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MaplePrimes Posts are for sharing your experiences, techniques and opinions about Maple, MapleSim and related products, as well as general interests in math and computing.

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  • Every four years, the world comes together to watch one of the most anticipated sporting events in history: the FIFA World Cup.

    Behind all the anticipation, venue planning, and media fanfare, there are many artists and researchers who devote themselves to designing a new FIFA World Cup ball to be rolled out for the public eye (pun intended).

    This post presents an overview of the geometric ideas behind the design of the FIFA 2026 "Trionda" ball, using Maple to visualize and explore these concepts in depth. The ideas presented here were inspired by this Scientific American Article. For more information and facts about the 2026 Trionda ball, as well how the shape of the ball impacts play on the pitch, I suggest you check it out!

    FIFA ball designs are often inspired by one of the 5 Platonic solids. A Platonic solid is a convex polyhedron with each face being the same regular polygon with the same number of faces meeting at each corner.

    This year, the Trionda ball was constructed from the simplest of these shapes, the tetrahedron, consisting of 4 triangles, with 3 faces meeting at each corner. Of the five Platonic solids, this shape has the fewest faces, making it the least sphere-like. Turning such a simple polyhedron into a smooth ball is therefore a surprisingly challenging geometric problem.

      

     

    So how can we turn our pointy tetrahedron into something that rolls? Rather than trying to transform the entire tetrahedron at once, we can start by redesigning a single triangular face. The goal is to create a curved triangle that will fit perfectly with three identical copies of itself while covering the surface of a sphere.

     

     
     
    Notice that in the above diagrams, the transformed triangle has the same area as the original triangle. Although the edges have been reshaped, no area is added or removed, only redistributed. Preserving the area ensures that four identical curved panels can still cover the sphere completely without leaving gaps or overlapping.
     
    Now that we know how to change one face of the tetrahedron, we need to perform the same sort of transformation (from a triangle to a curved tile), on the surface of a sphere. To start, we can inscribe the tetrahedron inside the sphere, like this:
    From here, we can project the edges of the tetrahedron onto the sphere, creating six great-circle-arcs (also known as geodesics) as shown in the diagram below.
    Each region enclosed by these geodesics corresponds to one triangular face of the tetrahedron within the sphere. By transforming each geodesic triangle into a smooth curved tile (using a bit of AI help), we create a tiling of the surface similar to that of the 2026 FIFA World Cup ball!
    Because each curved tile maintains the area of the geodesic-generated region, the four panels form a complete tiling of the sphere. 
     
    I would have liked to find a better function between the points on the sphere that resemble the actual Trionda ball more accurately but didn't get the chance to dive into that. If you want to take on the challenge and are successful, please reply in the comments.
     
    To see the Maple Worksheet used to generate these diagrams, check out: Trionda Ball Worksheet

    Hi Maple community and others,

    I'm very proud to present my code.

    Sequences are fun,
    for those who know, about them

    consider Fermat numbers, of the form,
    F(n) = (2^(2^n)) + 1.
    goes like

    3, 5, 17, 257, 65537, 4294967297, 18446744073709551617, 
    340282366920938463463374607431768211457, ...

    in oeis.org database at
    https://oeis.org/A000215 .


    Similarly we can have base 3,

    B(a) = (3^(3^a)) + 1.
    goes like, this,
    4,28,19684, ...
    online, in database, with Universal Resource Location (URL)
    https://oeis.org/A129290

    There could also be base 4, that grows even faster
     

    double_exponential_2_and_3_and_4.mw

    That is all that I have, for now.

    Thank you for this free forum.
    regards,
    Matt

     

    Hi Maple community, and all,

    Here is a little Maple worksheet, shoing an interesting property of prime numbers.

    Numerical evidence supports Andreca's conjecture.

    see    

    _Andricas_conjecture.mw

    good fun

    see, also
    Andrica's Conjecture -- from Wolfram MathWorld
    Enjoy
    regards,
    Matt

    PS online at https://MattAnderson.fun/

    PPS Have a good day, everybody.

    Last week, we launched the Maplesoft Math Success Platform. 
     

    Maplesoft Math Success Platform


    This launch reflects a lot of conversations I’ve had over the past year with educators and institutions about what it means to teach and learn math in the age of AI. 

    At first, many of those conversations were about visibility. If students were completing homework, quizzes, and other assessments with help from AI, those results became harder to interpret. Did students understand the work, or had they copied down a solution that made sense in the moment without building the understanding needed to do something similar on their own?

    That visibility still matters. 

    Over time, though, those conversations led to a more nuanced conclusion. The question is not simply how we prevent students from taking shortcuts. It is how we help them develop the mathematical judgment, intuition, and critical thinking they will need in a world where AI is part of how they learn and work. 

    In some ways, that has become even more important. When answers are easy to generate, students need to be able to test ideas, recognize when something does not make sense, explain their reasoning, and trust their own thinking. 

    That is why I am proud to share the launch of the Maplesoft Math Success Platform. 

    Built on Maple, the platform brings together our math technology and extends it with analytics, AI-driven insights, targeted resources, and content expertise to help institutions support math learning in a more complete way. 

    It gives instructors and learning support teams better insight into where students are struggling, supports the creation of better questions and learning experiences, helps students move beyond the answer, and helps institutions respond to a world where AI is now part of how students practice, study, and get help. 

    You can learn more about the Maplesoft Math Success Platform on our website.

    We also wrote more about the thinking behind this launch in our new whitepaper, Math Education in the Age of AI: From Grading Answers to Understanding Student Progress. It looks at why math education needs a new approach in the age of AI: one that helps instructors ask better questions, create learning experiences that build understanding, and use learning signals to see where students need support.

    Math success in the age of AI requires a new approach

    I’d love to hear what you think. How are you seeing AI change the way students learn, practice, and get help in math? And what kinds of tools or approaches do you think will be most important as math education continues to evolve?

     

    Little bit of a followup on the "Series Solutions of ODEs in Maple" online seminar.

    According to Mathematical Methods for Physicists, 7th Edition by Arfken, Weber and Harris,

    Pages 343-345,

    Singular points are classified as regular or irregular

    Irregular points are called essential singularies.

    They show how to apply these to famous differential equations in Quantum Mechanics and other physical applications (examples given in Farlow's Partial Differential Equations for Scientists and Engineers).

    In Section 12.1 of Mathematical Methods for Physicists, the complex series Laurent expansion (chapter 11 of the book) is applied to generalized to the complex plane (see Saff and Snider Fundamentals of Complex Analysis for Mathematics, Science and Engineering, 2nd Edition).  Not too sure how Maple handles contour integrals though.

    It seems that a regular point is the same as a ordinary point, as per Elementary Differential Equations and Boundary Value Problems, 8th Edition by Boyce and DiPrima, Chapter 5.

    A little while ago, I created a video, Engaging and Enlightening Students with Maple Visualizations, that showed a sample of Maple visualizations that would be helpful in teaching math. Doing that allowed me to get reacquainted with some of Maple's plotting features that I hadn't used for a while. As a result, I made a second instructional video for my Maple tips series, Animating a Polyhedron in Maple

    I chose this topic because I thought it would show several features in Maple that might not be known to all users. I list them below and encourage you to try them out.

    • The plots:-polyhedraplot command allows you to create a 3-D plot of a polyhedron, including one of 138 polyhedra that Maple knows about.

    • The list of named polyhedra available can be obtained by calling the plots:-polyhedra_supported command.

    • The viewpoint option, which allows you to create an animation by varying the viewpoint through a 3D plot, can be used to rotate the polyhedron.

    • Finally, the Export feature allows you to save the plot animation as an animated GIF.

     

    Recently @salim-barzani asked a question about a paper that involved analysing the different types of roots of polynomials. The appendix in that paper gave the example of the roots of x^4+x^2*e[2]+x*e[1]+e[0]using the analysis in Lu et al, "A complete discrimination system for polynomials", Science in China (Ser. E), 39 (1996) 628-646. The analysis uses the discriminant sequence and extensions. Maple provides this through RegularChains:-ParametricSystemTools:-DiscrminantSequence. For example for this polynomial we find there is a real root of multiplicity 2 and a complex conjugate pair when D__2*D__3 < 0 and D__4 = 0 where the D__i are the ith entries in the discriminant sequence [1, -e[2], -2*e[2]^3+8*e[0]*e[2]-9*e[1]^2, 16*e[0]*e[2]^4-4*e[1]^2*e[2]^3-128*e[0]^2*e[2]^2+144*e[0]*e[1]^2*e[2]-27*e[1]^4+256*e[0]^3].

     

    The problem with these conditions is that they are in terms of the D__i and not directly in terms of the e__i parameters. One can derive these conditions and then solve them to find the conditions on the parameters, but Maple has various routines in the RegularChains, RootFinding:-Parametric and SolveTools packages that directly find conditions on parameters to find when there are specified numbers of real or complex roots for polynomial systems. So this post is my attempt to use these tools to find the conditions on the parameters of the above polynomial that give various types of roots. One immediate difficulty is that generally these routines count distinct roots irrespective of multiplicity, and so some indirect analysis is required. There are several different types of commands and analyses that could be used, and my choices here are more to do with my learning experience than an optimum analysis.

     

    The first conclusion is that it is possible, although RealComprehensiveTriangularize did not work as I expected when asking for zero real roots (see cases (a) and (b)) (bug?). Assuming it had worked, RealComprehensiveTriangularize could cover all the cases here, though that will not be true for higher-degree polynomials with more parameters. There doesn't seem to be an obvious systematic way of doing this analysis, which is a downside. Another downside is the large number of subcase conditions, which look as if they could be combined into fewer subcases. CellDecomposition works well for cases without multiplicity.


    Main worksheet [not all is displayed below]:

    Download RootAnalysis4.mw

    restart

    with(RegularChains); with(ParametricSystemTools); with(RootFinding:-Parametric)

    Consider the following polynomial in x with the three real parameters e[0], e[1], e[2]. We would like to know the conditions on these parameters that lead to different numbers of real and complex-conjugate pairs of roots of different multiplicities.

    p := x^4+x^2*e[2]+x*e[1]+e[0]

    x^4+x^2*e[2]+x*e[1]+e[0]

    Consider first how many cases there are. We can set this up as a combinatorial problem in the combstruct package.

    sys := {C = Atom, R = Atom, realrts = Set(multiplereal), rts = Prod(realrts, complexrts), complexpr = Prod(C, C), complexrts = Set(multiplecomplex), multiplecomplex = Sequence(complexpr, card > 0), multiplereal = Sequence(R, card > 0)}

    Draw := proc (q) options operator, arrow; eval(q, {Epsilon = NULL, Prod = `[]`, Set = (proc () options operator, arrow; args end proc), Sequence = `*`}) end proc

    For a degree 4 polynomial there are 9 different cases to consider. Here [C, C] means a (non-real) complex-conjugate pair of roots and R means a real root; the exponents indicate the multiplicities.

    all := combstruct:-allstructs([rts, sys], size = degree(p, x)); nops(%); `~`[Draw](all)

    9

    [[[C, C]^2], [[C, C], [C, C]], [R^2, [C, C]], [R^4], [R, R, [C, C]], [R^2, R^2], [R^3, R], [R, R, R^2], [R, R, R, R]]

    These are (in order)
    (a) A duplicate pair of complex-conjugate roots

    (b) Two distinct pairs of complex-conjugate roots

    (c) A real root of multiplicity 2 and a pair of complex-conjugate roots

    (d) A real root of multiplicity 4

    (e) Two distinct real roots of multiplicity 1 and a complex-conjugate pair

    (f) Two distinct real roots each of multiplicity 2

    (g) A real root of multiplicity 3 and a real root of multiplicity 1

    (h) Three distinct real roots, of multiplicities 2, 1, and 1

    (i) Four distinct real roots of multiplicity 1

    Declare the variables first and parameters last. np is the number of parameters. Use the suggested order.

    vp := SuggestVariableOrder([p = 0], [x]); R := PolynomialRing(vp); np := nops(`minus`({vp[]}, {x}))

    [x, e[0], e[1], e[2]]

    polynomial_ring

    3

    Define derivative polynomials. p2 = 0 when there is a root of multiplicity 2 or more; p3 = 0 when there is a root of multiplicity 3 or more and p4 = 0when there is a root of multiplicity 4.

    p2 := diff(p, x); p3 := diff(p2, x); p4 := diff(p3, x)

    4*x^3+2*x*e[2]+e[1]

    12*x^2+2*e[2]

    24*x

    Discriminant is zero if and only if there are repeated roots.

    Delta := discrim(p, x)

    16*e[0]*e[2]^4-4*e[1]^2*e[2]^3-128*e[0]^2*e[2]^2+144*e[0]*e[1]^2*e[2]-27*e[1]^4+256*e[0]^3

    (d) A real root of multiplicity 4

     

    This is perhaps the simplest case and can be done using RealComprehensiveTriangularize. Specifying np = 3 means use the last 3 variables in the PolynomialRing as parameters. The argument 1 means we want the cases where there is one distinct real root. We specify that all of p, p2, p3, p4 are zero so that the 1 real root is the common root of these polynomials, i.e., is a root on multiplicity 4. (I find the cadcell output a little easier to use, but it is not critical.)

    rct := RealComprehensiveTriangularize({p = 0, p2 = 0, p3 = 0, p4 = 0}, np, R, 1, output = cadcell); Display(rct, R)

    PiecewiseTools:-Is, "Wrong kind of parameters in piecewise"

    This means that the conditions on the parameters to get a single real root of multiplicity 4 are

    conds := Info(rct[2][1][1], R)

    [e[2] = 0, e[1] = 0, e[0] = 0]

    and that the polynomial to solve to find this root under these conditions is

    poly := Info(rct[1][][2], R)

    [x = 0]

    which we can check:

    eval(p, conds); solve(%, x)

    x^4

    0, 0, 0, 0

    (g) A real root of multiplicity 3 and a real root of multiplicity 1

       

    (f) Two distinct real roots each of multiplicity 2

       

    (i) Four distinct real roots of multiplicity 1

       

    (h) Three distinct real roots, of multiplicities 2, 1, and 1

       

    (e) Two distinct real roots of multiplicity 1 and a complex-conjugate pair

       

    (c) A real root of multiplicity 2 and a pair of complex-conjugate roots

       

    (b) Two distinct pairs of complex-conjugate roots

       

    (a) A duplicate pair of complex-conjugate roots

     

    Here we want multiplicity 2 but no real roots. The discriminant is expected to be zero, but in most cases is not.

    rct := RealComprehensiveTriangularize({p = 0, p2 = 0, p3 <> 0, p4 <> 0}, np, R, 0, output = cadcell); nops(rct[2]); Display(rct[2][1 .. 4], R)

    40

    [[PIECEWISE([e[0] < RootOf(256*_Z^3-128*e[2]^2*_Z^2+(16*e[2]^4+144*e[1]^2*e[2])*_Z-4*e[1]^2*e[2]^3-27*e[1]^4, index = real[1]), ``], [e[1] < -(2/9)*(-6*e[2]^3)^(1/2), ``], [e[2] < 0, ``]), []], [PIECEWISE([RootOf(256*_Z^3-128*e[2]^2*_Z^2+(16*e[2]^4+144*e[1]^2*e[2])*_Z-4*e[1]^2*e[2]^3-27*e[1]^4, index = real[1]) < e[0], ``], [e[1] < -(2/9)*(-6*e[2]^3)^(1/2), ``], [e[2] < 0, ``]), []], [PIECEWISE([e[0] < -(1/12)*e[2]^2, ``], [e[1] = -(2/9)*(-6*e[2]^3)^(1/2), ``], [e[2] < 0, ``]), []], [PIECEWISE([e[0] = -(1/12)*e[2]^2, ``], [e[1] = -(2/9)*(-6*e[2]^3)^(1/2), ``], [e[2] < 0, ``]), []]]

    Consider one of the cases with an equality for e[0], suggesting a zero discriminant.
    Find a sample point satisfying the conditions, and see what the roots are like

    j := 37; cell := rct[2][j][1]; conds := Info(cell, R); pts := Info(SamplePoints(cell, R), R)[1]; `~`[is](eval(conds, pts))

    37

    cad_cell

    [0 < e[2], e[1] = 0, e[0] = (1/4)*e[2]^2]

    [e[0] = 1/16, e[1] = 0, e[2] = 1/2]

    [true, true, true]

    We find two complex roots of multiplicity 2, which are complex conjugates, as expected

    eval(p, pts); solve(%, x)

    x^4+(1/2)*x^2+1/16

    (1/2)*I, -(1/2)*I, (1/2)*I, -(1/2)*I

    Check that discriminant is zero.

    eval(Delta, pts)

    0

    But, for example, the first cell does not have the discriminant zero, and does not give a correct result.

    j := 1; cell := rct[2][j][1]; conds := Info(cell, R); pts := Info(SamplePoints(cell, R), R)[1]; `~`[is](eval(conds, pts))

    1

    cad_cell

    [e[2] < 0, e[1] < -(2/9)*(-6*e[2]^3)^(1/2), e[0] < RootOf(256*_Z^3-128*e[2]^2*_Z^2+(16*e[2]^4+144*e[1]^2*e[2])*_Z-4*e[1]^2*e[2]^3-27*e[1]^4, index = real[1])]

    [e[0] = 1/2, e[1] = -3/2, e[2] = -1/2]

    [true, true, true]

    We find a complex conjugate pair and two distinct real roots, which is not expected for this case.

    eval(p, pts); fsolve(%, x, complex)

    x^4-(1/2)*x^2-(3/2)*x+1/2

    -.7473459056-.9001675303*I, -.7473459056+.9001675303*I, .3077440660, 1.186947745

    The discriminant is indeed nonzero.

    eval(Delta, pts)

    -3073/16

    We did not yet find the conditions for this case. We can ask for the conditions for different numbers of complex roots (complex in this context includes real).

    cmplx := ComplexRootClassification([p], np, R)

    [[constructible_set, 1], [constructible_set, 2], [constructible_set, 3], [constructible_set, 4]]

    We are interested in the conditions for exactly two distinct roots, which is found from the second constructible_set. There are two subcases.

    Display(cmplx[2][1], R)

    PIECEWISE([12*e[0]+e[2]^2 = 0, ``], [27*e[1]^2+8*e[2]^3 = 0, ``], [e[2] <> 0, ``]), PIECEWISE([4*e[0]-e[2]^2 = 0, ``], [e[1] = 0, ``], [e[2] <> 0, ``])

    Consider the second case

    case2 := Info(cmplx[2][1], R)[2]

    [[4*e[0]-e[2]^2, e[1]], [e[2]]]

    solve(case2[1], {e[0], e[1]}); q1 := eval(p, %); rts2 := [solve(%, x)]

    {e[0] = (1/4)*e[2]^2, e[1] = 0}

    x^4+x^2*e[2]+(1/4)*e[2]^2

    [(1/2)*(-2*e[2])^(1/2), -(1/2)*(-2*e[2])^(1/2), (1/2)*(-2*e[2])^(1/2), -(1/2)*(-2*e[2])^(1/2)]

    We saw this before when e[2]<0 as case (f) with real roots of multiplicity 2. Now, for e[2]>0 we indeed have two duplicate pairs of complex conjugate roots

    `assuming`([simplify(rts2)], [e[2] > 0])

    [((1/2)*I)*2^(1/2)*e[2]^(1/2), -((1/2)*I)*2^(1/2)*e[2]^(1/2), ((1/2)*I)*2^(1/2)*e[2]^(1/2), -((1/2)*I)*2^(1/2)*e[2]^(1/2)]

    Consider the first case

    case1 := Info(cmplx[2][1], R)[1]

    [[12*e[0]+e[2]^2, 27*e[1]^2+8*e[2]^3], [e[2]]]

    ans1 := {solve(case1[1], {e[0], e[1]}, explicit)}; q11 := eval(p, ans1[1]); rts11 := [solve(%, x, explicit)]

    {{e[0] = -(1/12)*e[2]^2, e[1] = -(2/9)*(-6*e[2])^(1/2)*e[2]}, {e[0] = -(1/12)*e[2]^2, e[1] = (2/9)*(-6*e[2])^(1/2)*e[2]}}

    x^4+x^2*e[2]-(2/9)*x*(-6*e[2])^(1/2)*e[2]-(1/12)*e[2]^2

    [(1/6)*(-6*e[2])^(1/2), (1/6)*(-6*e[2])^(1/2), (1/6)*(-6*e[2])^(1/2), -(1/2)*(-6*e[2])^(1/2)]

    The rts11 subcase polynomial q11 must have real coefficients and therefore only applies for e[2]<0. The roots are real with multiplicity 3 and multiplicity 1 and this case is just case (g) above. The rts12 subcase polynomial q12 (below) also requires e[2]<0 and corresponds to case (g), but with signs reversed.

    q12 := eval(p, ans1[2]); rts12 := [solve(%, x, explicit)]

    x^4+x^2*e[2]+(2/9)*x*(-6*e[2])^(1/2)*e[2]-(1/12)*e[2]^2

    [(1/2)*(-6*e[2])^(1/2), -(1/6)*(-6*e[2])^(1/2), -(1/6)*(-6*e[2])^(1/2), -(1/6)*(-6*e[2])^(1/2)]

    Therefore the rts2 case is the solution for case (a); the cell37 example was a special case of this. In fact if we have a duplicate pair of complex-conjugate roots, the polynomial must be a pefect square, as we see it is

    factor(q1)

    (1/4)*(2*x^2+e[2])^2

    NULL

    Download RootAnalysis5.mw

     

    A note on what I've been working on for the past while. Some of you may have seen the announcement on LinkedIn yesterday; this is for the home audience.

    The question I've been chasing is the one that's underneath the Physics package, the dsolve / pdsolve formal methods and heuristics, the advanced Mathematical Functions and FunctionAdvisor, and most of what I've written for Maple over the years. How can mathematicians and physicists speed up significantly their work using Computer Algebra Systems (CAS) and at the same time trust the result a computer hands back? The new chapter is what happens when AI sits between the human and the CAS, and the answer to that, in my view, turns out to be a much harder problem than the AI hype suggests.

    Why? Because AI is increasingly the driver of computational mathematics in research, engineering, and education. And the unsolved problem isn't whether AI can do mathematics. It can. The problem is that an incorrect AI result arrives with the same confidence as a correct one.

    On 100 challenging problems of undergraduate mathematics we tested, six independent state-of-the-art AIs returned mathematically equivalent answers on only 21% of them, and even within a single AI, repeated runs disagreed with themselves on 3% to 57% of the problems (details). The gap this validation crosses, between probabilistic inference and certified mathematical computation, is epistemological, not technological. It won't close with more training data. It needs validation across multiple AIs and multiple CAS, with no single engine having the final word.

    ExaktAI aims to address that gap. It guides AI through mathematical computation, validates each step against Maple and Mathematica, and automatically generates and opens a corresponding CAS document where the validation can be audited and reproduced for every step, and where one can continue working on the problem. The goal: AI-mathematics that is validated, with the human in the loop.

    ExaktAI is now well developed (TRL 6: System prototype demonstration in a simulated environment, on the ISED / Innovative Solutions Canada TRL scale). At the end an image. A Beta is scheduled for late summer / fall 2026; details at exaktai.ai.

    In summary: ExaktAI is my present, and if you work on AI for mathematics and computer algebra, or the validation problem for AI, I'd love to hear your perspective.



    Edgardo S. Cheb-Terrab
    ExaktAI
    Research Fellow Emeritus at Maplesoft.

    Hi MaplePrimes, and all,

    Here is a new, to me, set of numbers
    defined by ,
    the first three numbers are {1,2,3}
    and then, 
    the next number is the sum of the three 
    previous numbers,
    so,
    {1,2,3,6,11,20, ... }
    but can only calculate a finite number of numbers
    the, so called, Tribonacci numbers
    could start with {0,1,0}
    see online
    https://oeis.org/A001590

    and
    triple_recursive_sequence_simple_first.mw

    triple_recursive_sequence_simple_first.pdf

    regards,
    Matt
     

    The new ribbon style user interface of recent Maple versions is well structured and visually much more appealing than the former user interface. Great for new users. However, I do not use the new Maple version for productive work because it is considerably slower to use: Much more clicks and mouse movements are involved than before, which breaks the flow.

    To improve this situation, I thought about customizing the quick access toolbar with menu items that I need all the time. With Maple 2026 this suggestion has become a less viable solution because the quick access toolbar shrunk in size and moved to a screen location with low mouse activity (to get there fast, the mouse has to move back and forth like Speedy Gonzales). The tiny buttons in the toolbar are hard to distinguish and to hit in one go (a golfer might say “it's rare like an eagle”). If you disagree, try to write text and switch to non-executable math (to enter a symbol) and switch back to text and continue writing. Do the same with the former user interface (e.g. Maple 2024) and compare.

    As a new suggestion I thought about adding a new tab "My Tab" to the ribbon that is customizable by the user. Here is what I would pick from the current ribbon items

    (A subset from 4 out of 10 tabs: The Home, Insert, Edit and Help tab. The latter is less important)

    I would probably also add these two items

    although they do not fully replace the former buttons from the contextual tool bar

    .

    I use the above buttons from the former user interface allot in text passages to toggle between text and non-executable math. They are also useful to change the input mode of an empty document block (instead of inserting a new line with the desired input mode and deleting unwanted input lines). These buttons were introduced with Maple 2021 to improve usability, now they are gone and with it the ease of integrating math into text. With Maple 2026, I have to go back to using F5, which now “toggles” between three states (with the drawback that now in 1-D Math no indication of the state of the input mode is available on the user interface).

    The above selection of menu items is my selection to work efficiently on textbook style Maple documents composed of explanatory text passages (including non-executable math) and Maple input and output. Other users would probably customize differently according to their needs.

    A final remark about the undo function. Most software has undo on a top level. I do not understand why undo is not in the current quick access toolbar.

    I strongly hope for productivity improvements that I can stop using Maple 2025.2 for Screen Readers (having the former user interface). Please do something to reduce mouse movements and clicks of frequently used interface functions. There is too much tab switching between the 3 most important tabs (Home, Insert, Edit) and too little functionality and ease of use of the quick access toolbar.

    I would be interested to know which menu items other users would select.

    Hi again Maple community, and others,

    want to share
    tiwn_and_cousin_prime_numbers.mw
    tiwn_and_cousin_prime_numbers.pdf
    (spelling error in file name)

    ~

    just want to share,
    some successful code

    The lesser of the twin primes are listed
    {3,5,11,17,29,41,59,71}
    https://oeis.org/A001359
    Prime numbers p such that p+2 is also a prime number

    also, the lesser of the cousin primes are listed
    {3,7,13,19,37,43,67,79,97}
    https://oeis.org/A023200
    prime numbers p such that p+4 is also a prime number

    good fun

    also, my webpage has more details
    https://mattanderson.fun
    okay

    regards,
    Matt

    Would it be possible to include the file path in $File for the proposed header/footer insertions.

    Thanks in advance

    Peter

    I am very pleased to announce the publication of my new book written together with Nic Fillion, "Perturbation Methods Using Backward Error", which uses Maple heavily throughout.

    You can find it at

    the SIAM bookstore

    and I hope that you find it useful and interesting.

    You can also find a paper in Maple Transactions, written with Michelle Hatzel, that explains how we generated the image that was chosen for the cover.  Exploring Cover Designs for an Upcoming Book  In the end, the SIAM design people chose a different one than we had thought, but they did pick one of the ones we generated!  

    This was fun to do.

     

    a rainbow-hued image with many levels; two dark blue spots connected by a horizontal and a vertical blue line from each that intersect; alarming red spots in the upper and lower left corner
     

    Over the past few months, I've created a number of short videos. My intention is to help people use Maple more effectively. I occasionally give workshops introducing Maple and its programming language, and many of the topics come from questions I get from the participants. 

    These can be found on our Youtube channel. Here are the ones posted so far.

    What is a Workbook?
    Creating a Workbook
    How to Customize Your Maple Settings with the Options Dialog
    What is Maple Transactions?
    How to Submit an Article to Maple Transactions
    Quotation Marks in Maple
    Using Single Quotes to Prevent Evaluation
     

    If you find these helpful and have suggestions for future videos, please leave a comment, thanks!

    > kernelopts(version);
    Maple 2026.0, X86 64 LINUX, Apr 28 2026, Build ID 2011354

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