]*b[2, 0]*a[1, 0]+0.1443375675e30*b[1, 0]*b[2, 0]*a[1, 2]+0.1999999999e21*b[1, 0]*b[2, 0]*a[2, 0]-0.5178632795e21*b[1, 0]*b[2, 1]*b[1, 2]+0.2000000000e21*b[1, 0]*b[2, 1]*b[2, 0]-0.9999999929e20*b[1, 0]*b[2, 1]*b[2, 2]+0.2577350271e21*b[1, 0]*b[2, 1]*a[0, 0]-0.1288675135e21*b[1, 0]*b[2, 1]*a[0, 2]-0.1488033873e21*b[1, 0]*b[2, 1]*a[1, 0]+0.7440169378e20*b[1, 0]*b[2, 1]*a[1, 2]-0.8165807531e11*b[1, 0]*b[2, 1]*a[2, 0]-0.2499999988e30*b[1, 0]*b[2, 2]*a[0, 0]+0.1249999994e30*b[1, 0]*b[2, 2]*a[0, 2]+0.1443375666e30*b[1, 0]*b[2, 2]*a[1, 0]-0.7216878336e29*b[1, 0]*b[2, 2]*a[1, 2]-0.9999999907e20*b[1, 0]*b[2, 2]*a[2, 0]+0.4749999988e21*b[1, 2]*b[2, 0]*b[2, 2]-0.2499999998e30*b[1, 2]*b[2, 0]*a[0, 0]+0.1249999999e30*b[1, 2]*b[2, 0]*a[0, 2]+0.1443375672e30*b[1, 2]*b[2, 0]*a[1, 0]-0.7216878364e29*b[1, 2]*b[2, 0]*a[1, 2]-0.9999999982e20*b[1, 2]*b[2, 0]*a[2, 0]-0.9999999984e20*b[1, 2]*b[2, 1]*b[2, 0]+0.4999999937e20*b[1, 2]*b[2, 1]*b[2, 2]+0.5639528091e21*b[1, 2]*b[2, 1]*a[0, 0]-0.2819764046e21*b[1, 2]*b[2, 1]*a[0, 2]-0.3255983061e21*b[1, 2]*b[2, 1]*a[1, 0]+0.1627991531e21*b[1, 2]*b[2, 1]*a[1, 2]+0.3179571668e12*b[1, 2]*b[2, 1]*a[2, 0]+0.1249999979e30*b[1, 2]*b[2, 2]*a[0, 0]-0.6249999893e29*b[1, 2]*b[2, 2]*a[0, 2]-0.7216878241e29*b[1, 2]*b[2, 2]*a[1, 0]+0.3608439123e29*b[1, 2]*b[2, 2]*a[1, 2]+0.4999999891e20*b[1, 2]*b[2, 2]*a[2, 0]+0.2424871127e12*b[2, 0]*b[2, 1]*b[2, 2]-0.3464101619e21*b[2, 0]*b[2, 1]*a[0, 0]+0.1732050810e21*b[2, 0]*b[2, 1]*a[0, 2]+0.2000000002e21*b[2, 0]*b[2, 1]*a[1, 0]-0.1000000002e21*b[2, 0]*b[2, 1]*a[1, 2]-0.1385640646e12*b[2, 0]*b[2, 1]*a[2, 0]+0.1039230484e22*b[2, 0]*b[2, 2]*a[0, 0]-0.5196152421e21*b[2, 0]*b[2, 2]*a[0, 2]-0.5999999998e21*b[2, 0]*b[2, 2]*a[1, 0]+0.3000000001e21*b[2, 0]*b[2, 2]*a[1, 2]+0.4156921934e12*b[2, 0]*b[2, 2]*a[2, 0]+0.1732050805e21*b[2, 1]*b[2, 2]*a[0, 0]-0.8660254025e20*b[2, 1]*b[2, 2]*a[0, 2]-0.9999999985e20*b[2, 1]*b[2, 2]*a[1, 0]+0.4999999996e20*b[2, 1]*b[2, 2]*a[1, 2]+0.6928203188e11*b[2, 1]*b[2, 2]*a[2, 0]-0.4330127000e21*b[2, 2]^2*a[0, 0]+0.2165063500e21*b[2, 2]^2*a[0, 2]+0.2499999989e21*b[2, 2]^2*a[1, 0]-0.1249999995e21*b[2, 2]^2*a[1, 2]-0.1732050796e12*b[2, 2]^2*a[2, 0]+0.2000000000e21*a[1, 1]*b[0, 0]-0.1000000000e21*a[1, 1]*b[0, 2]-0.1154700538e21*a[1, 1]*b[1, 0]+0.5773502700e20*a[1, 1]*b[1, 2]+0.8000000000e11*a[1, 1]*b[2, 0]+0.8000000000e11*a[1, 1]*b[2, 1]-0.2000000000e12*a[1, 1]*b[2, 2]+0.5000000000e21*a[2, 2]*b[0, 0]-0.2500000000e21*a[2, 2]*b[0, 2]-0.2886751346e21*a[2, 2]*b[1, 0]+0.1443375675e21*a[2, 2]*b[1, 2]+0.2000000000e12*a[2, 2]*b[2, 0]+0.2000000000e12*a[2, 2]*b[2, 1]-0.5000000000e12*a[2, 2]*b[2, 2]+0.5000000000e21*b[0, 0]^2*a[2, 2]-0.5000000000e21*b[0, 0]*b[0, 2]*a[2, 2]-0.5773502692e21*b[0, 0]*b[1, 0]*a[2, 2]+0.2886751350e21*b[0, 0]*b[1, 2]*a[2, 2]+0.4000000000e12*b[0, 0]*b[2, 0]*a[2, 2]+0.4000000000e12*b[0, 0]*b[2, 1]*a[2, 2]+0.2886751346e21*b[0, 2]*b[1, 0]*a[2, 2]-0.1443375675e21*b[0, 2]*b[1, 2]*a[2, 2]-0.2000000000e12*b[0, 2]*b[2, 0]*a[2, 2]-0.2000000000e12*b[0, 2]*b[2, 1]*a[2, 2]-0.1666666669e21*b[1, 0]*b[1, 2]*a[2, 2]-0.2309401077e12*b[1, 0]*b[2, 0]*a[2, 2]-0.2309401077e12*b[1, 0]*b[2, 1]*a[2, 2]+0.1154700540e12*b[1, 2]*b[2, 0]*a[2, 2]+0.1154700540e12*b[1, 2]*b[2, 1]*a[2, 2]+160.*b[2, 0]*b[2, 1]*a[2, 2]+0.1250000000e21*b[0, 2]^2*a[2, 2]+0.1666666667e21*b[1, 0]^2*a[2, 2]+0.4166666678e20*b[1, 2]^2*a[2, 2]+80.*b[2, 0]^2*a[2, 2]+80.*b[2, 1]^2*a[2, 2]+0.6666666667e20*a[1, 1]*b[1, 0]^2-0.1333333333e21*b[1, 1]*b[1, 0]^2+0.2000000000e21*a[1, 1]*b[0, 0]^2-0.4000000000e21*b[1, 1]*b[0, 0]^2+0.5000000000e20*a[1, 1]*b[0, 2]^2-0.1000000000e21*b[1, 1]*b[0, 2]^2-0.2000000000e21*b[0, 0]*a[1, 1]*b[0, 2]-0.2309401077e21*b[0, 0]*a[1, 1]*b[1, 0]+0.1154700540e21*b[0, 0]*a[1, 1]*b[1, 2]+0.1600000000e12*b[0, 0]*a[1, 1]*b[2, 0]+0.1600000000e12*b[0, 0]*a[1, 1]*b[2, 1]-0.4000000000e12*b[0, 0]*a[1, 1]*b[2, 2]-0.1000000000e13*b[0, 0]*a[2, 2]*b[2, 2]+0.4000000000e21*b[0, 0]*b[1, 1]*b[0, 2]+0.4618802154e21*b[0, 0]*b[1, 1]*b[1, 0]-0.2309401080e21*b[0, 0]*b[1, 1]*b[1, 2]-0.3200000000e12*b[0, 0]*b[1, 1]*b[2, 0]+0.6000000000e12*b[0, 0]*b[1, 1]*b[2, 2]-0.4000000000e21*b[0, 0]*b[1, 1]*a[0, 0]+0.2000000000e21*b[0, 0]*b[1, 1]*a[0, 2]+0.2309401077e21*b[0, 0]*b[1, 1]*a[1, 0]-0.1154700539e21*b[0, 0]*b[1, 1]*a[1, 2]-0.1600000000e12*b[0, 0]*b[1, 1]*a[2, 0]+0.1154700538e21*b[0, 2]*a[1, 1]*b[1, 0]-0.5773502700e20*b[0, 2]*a[1, 1]*b[1, 2]-0.8000000000e11*b[0, 2]*a[1, 1]*b[2, 0]-0.8000000000e11*b[0, 2]*a[1, 1]*b[2, 1]+0.2000000000e12*b[0, 2]*a[1, 1]*b[2, 2]+0.5000000000e12*b[0, 2]*a[2, 2]*b[2, 2]-0.2309401077e21*b[0, 2]*b[1, 1]*b[1, 0]+0.1154700540e21*b[0, 2]*b[1, 1]*b[1, 2]+0.1600000000e12*b[0, 2]*b[1, 1]*b[2, 0]-0.3000000000e12*b[0, 2]*b[1, 1]*b[2, 2]+0.2000000000e21*b[0, 2]*b[1, 1]*a[0, 0]-0.1000000000e21*b[0, 2]*b[1, 1]*a[0, 2]-0.1154700538e21*b[0, 2]*b[1, 1]*a[1, 0]+0.5773502696e20*b[0, 2]*b[1, 1]*a[1, 2]+0.8000000000e11*b[0, 2]*b[1, 1]*a[2, 0]-0.6666666676e20*b[1, 0]*a[1, 1]*b[1, 2]-0.9237604307e11*b[1, 0]*a[1, 1]*b[2, 0]-0.9237604307e11*b[1, 0]*a[1, 1]*b[2, 1]+0.2309401077e12*b[1, 0]*a[1, 1]*b[2, 2]+0.5773502692e12*b[1, 0]*a[2, 2]*b[2, 2]+0.1333333335e21*b[1, 0]*b[1, 1]*b[1, 2]+0.1847520861e12*b[1, 0]*b[1, 1]*b[2, 0]-0.3464101615e12*b[1, 0]*b[1, 1]*b[2, 2]+0.2309401077e21*b[1, 0]*b[1, 1]*a[0, 0]-0.1154700538e21*b[1, 0]*b[1, 1]*a[0, 2]-0.1333333333e21*b[1, 0]*b[1, 1]*a[1, 0]+0.6666666672e20*b[1, 0]*b[1, 1]*a[1, 2]+0.9237604307e11*b[1, 0]*b[1, 1]*a[2, 0]+0.4618802160e11*b[1, 2]*a[1, 1]*b[2, 0]+0.4618802160e11*b[1, 2]*a[1, 1]*b[2, 1]-0.1154700540e12*b[1, 2]*a[1, 1]*b[2, 2]-0.2886751350e12*b[1, 2]*a[2, 2]*b[2, 2]-0.9237604320e11*b[1, 2]*b[1, 1]*b[2, 0]+0.1732050810e12*b[1, 2]*b[1, 1]*b[2, 2]-0.1154700540e21*b[1, 2]*b[1, 1]*a[0, 0]+0.5773502700e20*b[1, 2]*b[1, 1]*a[0, 2]+0.6666666676e20*b[1, 2]*b[1, 1]*a[1, 0]-0.3333333340e20*b[1, 2]*b[1, 1]*a[1, 2]-0.4618802160e11*b[1, 2]*b[1, 1]*a[2, 0]+64.*b[2, 0]*a[1, 1]*b[2, 1]-160.*b[2, 0]*a[1, 1]*b[2, 2]-400.*b[2, 0]*a[2, 2]*b[2, 2]+240.*b[2, 0]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 0]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 0]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 0]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 0]*b[1, 1]*a[1, 2]-64.*b[2, 0]*b[1, 1]*a[2, 0]-160.*b[2, 1]*a[1, 1]*b[2, 2]-400.*b[2, 1]*a[2, 2]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*b[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*b[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*b[1, 0]-0.4618802160e11*b[2, 1]*b[1, 1]*b[1, 2]-64.*b[2, 1]*b[1, 1]*b[2, 0]+80.*b[2, 1]*b[1, 1]*b[2, 2]-0.1600000000e12*b[2, 1]*b[1, 1]*a[0, 0]+0.8000000000e11*b[2, 1]*b[1, 1]*a[0, 2]+0.9237604307e11*b[2, 1]*b[1, 1]*a[1, 0]-0.4618802157e11*b[2, 1]*b[1, 1]*a[1, 2]-64.*b[2, 1]*b[1, 1]*a[2, 0]+0.4000000000e12*b[2, 2]*b[1, 1]*a[0, 0]-0.2000000000e12*b[2, 2]*b[1, 1]*a[0, 2]-0.2309401077e12*b[2, 2]*b[1, 1]*a[1, 0]+0.1154700539e12*b[2, 2]*b[1, 1]*a[1, 2]+160.*b[2, 2]*b[1, 1]*a[2, 0]+0.1666666671e20*a[1, 1]*b[1, 2]^2-0.3333333343e20*b[1, 1]*b[1, 2]^2+32.*a[1, 1]*b[2, 0]^2-64.*b[1, 1]*b[2, 0]^2+32.*a[1, 1]*b[2, 1]^2+200.*a[1, 1]*b[2, 2]^2+500.*a[2, 2]*b[2, 2]^2-200.*b[1, 1]*b[2, 2]^2+0.6428203230e31*b[0, 0]*b[0, 2]*b[1, 0]-0.4946152426e31*b[0, 0]*b[0, 2]*b[1, 2]+0.8660253998e30*b[0, 0]*b[0, 2]*b[2, 0]-0.4330126915e30*b[0, 0]*b[0, 2]*b[2, 2]-0.4000000000e31*b[0, 0]*b[0, 2]*a[0, 0]+0.2000000000e31*b[0, 0]*b[0, 2]*a[0, 2]+0.2309401077e31*b[0, 0]*b[0, 2]*a[1, 0]-0.1154700539e31*b[0, 0]*b[0, 2]*a[1, 2]-0.2000000000e22*b[0, 0]*b[0, 2]*a[2, 0]-0.3422649732e31*b[0, 0]*b[1, 0]*b[1, 2]+0.9999999986e30*b[0, 0]*b[1, 0]*b[2, 0]-0.4999999940e30*b[0, 0]*b[1, 0]*b[2, 2]-0.6547005380e30*b[0, 0]*b[1, 0]*a[0, 0]+0.3273502690e30*b[0, 0]*b[1, 0]*a[0, 2]+0.3779915319e30*b[0, 0]*b[1, 0]*a[1, 0])/((5000000000.+5000000000.*b[0, 0]-2500000000.*b[0, 2]-2886751346.*b[1, 0]+1443375675.*b[1, 2]+2.*b[2, 0]+2.*b[2, 1]-5.*b[2, 2])*(0.1000000000e11*b[0, 0]-5000000000.*b[0, 2]-5773502692.*b[1, 0]+2886751350.*b[1, 2]+4.*b[2, 0]-5.*b[2, 2]+0.1000000000e11*a[0, 0]-5000000000.*a[0, 2]-5773502692.*a[1, 0]+2886751348.*a[1, 2]+4.*a[2, 0])) = 0, -1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-8*a[2, 2]+2.*a[0, 1]+6.*a[0, 2] = 0, -1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-8*a[2, 2]+2.*a[0, 1]-6.*a[0, 2] = 0, 1.154700538*a[1, 1]-3.464101615*a[1, 2]+0.1000000000e-7*a[2, 2]+2.*a[0, 1]-6.*a[0, 2] = 0, 1.154700538*a[1, 1]+3.464101615*a[1, 2]-0.1000000000e-7*a[2, 2]+2.*a[0, 1]+6.*a[0, 2] = 0, 1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]-3.464101615*b[1, 2]+0.1000000000e-7*b[2, 2] = 0, 1.154700538*b[1, 1]+3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-7*b[2, 2] = 0, a[0, 0]-.5000000000*a[0, 2]-1.*a[1, 0]+.5000000000*a[1, 2]+a[2, 0]-.5000000000*a[2, 2] = 0, -.5000000000*b[0, 2]+.5000000000*b[1, 2]-.5000000000*b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0] = 0, -1.154700538*b[1, 1]+2.*b[0, 1]-6.*b[0, 2]+3.464101615*b[1, 2]-0.1000000000e-9*b[2, 1]-0.1000000000e-8*b[2, 2] = 0, -1.154700538*b[1, 1]-3.464101615*b[1, 2]+2.*b[0, 1]+6.*b[0, 2]-0.1000000000e-9*b[2, 1]+0.1000000000e-8*b[2, 2] = 0, a[0, 0]+a[0, 1]+a[0, 2]-1.*a[1, 0]-1.*a[1, 1]-1.*a[1, 2]+a[2, 0]+a[2, 1]+a[2, 2] = 0, a[0, 0]-1.*a[0, 1]+a[0, 2]-1.*a[1, 0]+a[1, 1]-1.*a[1, 2]+a[2, 0]-1.*a[2, 1]+a[2, 2] = 0, b[0, 0]-1.*b[0, 1]+b[0, 2]-1.*b[1, 0]+b[1, 1]-1.*b[1, 2]+b[2, 0]-1.*b[2, 1]+b[2, 2] = 0, b[0, 1]+b[0, 2]-1.*b[1, 1]-1.*b[1, 2]+b[2, 1]+b[2, 2]+b[0, 0]-1.*b[1, 0]+b[2, 0] = 0}, {a[0, 0], a[0, 1], a[0, 2], a[1, 0], a[1, 1], a[1, 2], a[2, 0], a[2, 1], a[2, 2], b[0, 0], b[0, 1], b[0, 2], b[1, 0], b[1, 1], b[1, 2], b[2, 0], b[2, 1], b[2, 2]})

(34)

``


 

Download aisha.mw

Version 2 do not enable to expand multiple product like A*A*B*E
Version 3 will now do that.
I just forgot to add this feature.

LL.
 

######################################################################
# NOTICE                                                             #
# Author: Louis Lamarche                                             #
#         Institute of Research of Hydro-Quebec (IREQ)               #
#         Science des données et haute performance                   #
#         2018, March 7                                              #
#                                                                    #
# Function name: ExpandQop (x)                                       #
#       Purpose: Compute the tensor product of two quantum           #
#                operators in Dirac notations                        #
#      Argument: x: a quantum operator                               #
#  Improvements: Manage all +, -, *, /, ^, mod  operations           #
#                in the argument. Manages multiple tensor products   #
#                like A*B*C*F                                        #
#       Version: 3                                                   #
#                                                                    #
#  Copyrigth(c) Hydro-Quebec.                                        #
#        Note 1: Permission to use this softwate is granted if you   #
#                acknowledge its author and copyright                #
#        Note 2: Permission to copy this softwate is granted if you  #
#                leave this 21 lines notice intact. Thank you.       #
######################################################################
restart;

with(Physics):
interface(imaginaryunit=i):
Setup(mathematicalnotation=true);

[mathematicalnotation = true]

(1)

Setup(quantumoperators={A,B,C,Cn});
Setup(noncommutativeprefix={a,b,q});

[quantumoperators = {A, B, C, Cn}]

 

[noncommutativeprefix = {a, b, q}]

(2)

opexp:= op(0,10^x):            # exponentiation id
opnp := op(0,10*x):            # normal product id
optp := op(0,Ket(q0)*Ket(q1)): # tensor product id
opdiv:= `Fraction`:            # fraction       id          
opsym:= op(0,x):               # symbol         id
opint:= op(0,10):              # integer        id
opflt:= op(0,10.0):            # float          id
opcpx:= op(0,i):               # complex        id
opbra:= op(0,Bra(q)):          # bra            id
opket:= op(0,Ket(q)):          # ket            id
opmod:= op(0, a mod b):        # mod            id
ExpandQop:=proc(x)
    local nx,ret,j,lkb,cbk,rkb,no,lop,success;
    lop:=op(0,x);
    no:=nops(x);
    if lop = opsym or lop = opint or lop = opflt or
       lop = opbra or lop = opket or lop = opcpx then
         ret:=x;
    else
    if lop = opexp then
        ret:=x;
    else       
    if lop = opnp then
        ret:=1;
        for j from 1 to no do
            ret:=ret*ExpandQop(op(j,x));
        end do;        
    else
    if lop = `+` then
        ret:=0;
        for j from 1 to no do
            ret:=ret+ExpandQop(op(j,x));
        end do;
    else
    if lop = `-` then
        ret:=0;
        for j from 1 to no do
            ret:=ret-ExpandQop(op(j,x));
        end do;
    else
    if lop = opdiv then
       ret:=1;
       for j from 1 to no do
           ret:=ret/ExpandQop(op(j,x));
       end do;
    else
    if lop = opmod then
       ret:=x;
    else
    if lop = optp then
       if (no > 3 ) then
           success:=false;
           nx:=x;
           while not success do
             lkb:=0; cbk:=0; rkb:=0;ret:=1;
             for j from 1 to no do
                 if (j>1) then
                      if(lkb=0) then
                          if( type(op(j-1,nx),Ket) and
                              type(op(j,nx),Bra) ) then lkb:=j-1; fi;
                      else
                          if( type(op(j-1,nx),Ket) and
                              type(op(j,nx),Bra) ) then rkb:=j;   fi;
                      fi;
                      if( type(op(j-1,nx),Bra) and type(op(j,nx),Ket) )
                                                   then cbk:=j;   fi;
                 fi;
             end do;
             if ( (lkb < cbk) and (cbk<rkb) ) then
                 for j from 1     to lkb   do ret := ret*op(j,nx); end do;
                 for j from cbk   to no    do ret := ret*op(j,nx); end do;
                 for j from lkb+1 to cbk-1 do ret := ret*op(j,nx); end do;
             else
               ret:=nx;
             fi;
             
             if nx = ret then
                success := true;
             else
                nx := ret;
             fi
           end do;
       else
           ret:=x;
       fi;
    else ret:=x;
    fi; # optp
    fi; # opmod
    fi; # opdiv
    fi; # `-`
    fi; # `+`
    fi; # `opnp
    fi; # `opexp`
    fi; # opsym, opint, opflt, opbra, opket, opcpx

    return ret;
end proc:

# For saving
# save opexp,opnp,optp,opdiv,opint,opflt,opcpx,opbra,opket,opmod, ExpandQop,"ExpandQop.m"

# Let A be an operator in a first Hilbert space of dimension n
#  using the associated orthonormal ket and bra vectors
#
#
kets1:=Ket(a1)*Ket(a2)*Ket(a3)*Ket(a4)*Ket(a5):
A:=kets1*Dagger(kets1);


# Let B be an operator in a second Hilbert (Ketspace of dimension m
#  using the associated orthonormal ket and bra vectors
#
#
kets2:=Ket(b1)*Ket(b2)*Ket(b3):
B:=kets2*Dagger(kets2);


# The tensor product of the two operators acts on a n+m third
# Hilbert space   unsing the appropriately ordered ket
# and bra  vectors of the two preceding spaces. The rule for
# building this operator in Dirac notation is as follows,
#
#


print("Maple do not compute the tensor product of operators,");
print("C=A*B gives:");
C:=A*B;

print("ExpandQop(C) gives the expected result:");
Cn:=ExpandQop(C);

Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1))

 

Physics:-`*`(Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1))

 

"Maple do not compute the tensor product of operators,"

 

"C=A*B gives:"

 

Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1))

 

"ExpandQop(C) gives the expected result:"

 

Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1))

(3)

kets3:=kets1*kets2;
bras3:=Dagger(kets3);
print("Matrix elements computed with C appears curious");
'bras3.C. kets3'="...";
bras3.C.kets3;
print("Matrix elements computed with Cn as expected");
'bras3.Cn.kets3'=bras3.Cn.kets3;

Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3))

 

Physics:-`*`(Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1))

 

"Matrix elements computed with C appears curious"

 

Physics:-`.`(bras3, C, kets3) = "..."

 

Physics:-Bracket(Physics:-Bra(b1), Physics:-Ket(a1))*Physics:-Bracket(Physics:-Bra(b2), Physics:-Ket(a2))*Physics:-Bracket(Physics:-Bra(b3), Physics:-Ket(a3))*Physics:-Bracket(Physics:-Bra(a1), Physics:-Ket(b1))*Physics:-Bracket(Physics:-Bra(a2), Physics:-Ket(b2))*Physics:-Bracket(Physics:-Bra(a3), Physics:-Ket(b3))*Physics:-Bracket(Physics:-Bra(a4), Physics:-Ket(a4))^2*Physics:-Bracket(Physics:-Bra(a5), Physics:-Ket(a5))^2*Physics:-Bracket(Physics:-Bra(a1), Physics:-Ket(a1))*Physics:-Bracket(Physics:-Bra(a2), Physics:-Ket(a2))*Physics:-Bracket(Physics:-Bra(a3), Physics:-Ket(a3))*Physics:-Bracket(Physics:-Bra(b1), Physics:-Ket(b1))*Physics:-Bracket(Physics:-Bra(b2), Physics:-Ket(b2))*Physics:-Bracket(Physics:-Bra(b3), Physics:-Ket(b3))

 

"Matrix elements computed with Cn as expected"

 

Physics:-`.`(bras3, Cn, kets3) = Physics:-Bracket(Physics:-Bra(a1), Physics:-Ket(a1))^2*Physics:-Bracket(Physics:-Bra(a2), Physics:-Ket(a2))^2*Physics:-Bracket(Physics:-Bra(a3), Physics:-Ket(a3))^2*Physics:-Bracket(Physics:-Bra(a4), Physics:-Ket(a4))^2*Physics:-Bracket(Physics:-Bra(a5), Physics:-Ket(a5))^2*Physics:-Bracket(Physics:-Bra(b1), Physics:-Ket(b1))^2*Physics:-Bracket(Physics:-Bra(b2), Physics:-Ket(b2))^2*Physics:-Bracket(Physics:-Bra(b3), Physics:-Ket(b3))^2

(4)

print("Example");
En:=ExpandQop(10*(1-x+y+z)*i*(1/sqrt(2))*A*B);

"Example"

 

-(5*I)*2^(1/2)*(-1+x-y-z)*Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1))

(5)

print("Another example");
'F'='A*B/sqrt(2)+B*A/sqrt(2)';
F:=A*B/sqrt(2)+B*A/sqrt(2):
'op(1,F)'=op(1,F);
'op(2,F)'=op(2,F);

'Fn'='ExpandQop(F)';
Fn:=ExpandQop(F):
'op(1,Fn)'=op(1,Fn);
'op(2,Fn)'=op(2,Fn);

"Another example"

 

F = Physics:-`*`(Physics:-`*`(A, B), Physics:-`^`(sqrt(2), -1))+Physics:-`*`(Physics:-`*`(B, A), Physics:-`^`(sqrt(2), -1))

 

op(1, F) = (1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1))

 

op(2, F) = (1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1))

 

Fn = ExpandQop(F)

 

op(1, Fn) = (1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1))

 

op(2, Fn) = (1/2)*2^(1/2)*Physics:-`*`(Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Ket(a1), Physics:-Ket(a2), Physics:-Ket(a3), Physics:-Ket(a4), Physics:-Ket(a5), Physics:-Bra(a5), Physics:-Bra(a4), Physics:-Bra(a3), Physics:-Bra(a2), Physics:-Bra(a1), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1))

(6)

print("Final example, multiple products");
G:=B*B*B;
'G'=ExpandQop(G);

"Final example, multiple products"

 

Physics:-`*`(Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1))

 

G = Physics:-`*`(Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Ket(b1), Physics:-Ket(b2), Physics:-Ket(b3), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1), Physics:-Bra(b3), Physics:-Bra(b2), Physics:-Bra(b1))

(7)

 


 

Download ExpandQopV3.mw

Dear all

Is there any one can help me to find  the Maple code to solve these fractioanal equations  using fractional Adams-Bashforth-Moulton method

Doc229.pdf

Thank you very much for helping me.

 

 

 

 

 

 

 

I have the following ode: 

ode1 := diff(x(t), t, t) = (5*9.80665)*sin((1/6)*Pi)-(10*(10-sqrt(x(t)^2+25)))*x(t)/sqrt(x(t)^2+25)-(diff(x(t), t))

I tried the following code: 

DEplot(ode, x(t), t = -2 .. 2, [`$`([x(0) = (1/4)*k], k = -20 .. 20)], x = -8 .. 8, color = blue, stepsize = 0.5e-1, linecolour = red, arrows = MEDIUM)

But I get the following error: 

Error, (in DEtools/DEplot/CheckInitial) too few initial conditions: [x(0) = -5]

Any help in plotting this differential equation will be much appreciated. 

 

Hi,

I'm searching for an easier way to execute the following computation using only matrix calculations
(meaning no programming, no loops):

> restart:with(linalg):
> S:=matrix(3,3,[s11,s12,s13,s21,s22,s23,s31,s32,s33]):
> X:=matrix(3,1,[x1,x2,x3]):
> A:=array(1..3,1..3):
> for j from 1 to 3 do
>   for i from 1 to 3 do
>     A[i,j]:=S[i,j]/X[j,1]
>   od;
> od;
> op(A);

So far, I've got the following ideas:

A)
> S:=matrix(3,3,[s11,s12,s13,s21,s22,s23,s31,s32,s33]):
> X:=matrix(3,1,[x1,x2,x3]):
> h:=matrix(1,3,[1,1,1]):
> Xm:=evalm(transpose(h)&*transpose(X)):
## memberwise division: S / Xm   

How can I do a memberwise division?

B)
>S:=matrix(3,3,[s11,s12,s13,s21,s22,s23,s31,s32,s33]):
>X:=matrix(3,1,[x1,x2,x3]):
## make X the diagonal of a square matrix
> Xd:=matrix(3,3,[x1,0,0,0,x2,0,0,0,x3]):
> A:=evalm(S&*inverse(Xd));

How can I make a vector X the diagonal of a square matrix (without retyping the values)?

Thanks in advance
Ben

 

with(Physics[Vectors]);

This should  equal Dirac delta function

I know this must have been addressed somewhere previously.  However I have searched extensively and not been able to find an answer.  Sorry for asking again.

In the package Student[Calculus1], the NewTon-Cotes closed formulas are implemented. But I was thinking if there is any other package of Maple having the open Newton-Cotes Fromulas. I searched and I just saw in Student[NumericalAnalysis] for Quadratures.

I have a vector P_X

I want to use it in the constraint of Maple optimization, that all item in P_X is smaller than 1. I am looking for some expression looks like: all(P_X[i]<1,i=1..10)

Thanks.

Hello, 

I want to change some values of a matrix. 

For example: I have a matrix with measured data, but some of these values get the number 1.0 (because maple cannot import these expression correctly). Is it possible to change all "1.0" with an other expression?

Thanks a lot!
Martin

First 839 840 841 842 843 844 845 Last Page 841 of 2216