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Physics

 

 

Maple provides a state-of-the-art environment for algebraic and tensorial computations in Physics, with emphasis on ensuring that the computational experience is as natural as possible.

 

The theme of the Physics project for Maple 2017 has been the consolidation of the functionality introduced in previous releases, together with significant enhancements and new functionality in General Relativity, in connection with classification of solutions to Einstein's equations and tensor representations to work in an embedded 3D curved space - a new ThreePlusOne  package. This package is relevant in numerical relativity and a Hamiltonian formulation of gravity. The developments also include first steps in connection with computational representations for all the objects entering the Standard Model in particle physics.

Classification of solutions to Einstein's equations and the Tetrads package

 

In Maple 2016, the digitizing of the database of solutions to Einstein's equations  was finished, added to the standard Maple library, with all the metrics from "Stephani, H.; Kramer, D.; MacCallum, M.; Hoenselaers, C.; and Herlt, E., Exact Solutions to Einstein's Field Equations". These metrics can be loaded to work with them, or change them, or searched using g_  (the Physics command representing the spacetime metric that also sets the metric to your choice in one go) or using the command DifferentialGeometry:-Library:-MetricSearch .


In Maple 2017, the Physics:-Tetrads  package has been vastly improved and extended, now including new commands like PetrovType  and SegreType  to classify these metrics, and the TransformTetrad  now has an option canonicalform to automatically derive a transformation and put the tetrad in canonical form (reorientation of the axis of the local system of references), a relevant step in resolving the equivalence between two metrics.

Examples

 

Petrov and Segre types, tetrads in canonical form

   

Equivalence for Schwarzschild metric (spherical and Kruskal coordinates)

 

Formulation of the problem (remove mixed coordinates)

   

Solving the Equivalence

   

The ThreePlusOne (3 + 1) new Maple 2017 Physics package

 

ThreePlusOne , is a package to cast Einstein's equations in a 3+1 form, that is, representing spacetime as a stack of nonintersecting 3-hypersurfaces Σ. This 3+1 description is key in the Hamiltonian formulation of gravity as well as in the study of gravitational waves, black holes, neutron stars, and in general to study the evolution of physical system in general relativity by running numerical simulations as traditional initial value (Cauchy) problems. ThreePlusOne includes computational representations for the spatial metric gamma[i, j] that is induced by g[mu, nu] on the 3-dimensional hypersurfaces, and the related covariant derivative, Christoffel symbols and Ricci and Riemann tensors, the Lapse, Shift, Unit normal and Time vectors and Extrinsic curvature related to the ADM equations.

 

The following is a list of the available commands:

 

ADMEquations

Christoffel3

D3_

ExtrinsicCurvature

gamma3_

Lapse

Ricci3

Riemann3

Shift

TimeVector

UnitNormalVector

 

 

The other four related new Physics  commands:

 

• 

Decompose , to decompose 4D tensorial expressions (free and/or contracted indices) into the space and time parts.

• 

gamma_ , representing the three-dimensional metric tensor, with which the element of spatial distance is defined as  `#mrow(msup(mi("dl"),mrow(mo("⁢"),mn("2"))),mo("="),msub(mi("γ",fontstyle = "normal"),mrow(mi("i"),mo(","),mi("j"))),mo("⁢"),msup(mi("dx"),mi("i")),mo("⁢"),msup(mi("dx"),mi("j")))`.

• 

Redefine , to redefine the coordinates and the spacetime metric according to changes in the signature from any of the four possible signatures(− + + +), (+ − − −), (+ + + −) and ((− + + +) to any of the other ones.

• 

EnergyMomentum , is a computational representation for the energy-momentum tensor entering Einstein's equations as well as their 3+1 form, the ADMEquations .

 

Examples

 

restart; with(Physics); Setup(coordinatesystems = cartesian)

`Default differentiation variables for d_, D_ and dAlembertian are: `*{X = (x, y, z, t)}

 

`Systems of spacetime Coordinates are: `*{X = (x, y, z, t)}

 

[coordinatesystems = {X}]

(2.1.1)

with(ThreePlusOne)

`Setting lowercaselatin_is letters to represent space indices `

 

0, "%1 is not a command in the %2 package", ThreePlusOne, Physics

 

`Changing the signature of spacetime from `(`- - - +`)*` to `(`+ + + -`)*` in order to match the signature customarily used in the ADM formalism`

 

[ADMEquations, Christoffel3, D3_, ExtrinsicCurvature, Lapse, Ricci3, Riemann3, Shift, TimeVector, UnitNormalVector, gamma3_]

(2.1.2)

Note the different color for gamma[mu, nu], now a 4D tensor representing the metric of a generic 3-dimensional hypersurface induced by the 4D spacetime metric g[mu, nu]. All the ThreePlusOne tensors are displayed in black to distinguish them of the corresponding 4D or 3D tensors. The particular hypersurface gamma[mu, nu] operates is parameterized by the Lapse  alpha and the Shift  beta[mu].

The induced metric gamma[mu, nu]is defined in terms of the UnitNormalVector  n[mu] and the 4D metric g[mu, nu] as

gamma3_[definition]

Physics:-ThreePlusOne:-gamma3_[mu, nu] = Physics:-ThreePlusOne:-UnitNormalVector[mu]*Physics:-ThreePlusOne:-UnitNormalVector[nu]+Physics:-g_[mu, nu]

(2.1.3)

where n[mu] is defined in terms of the Lapse  alpha and the derivative of a scalar function t that can be interpreted as a global time function

UnitNormalVector[definition]

Physics:-ThreePlusOne:-UnitNormalVector[mu] = -Physics:-ThreePlusOne:-Lapse*Physics:-D_[mu](t)

(2.1.4)

The TimeVector  is defined in terms of the Lapse  alpha and the Shift  beta[mu] and this vector  n[mu] as

TimeVector[definition]

Physics:-ThreePlusOne:-TimeVector[mu] = Physics:-ThreePlusOne:-Lapse*Physics:-ThreePlusOne:-UnitNormalVector[mu]+Physics:-ThreePlusOne:-Shift[mu]

(2.1.5)

The ExtrinsicCurvature  is defined in terms of the LieDerivative  of  gamma[mu, nu]

ExtrinsicCurvature[definition]

Physics:-ThreePlusOne:-ExtrinsicCurvature[mu, nu] = -(1/2)*Physics:-LieDerivative[Physics:-ThreePlusOne:-UnitNormalVector](Physics:-ThreePlusOne:-gamma3_[mu, nu])

(2.1.6)

The metric gamma[mu, nu]is also a projection tensor in that it projects 4D tensors into the 3D hypersurface Σ. The definition for any 4D tensor that is also a 3D tensor in Σ, can thus be written directly by contracting their indices with gamma[mu, nu]. In the case of Christoffel3 , Ricci3  and Riemann3,  these tensors can be defined by replacing the 4D metric g[mu, nu] by gamma[mu, nu] and the 4D Christoffel symbols GAMMA[mu, nu, alpha] by the ThreePlusOne GAMMA[mu, nu, alpha] in the definitions of the corresponding 4D tensors. So, for instance

Christoffel3[definition]

Physics:-ThreePlusOne:-Christoffel3[mu, nu, alpha] = (1/2)*Physics:-ThreePlusOne:-gamma3_[mu, `~beta`]*(Physics:-d_[alpha](Physics:-ThreePlusOne:-gamma3_[beta, nu], [X])+Physics:-d_[nu](Physics:-ThreePlusOne:-gamma3_[beta, alpha], [X])-Physics:-d_[beta](Physics:-ThreePlusOne:-gamma3_[nu, alpha], [X]))

(2.1.7)

Ricci3[definition]

Physics:-ThreePlusOne:-Ricci3[mu, nu] = Physics:-d_[alpha](Physics:-ThreePlusOne:-Christoffel3[`~alpha`, mu, nu], [X])-Physics:-d_[nu](Physics:-ThreePlusOne:-Christoffel3[`~alpha`, mu, alpha], [X])+Physics:-ThreePlusOne:-Christoffel3[`~beta`, mu, nu]*Physics:-ThreePlusOne:-Christoffel3[`~alpha`, beta, alpha]-Physics:-ThreePlusOne:-Christoffel3[`~beta`, mu, alpha]*Physics:-ThreePlusOne:-Christoffel3[`~alpha`, nu, beta]

(2.1.8)

Riemann3[definition]

Physics:-ThreePlusOne:-Riemann3[mu, nu, alpha, beta] = Physics:-g_[mu, lambda]*(Physics:-d_[alpha](Physics:-ThreePlusOne:-Christoffel3[`~lambda`, nu, beta], [X])-Physics:-d_[beta](Physics:-ThreePlusOne:-Christoffel3[`~lambda`, nu, alpha], [X])+Physics:-ThreePlusOne:-Christoffel3[`~lambda`, upsilon, alpha]*Physics:-ThreePlusOne:-Christoffel3[`~upsilon`, nu, beta]-Physics:-ThreePlusOne:-Christoffel3[`~lambda`, upsilon, beta]*Physics:-ThreePlusOne:-Christoffel3[`~upsilon`, nu, alpha])

(2.1.9)

When working with the ADM formalism, the line element of an arbitrary spacetime metric can be expressed in terms of the differentials of the coordinates dx^mu, the Lapse , the Shift  and the spatial components of the 3D metric gamma3_ . From this line element one can derive the relation between the Lapse , the spatial part of the Shift , the spatial part of the gamma3_  metric and the g[0, j] components of the 4D spacetime metric.

For this purpose, define a tensor representing the differentials of the coordinates and an alias  dt = `#msup(mi("dx"),mn("0"))`

Define(dx[mu])

`Defined objects with tensor properties`

 

{Physics:-ThreePlusOne:-D3_[mu], Physics:-Dgamma[mu], Physics:-Psigma[mu], Physics:-ThreePlusOne:-Ricci3[mu, nu], Physics:-ThreePlusOne:-Shift[mu], Physics:-d_[mu], dx[mu], Physics:-g_[mu, nu], Physics:-ThreePlusOne:-gamma3_[mu, nu], Physics:-gamma_[i, j], Physics:-ThreePlusOne:-Christoffel3[mu, nu, alpha], Physics:-KroneckerDelta[mu, nu], Physics:-LeviCivita[alpha, beta, mu, nu], Physics:-ThreePlusOne:-Riemann3[mu, nu, alpha, beta], Physics:-ThreePlusOne:-TimeVector[mu], Physics:-ThreePlusOne:-ExtrinsicCurvature[mu, nu], Physics:-ThreePlusOne:-UnitNormalVector[mu], Physics:-SpaceTimeVector[mu](X)}

(2.1.10)

"alias(dt = dx[~0]):"

The expression for the line element in terms of the Lapse  and Shift   is (see [2], eq.(2.123))

ds^2 = (-Lapse^2+Shift[i]^2)*dt^2+2*Shift[i]*dt*dx[`~i`]+gamma_[i, j]*dx[`~i`]*dx[`~j`]

ds^2 = (-Physics:-ThreePlusOne:-Lapse^2+Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`])*dt^2+2*Physics:-ThreePlusOne:-Shift[i]*dt*dx[`~i`]+Physics:-gamma_[i, j]*dx[`~i`]*dx[`~j`]

(2.1.11)

Compare this expression with the 3+1 decomposition of the line element in an arbitrary system. To avoid the automatic evaluation of the metric components, work with the inert form of the metric %g_

ds^2 = %g_[mu, nu]*dx[`~mu`]*dx[`~nu`]

ds^2 = %g_[mu, nu]*dx[`~mu`]*dx[`~nu`]

(2.1.12)

Decompose(ds^2 = %g_[mu, nu]*dx[`~mu`]*dx[`~nu`])

ds^2 = %g_[0, 0]*dt^2+%g_[0, j]*dt*dx[`~j`]+%g_[i, 0]*dt*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`]

(2.1.13)

The second and third terms on the right-hand side are equal

op(2, rhs(ds^2 = dt^2*%g_[0, 0]+dt*%g_[0, j]*dx[`~j`]+dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`])) = op(3, rhs(ds^2 = dt^2*%g_[0, 0]+dt*%g_[0, j]*dx[`~j`]+dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`]))

%g_[0, j]*dt*dx[`~j`] = %g_[i, 0]*dt*dx[`~i`]

(2.1.14)

subs(%g_[0, j]*dt*dx[`~j`] = %g_[i, 0]*dt*dx[`~i`], ds^2 = dt^2*%g_[0, 0]+dt*%g_[0, j]*dx[`~j`]+dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`])

ds^2 = %g_[0, 0]*dt^2+2*%g_[i, 0]*dt*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`]

(2.1.15)

Taking the difference between this expression and the one in terms of the Lapse  and Shift  we get

simplify((ds^2 = dt^2*%g_[0, 0]+2*dt*%g_[i, 0]*dx[`~i`]+%g_[i, j]*dx[`~i`]*dx[`~j`])-(ds^2 = (-Physics:-ThreePlusOne:-Lapse^2+Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`])*dt^2+2*Physics:-ThreePlusOne:-Shift[i]*dt*dx[`~i`]+Physics:-gamma_[i, j]*dx[`~i`]*dx[`~j`]))

0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])

(2.1.16)

Taking coefficients, we get equations for the Shift , the Lapse  and the spatial components of the metric gamma3_

eq[1] := coeff(coeff(rhs(0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])), dt), dx[`~i`]) = 0

2*%g_[i, 0]-2*Physics:-ThreePlusOne:-Shift[i] = 0

(2.1.17)

eq[2] := coeff(rhs(0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])), dt^2)

Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0]

(2.1.18)

eq[3] := coeff(coeff(rhs(0 = (Physics:-ThreePlusOne:-Lapse^2-Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]+%g_[0, 0])*dt^2+2*dx[`~i`]*(%g_[i, 0]-Physics:-ThreePlusOne:-Shift[i])*dt-dx[`~i`]*dx[`~j`]*(Physics:-gamma_[i, j]-%g_[i, j])), dx[`~i`]), dx[`~j`]) = 0

-Physics:-gamma_[i, j]+%g_[i, j] = 0

(2.1.19)

Using these equations, these quantities can all be expressed in terms of the time and space components of the 4D metric g[0, 0] and g[i, j]

isolate(eq[1], Shift[i])

Physics:-ThreePlusOne:-Shift[i] = %g_[i, 0]

(2.1.20)

isolate(eq[2], Lapse^2)

Physics:-ThreePlusOne:-Lapse^2 = Physics:-ThreePlusOne:-Shift[i]*Physics:-ThreePlusOne:-Shift[`~i`]-%g_[0, 0]

(2.1.21)

isolate(eq[3], gamma_[i, j])

Physics:-gamma_[i, j] = %g_[i, j]

(2.1.22)

References

 
  

[1] Landau, L.D., and Lifshitz, E.M. The Classical Theory of Fields, Course of Theoretical Physics Volume 2, fourth revised English edition. Elsevier, 1975.

  

[2] Alcubierre, M., Introduction to 3+1 Numerical Relativity, International Series of Monographs on Physics 140, Oxford University Press, 2008.

  

[3] Baumgarte, T.W., Shapiro, S.L., Numerical Relativity, Solving Einstein's Equations on a Computer, Cambridge University Press, 2010.

  

[4] Gourgoulhon, E., 3+1 Formalism and Bases of Numerical Relativity, Lecture notes, 2007, https://arxiv.org/pdf/gr-qc/0703035v1.pdf.

  

[5] Arnowitt, R., Dese, S., Misner, C.W., The Dynamics of General Relativity, Chapter 7 in Gravitation: an introduction to current research (Wiley, 1962), https://arxiv.org/pdf/gr-qc/0405109v1.pdf

  

 

Examples: Decompose, gamma_

 

restartwith(Physics)NULL

Setup(mathematicalnotation = true)

[mathematicalnotation = true]

(2.2.1)

Define  now an arbitrary tensor A

Define(A)

`Defined objects with tensor properties`

 

{A, Physics:-Dgamma[mu], Physics:-Psigma[mu], Physics:-d_[mu], Physics:-g_[mu, nu], Physics:-KroneckerDelta[mu, nu], Physics:-LeviCivita[alpha, beta, mu, nu]}

(2.2.2)

So A^mu is a 4D tensor with only one free index, where the position of the time-like component is the position of the different sign in the signature, that you can query about via

Setup(signature)

[signature = `- - - +`]

(2.2.3)

To perform a decomposition into space and time, set - for instance - the lowercase latin letters from i to s to represent spaceindices and

Setup(spaceindices = lowercase_is)

[spaceindices = lowercaselatin_is]

(2.2.4)

Accordingly, the 3+1 decomposition of A^mu is

Decompose(A[`~mu`])

Array(%id = 18446744078724512334)

(2.2.5)

The 3+1 decomposition of the inert representation %g_[mu,nu] of the 4D spacetime metric; use the inert representation when you do not want the actual components of the metric appearing in the output

Decompose(%g_[mu, nu])

Matrix(%id = 18446744078724507998)

(2.2.6)

Note the position of the component %g_[0, 0], related to the trailing position of the time-like component in the signature "(- - - +)".

Compare the decomposition of the 4D inert with the decomposition of the 4D active spacetime metric

g[]

g[mu, nu] = (Matrix(4, 4, {(1, 1) = -1, (1, 2) = 0, (1, 3) = 0, (1, 4) = 0, (2, 1) = 0, (2, 2) = -1, (2, 3) = 0, (2, 4) = 0, (3, 1) = 0, (3, 2) = 0, (3, 3) = -1, (3, 4) = 0, (4, 1) = 0, (4, 2) = 0, (4, 3) = 0, (4, 4) = 1}))

(2.2.7)

Decompose(g_[mu, nu])

Matrix(%id = 18446744078724494270)

(2.2.8)

Note that in general the 3D space part of g[mu, nu] is not equal to the 3D metric gamma[i, j] whose definition includes another term (see [1] Landau & Lifshitz, eq.(84.7)).

gamma_[definition]

Physics:-gamma_[i, j] = -Physics:-g_[i, j]+Physics:-g_[0, i]*Physics:-g_[0, j]/Physics:-g_[0, 0]

(2.2.9)

The 3D space part of -g[`~mu`, `~nu`] is actually equal to the 3D metric "gamma[]^(i,j)"

"gamma_[~,definition];"

Physics:-gamma_[`~i`, `~j`] = -Physics:-g_[`~i`, `~j`]

(2.2.10)

To derive the formula  for the covariant components of the 3D metric, Decompose into 3+1 the identity

%g_[`~alpha`, `~mu`]*%g_[mu, beta] = KroneckerDelta[`~alpha`, beta]

%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics:-KroneckerDelta[beta, `~alpha`]

(2.2.11)

To the side, for illustration purposes, these are the 3 + 1 decompositions, first excluding the repeated indices, then excluding the free indices

Eq := Decompose(%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics[KroneckerDelta][beta, `~alpha`], repeatedindices = false)

Matrix(%id = 18446744078132963318)

(2.2.12)

Eq := Decompose(%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics[KroneckerDelta][beta, `~alpha`], freeindices = false)

%g_[0, beta]*%g_[`~alpha`, `~0`]+%g_[i, beta]*%g_[`~alpha`, `~i`] = Physics:-KroneckerDelta[beta, `~alpha`]

(2.2.13)

Compare with a full decomposition

Eq := Decompose(%g_[`~alpha`, `~mu`]*%g_[mu, beta] = Physics[KroneckerDelta][beta, `~alpha`])

Matrix(%id = 18446744078724489454)

(2.2.14)

Eq is a symmetric matrix of equations involving non-contracted occurrences of `#msup(mi("g"),mrow(mn("0"),mo(","),mn("0")))`, `#msup(mi("g"),mrow(mi("j"),mo(","),mo("0")))` and `#msup(mi("g"),mrow(mi("j"),mo(","),mi("i")))`. Isolate, in Eq[1, 2], `#msup(mi("g"),mrow(mi("j"),mo(","),mo("0")))`, that you input as %g_[~j, ~0], and substitute into Eq[1, 1]

"isolate(Eq[1, 2], `%g_`[~j, ~0]);"

%g_[`~j`, `~0`] = -%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0]

(2.2.15)

subs(%g_[`~j`, `~0`] = -%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0], Eq[1, 1])

-%g_[0, k]*%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0]+%g_[i, k]*%g_[`~j`, `~i`] = Physics:-KroneckerDelta[k, `~j`]

(2.2.16)

Collect `#msup(mi("g"),mrow(mi("j"),mo(","),mi("i")))`, that you input as %g_[~j, ~i]

collect(-%g_[0, k]*%g_[i, 0]*%g_[`~j`, `~i`]/%g_[0, 0]+%g_[i, k]*%g_[`~j`, `~i`] = Physics[KroneckerDelta][k, `~j`], %g_[`~j`, `~i`])

(-%g_[0, k]*%g_[i, 0]/%g_[0, 0]+%g_[i, k])*%g_[`~j`, `~i`] = Physics:-KroneckerDelta[k, `~j`]

(2.2.17)

Since the right-hand side is the identity matrix and, from , `#msup(mi("g"),mrow(mi("i"),mo(","),mi("j")))` = -`#msup(mi("γ",fontstyle = "normal"),mrow(mi("i"),mo(","),mi("j")))`, the expression between parenthesis, multiplied by -1, is the reciprocal of the contravariant 3D metric `#msup(mi("γ",fontstyle = "normal"),mrow(mi("i"),mo(","),mi("j")))`, that is the covariant 3D metric gamma[i, j], in accordance to its definition for the signature `- - - +`

gamma_[definition]

Physics:-gamma_[i, j] = -Physics:-g_[i, j]+Physics:-g_[0, i]*Physics:-g_[0, j]/Physics:-g_[0, 0]

(2.2.18)

NULL

References

 
  

[1] Landau, L.D., and Lifshitz, E.M. The Classical Theory of Fields, Course of Theoretical Physics Volume 2, fourth revised English edition. Elsevier, 1975.

Example: Redefine

   

Tensors in Special and General Relativity

 

A number of relevant changes happened in the tensor routines of the Physics package, towards making the routines pack more functionality both for special and general relativity, as well as working more efficiently and naturally, based on Maple's Physics users' feedback collected during 2016.

New functionality

 
• 

Implement conversions to most of the tensors of general relativity (relevant in connection with functional differentiation)

• 

New setting in the Physics Setup  allows for specifying the cosmologicalconstant and a default tensorsimplifier


 

Download PhysicsMaple2017.mw

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

In this file you will be able to observe and analyze how the exercises and problems of Kinematics and Dynamics are solved using the commands and operators through a very well-structured syntax; Allowing me to save time and use it in interpretation. I hope you can share and spread to break the traditional and unnecessary myths. Only for Engineering and Science. Share if you like.

In Spanish.

Kinematics_using_syntax_in_Maple.mw

Lenin Araujo Castillo

Ambassador of Maple

   It’s that time of year again for the University of Waterloo’s Submarine Racing Team – international competitions for their WatSub are set to soon begin. With a new submarine design in place, they’re getting ready to suit up, dive in, and race against university teams from around the world.

 

   The WatSub team has come a long way from its roots in a 2014 engineering project. Growing to over 100 members, students have designed and redesigned their submarine in efforts to shave time off their race numbers while maintaining the required safety and performance standards. Their submarine – “Bolt,” as it’s named – was officially unveiled for the 2017 season on Thursday, June 1st.

 

 

   As the WatSub team says, "Everything is simple, until you go underwater."

 

 

    Designing a working submarine is no easy task, and that’s before you even think about all the details involved. Bolt needs to accommodate a pilot, be transported around the world, and cut through the water with speed, to name a few of the requirements if the WatSub team is to be a serious competitor.

 

    To help squeeze even more performance out of their design, the team has been using Maple to fine tune and optimize some of their most important structural components. At Maplesoft, we’ve been excited to maintain our sponsorship of the WatSub team as they continue to find new ways to push Bolt’s performance even further.

 

 

   The 2017 design unveiling on June 1st. After adding decals and final touches, Bolt will soon be ready to race.

 

   This year, the WatSub team has given their sub a whole new design, machining new body parts, optimizing the weight distribution of their gearbox, and installing a redesigned propeller system. Using Maple, they could go deep into design trade-offs early, and come away knowing the optimal gearbox design for their submarine.

 

   In just over a month, the WatSub team will take Bolt across the pond and compete in the European International Submarine Races (eISR). Many teams competing have been in existence for well over a decade, but the leaps and strides taken by the WatSub team have made them a serious competitor for this year.

  Best of luck to the WatSub team and their submarine, Bolt – we’re all rooting for you!

With this application the components of the acceleration can be calculated. The components of the acceleration in scalar and vector of the tangent and the normal. In addition to the curvilinear kinetics in polar coordinates. It can be used in different engineers, especially mechanics, civilians and more.

In Spanish.

Kinematics_Curvilinear.mw

Lenin Araujo Castillo

Ambassador of Maple

 

 

Meta Keijzer-de Ruijter is a Project Manager for Digital Testing at TU Delft, an institution that is at the forefront of the digital revolution in academic institutions. Meta has been using Maple T.A. for years, and offered to provide her insight on the role that automated testing & assessment played in improving student pass rates at TU Delft.

 

Modern technology is transforming many aspects of the world we live in, including education. At TU Delft in the Netherlands, we have taken a leadership role in transforming learning through the use of technology. Our ambition is to get to a point where we are offering fully digitalized degree programs and we believe digital testing and assessment can play an important role in this process.

 

A few years ago we launched a project with the goal of using digital testing to drastically improve the pass rates in our programs. Digital testing helps organize testing more efficiently for a larger number of students, addressing issues of overcrowded classrooms, and high teaching workloads. To better facilitate this transformation, we decided to adopt Maple T.A., the online testing and assessment suite from Maplesoft. Maple T.A. also provides anytime/anywhere testing, allowing students to take tests digitally, even from remote locations.

 

Regular and repeated testing produces the best learning results because progressive monitoring offers instructors the possibility of making adjustments throughout the course. The randomization feature in Maple T.A. provides each student with an individual set of problems, reducing the likelihood that answers will be copied. Though Maple T.A. is specialized in mathematics, it also supports more common question types like multiple choice, multiple selection, fill-in-the-blanks and hot spot. Maple T.A.’s question randomization, possibilities for multiple response fields per question and question workflow (adaptive questions) are superior to other options. By offering regular homework assignments and analyzing the results, we gain better insight into the progress of students and the topics that students perceive as difficult. Our lecturers can use this insight to decide whether to repeat particular material or to offer it in another manner. In many courses, preparing and reviewing practice tests comprise an important, yet time-consuming task for lecturers, and Maple T.A. alleviates that burden.

 

At TU Delft, we require all first-year students to take a math entry test using Maple T.A in order to assess the required level of math. Since the assessment of the student’s ability is so heavily dependent upon qualifying tests, it is extremely important for the test to be completed under controlled conditions. In Maple T.A., it is easy to generate multiple versions of the test questions without increasing the burden of review, as the tests are graded immediately. Students that fail the entry test are offered a remedial course in which they receive explanations and complete exercises, under the supervision of student assistants. The use of Maple T.A. facilitates this process without placing additional burden on the teacher. When the practice tests and the associated feedback are placed in a shared item bank in Maple T.A., teachers are able to offer additional practice materials to students with little effort. It makes it considerably easier on us as teachers to be able to use a variety of question types, thus creating a varied test.

 

Each semester, TU Delft offers an English placement test that is taken by approximately 200 students and 50 PhD candidates, in which students are required to formulate their reasons for their program choices or research topics. It used to take four lecturers working full-time for two days to mark the tests and report the results to participants in a timely manner. The digitization of this test has saved us considerable time. The hundred fill-in-the-blank questions are now marked automatically, and we no longer have to decipher handwriting for the open questions!

 

TU Delft is not alone in its emphasis on digital testing; it has a prominent position on the agendas of many institutions in Europe and elsewhere. These institutions are intensively involved in improving, expanding and advocating the positive results from digital testing and digital learning experiences. Online education solutions like Maple T.A. are playing a key role in improving the quality of digital offerings at institutions.

In the recent years much software has undergone a change towards allowing for better sharing of documents. As is the case with other software as well, the users are no longer mainly single persons sitting in a dark corner doing their own stuff. Luckily Maplesoft has taken an important step in that direction too by introducing MapleCloud some years ago. This means that it is now possible quite easily to discuss calculations done in Maple in the classroom. One student uploads and the Teacher can find the document seconds later on his own computer connected to a Projector and show the student's solutions for the other  students in the classroom. That's indeed great! Maple is however lacking in one important aspect: It's Graphics User Interface (GUI) is not completely ready to for that challenge! I noticed that quite recently when the entire teaching staff received new netbooks: 14 inch Lenovo Yoga X1 with a resolution of 2560 x 1440 pixels. From factory defaults text zoom was set to 200%. Without it, text would be too small in all applications used on the computer. The Microsoft Office package and most other software has adapted to this new situation dealing with high variation in the users screen resolutions, but not Maplesoft:

  1. Plots and Images inserted become very small
  2. Open File dialogs and the like contain shortened text for folder names ... (you actually have to guess what the folders are)
  3. Help menus are cluttered up and difficult to read.

I show screen images of all three types below.

I know it is possible to make plots larger by using the option size, but since it relies on pixels it doesn't work when documents are shared between students and teachers. You cannot expect the receiving student/teacher to make a lot of changes in the document just to be able to read it. It will completely destroy the workflow!

Why doesn't Maplesoft allow for letting documents display proportionally on the users computer like so many other programs do? Why do it need to be in pixels? If it is possible to make it proportional, it would also solve another issue: Making prints (to a printer or to pdf) look more like they do on the screen than is the case at present.

I really hope Maplesoft will address this GUI challenge, because I am sure the issue will pile up quite rapidly. Due to higher costs, most laptops/netbooks among students don't have that high resolution compared to computer dimensions at the moment, but we already have received a few remarks from students owning such computers. Very soon those highend solution computers will dive into the consumer market and become very common.

I have mentioned this important GUI issue in the beta-testing group, but I don't think those groups really are adapted to discussions, more bug fixes. Therefore I have made this Post in the hope that some Maple users and some chief developers will comment on it!
     

Now I have criticized the Maple GUI, I also feel urged to tell in what departments I think Maple really excels:

  1. The Document-structure is great. One can produce good looking documents containing 'written math' (inactive math) and/or 'calculated math'. All-in-one! Other competting software does need one to handle things separatly.
  2. Sections and subsections. We have actually started using Maple to create documents containing entire chapters or surveys of mathematics or physics subjects, helping students to get a better overview. I am pretty sure the Workbook tool also will help here.
  3. Calculations are all connected. One can recalculate the document or parts of it, eventually using new parameters. Using Maple for performing matematical experiments. Mathematical experiments is a method entering more into the different mathematics curriculums.
  4. MapleCloud. Easy sharing of documents among students and teachers.
  5. Interactive possibilities through the Explore command and other commands. Math Apps as well.
  6. Besides that mathematical symbols can be accessed from the keyboard, they can also be accessed from palettes by less experinced users.  
  7. Good choice by Maple to let the user globally decide the size text and math is displayed in Maple - set globally in the menu Tools < Options.
  8. Maple can handle units in Physics
  9. Maple has World-Class capabilities. If you have a mathematical problem, Maple can probably handle it. You just need to figure out how.
  10. etc.

 

Small plots:

 

Shortened dialog text:

 

Cluttered help menus:

 

Regards,

Erik

 

This worksheet is designed to develop engineering exercises with Maple applications. You should know the theory before using these applications. It is designed to solve problems faster. I hope you use something that is fully developed with embedded components.

In Spanish

Vector_Force.mw

Lenin Araujo Castillo

Ambassador Of Maple

 

 

I am very pleased to announce a new user community centered around Maplesoft's online testing and assessment and courseware products. The new site is specifically for instructors and administrators currently using Maple T.A. or Möbius. This community of users are a small, specialised group who we want to bring together so they can share ideas and best practices. To find the community, go to either mapletacommunity.com or mobiuscommunity.com.

"The Maple T.A. Community has grown organically to support new developers as they pool their knowledge and queries. This has resulted in a fluid searchable structure, with answers available for all levels of question - from beginner to pushing the frontiers of what Maple T.A. has been designed to do. Our summer student interns rely on the Community as they become proficient in their question writing skills - and many have become contributors as they realise that they are in a position to teach others. Opening it out more broadly will be great in sharing good practice on a 'need to know now' basis.”

----Professor Nicola Wilkin, University of Birmingham

 

What content is in the community?

The community has many posts from active Maple T.A. and Möbius users from beginners to advanced users. The site is broken down into categories like 'Best Practices' - longer form posts that cover a broader concept in more detail and 'Quick Code snippets' that are small piece of code that you can drop straight into your question algorithms.

Much of the content is openly available and can be found by google, however there is additional content that can only be accessed by members of the community, such as the Maple T.A. school material which teaches you how to author content in Maple T.A. and Möbius.

 

Who runs the community

The community is jointly run by users based at the University of Birmingham, TU Wien, The University of Turin and TU Delft.

 

How does this fit into Mapleprimes?

It began as an offshoot of a private, internal customer forum. As this community grows, the ultimate goal is to eventually roll it into MaplePrimes proper. But this alternative site gave us the quickest way to get up and running. Maple T.A. and Möbius questions and posts are still welcome on MaplePrimes, and will continue to be monitored by Maplesoft.

 

How do I access the community?

You can find the community by going to either mapletacommunity.com or mobiuscommunity.com.

 

Where else can I get support for Maple T.A. and Mobiüs?

Official support for Maple T.A. and Möbius is provided by the wonderful Customer Success Team at Maplesoft. You can contact them at help@maplesoft.com. For other contact methods see www.maplesoft.com/support/.

 

 

I am pleased to announce the public release of Möbius, the online courseware environment that focuses on science, technology, engineering, and mathematics education. After months of extensive pilot testing at select leading academic institutions around the world, Möbius is now available to everyone for your online learning needs.

We are very excited about Möbius. As you can imagine, many of us here at Maplesoft have backgrounds in STEM fields, and we are truly excited to be working on a project that gives students a hands-on approach to learning math-based content.  You can’t learn math (or science, or engineering, or …) just by reading about it or listening to someone talk about it. You have to do it, and that’s what Möbius lets students do, online, with instant feedback.  Not only can students explore concepts interactively, but they can find out immediately what they’ve understood and what they haven’t - not a few hours after the lecture as they are reviewing their notes, not two weeks later when they get their assignments back, but while they are in the middle of learning the lesson.

During its pilot phase, Möbius was used by multiple institutions around the world for a variety of projects, such as preparing students in advance for their first year math and engineering courses, and for complete online courses.  Over one hundred thousand students have already used Möbius, and the experiences of these students and their instructors has fed back into the development process, resulting in this public release.  You can read about the experiences of the University of Waterloo, the University of Birmingham, and the Perimeter Institute for Theoretical Physics on our web site.

We are also happy to announce that Maplesoft has partnered with the University of Waterloo, one of the largest institutions in the world for STEM education, to provide institutions and professors with rich online courses and materials that enable students to learn by doing.  These Möbius courses are created by experts at the University of Waterloo for use by their own students and for their outreach programs, and will be made available to other Möbius users.  Course materials range from late high school to the graduate level, with initial offerings available soon and many more to follow.

Visit the Möbius section of our web site for lots more information, including videos, whitepapers, case studies, and upcoming user summits.

Hi everybody,

The Collatz conjecture can be used to give students a taste of a topic in Number Theory.  See the Wikipedia article for a good explaination.

https://en.wikipedia.org/wiki/Collatz_conjecture

Also, a conjecture is something that is probrably true.  Enjoy my little Maple procedure.  (in .mw and .pdf forms)

Collatz_third_time.mw

Collatz_third_time.pdf

Comments are appreciated.

Matt

 

Here is a problem from SEEMOUS 2017 (South Eastern European Mathematical Olympiad for University Students)
which Maple can solve (with a little help).

For k a fixed nonnegative integer, compute:

Sum( binomial(i,k) * ( exp(1) - Sum(1/j!, j=0..i) ), i=k..infinity );

(It is the last one, theoretically the most difficult.)

Application that allows us to measure the reliability of a group of data through a row and columns called cronbach alpha at the same time to measure the correlation of items through the pearson correlation of even and odd items. It can run on maple 18 to maple 2017. This will be useful when we are developing a thesis in the statistical part.

In Spanish

StatisticsSocialCronbachPearson.zip

Lenin Araujo Castillo

Ambassador of Maple

 

 

 

I have proposed a SE site for maple.

This will help to put maple on SE.

Please follow this site.

http://area51.stackexchange.com/proposals/107315/maple

 Update

We have moved to the next phase Commitment. Come and join us.

   Maplesoft aims to promote innovation in science, technology, engineering and math (STEM) in high school students by partnering with various organizations, and sponsoring initiatives in education, research and innovation. Every year, Maplesoft commits time, funds and people to enhance the quality of math-based learning and discovery and to encourage high school students to strengthen their math skills.

   One such organization we partner with is The Perimeter Institute, a leading centre for scientific research, training and educational outreach in foundational theoretical physics.  Maplesoft currently serves as its Educational Outreach Champion, supporting various initiatives that promote math learning and exploration. Perhaps the most popular of its student outreach program is the annual International Summer School for Young Physicists (ISSYP), a two-week camp that brings together 40 exceptional students from high schools across the globe.  Each year students receive a complimentary copy of Maple, and use the product to practice and strengthen their math skills.  The ISSYP program also uses Möbius, the comprehensive online STEM courseware platform from Maplesoft, to offer preparatory course materials to students.  Completing lessons in Möbius aid in making the summer program a more productive and dynamic experience for the students.

  

International Summer School for Young Scientists at Perimeter Institute

 

   Who Wants to Be a Mathematician is a competition organized by the American Mathematical Society (AMS) for high school students in North America. Maplesoft has been a sponsor of the contest for many years.  Maple T.A., the testing and assessment tool by Maplesoft, is used to administer the tests online, saving significant time and money for the organizers. When Maplesoft first introduced Maple T.A. to the contest, taking the competition from pen-and-paper tests to online tests, the number of contestants doubled, with about 2000 students participating in the contest. Maplesoft also donates prizes to the games in order to promote the use and love of math by high school students.  This year will be first time the competition moves international. Six students in the UK took the Round 2 qualifying test, with the use of Maple T.A., and qualified for the live, on-stage finals of the UK edition of the competition that took place at the 2017 Maths Fest in London. Maplesoft is also supporting the spread of the WWTBAM contest to Canada in 2017.


Who Wants to be a Mathematician finals

Maplesoft also sponsors two outreach initiatives in Texas A&M University.  The Summer Educational Enrichment (SEE) Math Program is a summer workshop attended by gifted middle school students. Students spend two weeks exploring ideas such as algebra, geometry, graph theory, and topology.  The University also conducts the Integral Bee every year, a math based contest for high school students.

In addition to the above key projects, throughout the year Maplesoft also sponsors and is associated with a number of other competitions, conferences, and educational initiatives. A few of these are listed below.

  • The Connecticut Science & Engineering Fair is a yearly, statewide science and engineering fair open to all 7th through 12th grade students.  An important objective of their program is to attract young people to careers in science and engineering while developing skills essential to critical thinking.
  • FIRST Robotics Competition is a high school robotics competition. Each year, teams of high school students and mentors work during a six-week period to build game-playing robots that weigh up to 120 pounds.

 

FIRSTRobotics Competition

  • ScienceExpo Conference is a student-run event that engages students with STEM-related opportunities and workshops
  • SWATposium is an annual robotics conference that brings together nearly 40 First Robotic Competition teams from both Canada and the United States for a day of guest speakers, workshops and social activities.

        

SWATposium

  • FIRST LEGO League gives elementary and middle school students and their adult coaches the opportunity to work and create together to solve a common problem.

      

FIRST LEGO League at St. Luke's School in Waterloo

   Maplesoft’s objective of these sponsorships is to support those who inspire and channel young minds to be STEM focussed. By engaging them in exciting contests and programs the hope is that they build science, engineering, and technology skills at a young age and grow to be innovators and technology leaders of tomorrow.

The distance from the point to the surface easily calculated using the NLPSolve of Optimization package. If the point is not special, we will find for it a point on the surface, the distance between these two points is the shortest between the selected point and the surface.
Two examples:  the implicit surface and the parametric surface.
To test, we restore the normals from the  calculated  points (red) by using analytical equations.
DISTANCE_TO_SURFACE.mw

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