Greetings to all.

This past year I have on occasion shared mathematical adventures with cycle index computations and Maple, e.g. at these links:

• Fascinating cycle indices with Maple
• The enumeration of non-isomorphic graphs
• Automorphisms of the Petersen Graph.

Befitting the season I am sending another post to continue this series of cycle index computations. I present two Maple implementations of Power Group Enumeration as described by Harary and Palmer in their book "Graphical Enumeration" and by Fripertinger in his paper "Enumeration in Musical Theory." It was a real joy working with Maple to implement the computational aspects of their work, i.e. the Power Group Enumeration Theorem. Moreover the resulting software is easy to read, simple and powerful and has a straightforward interface, taking advantage of many different capabilities present in Maple.

The problem I am treating is readily described. Consider a cube in 3 space and its symmetries under rotation, i.e. rigid motions. We ask in how many different ways we may color the edges of the cube with at most N colors where all colors are completely interchangable, i.e. have the symmetric group acting on them in addition to the edge permutation group of the cube. At the following Math Stackexchange Link  I have posted the Maple code to implement the algorithms / formulas of Harary / Palmer / Fripertinger to solve this problem. The reader is invited to study and test these algorithms. It seems to me an excellent instance of computational combinatorics fun.

To conclude I would like to point out that these algorithms might be candidates for a Polya Enumeration Theorem (PET) package that I have been suggesting for a future Maple release at the above posts, the algorithms being of remarkable simplicity while at the same time providing surprisingly sophisticated combinatorics and enumeration methods.

Season's greetings!

Marko Riedel

Hi

It's been 3+ months since we launched this new, experimental, Maple Physics: Research & Development webpage, containing fixes and new developments around the clock made available to everybody. Today we are extending this experience to Differential Equations and Mathematical functions, launching the Maple Differential Equations and Mathematical Functions: Research & Development Maplesoft webpage. Hey!

With these pages we intend to move the focus of developments directly into the topics people are actually working on. The experience so far has been really good, putting our development at high RPM, an exciting roller-coast of exchange and activity.

As with the Research version of Physics, when suggestions about DEs or Mathematical Functions are implemented or issues are fixed, typically within a couple of days when that is possible, the changes will be made available to everybody directly in this new Maplesoft webpage. One word of clarification: for now, these updates will not include numerical ODE or numerical PDE solutions nor their numerical plotting. Sorry guys. One step at a time :)

This first update today concerns Differential Equations: dsolve and pdsolve can now handle linear systems of equations also when entered in Vector notation (Matrices and Vectors), related to a post in Mapleprimes from October/29. Attached is a demo illustrating the idea.

Everybody is welcome to bring suggestions and post issues. You can do that directly in Mapleprimes or writing to physics@maplesoft.com. While Differential Equations and Mathematical Functions are two areas where the Maple system is currently more mature than in Physics, these two areas cover so many subjects, including that there are the Research and the Education perspectives, that the number of possible topics is immense. 

DEsAndMathematicalFu.pdf   DEsAndMathematicalFu.mw

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

Thу post is the answer to  http://www.mapleprimes.com/questions/200355-Clever-Cutter-3?reply=reply

This message contains two procedures . The first procedure called  LargestIncircle  symbolically looks for the largest circle inscribed in a convex polygon . Polygon must be specified as a list of lists of its vertices . If the polygon does not have parallel sides , the problem has a unique solution , otherwise may be several solutions . It is easy to prove that there is always a maximum circle that touches three sides of the polygon . Procedure code based on this property of the optimal solution.

The second procedure called  MinCoveringCircle  symbolically seeking smallest circle that encloses a given set of points. The set of points can be anyone not necessarily being vertices of a convex polygon. Procedure code based on the following geometric properties of the optimal solution , which can easily be proved :

1) The minimum covering circle is unique.

2) The minimum covering circle of a set Set can be determined by at most three points in  Set  which lie on the boundary of the circle. If it is determined by only two points, then the line segment joining those two points must be a diameter of the minimum circle. If it is determined by three points, then the triangle consisting of those three points is not obtuse.

Code of the 1st procedure:

restart;

LargestIncircle:=proc(L::listlist)

local n, x, y, P, S, T, Eqs, IsInside, OC, Pt, E, R, t, Sol, P0, R1, Circle;

uses combinat, geometry;

n:=nops(L); _EnvHorizontalName := x; _EnvVerticalName := y;

P:=[seq(point(A||i, L[i]), i=1..n)];

if nops(convexhull(P))<n then error "L should be a convex polygon" fi;

S:={seq(line(l||i,[A||i, A||(i+1)]), i=1..n-1), line(l||n,[A||n, A||1])};

Eqs:=map(lhs,{seq(Equation(l||i), i=1..n)});

T:=choose({seq(l||i, i=1..n)}, 3);

IsInside:=proc(Point, OC, Eqs)

convert([seq(is(eval(Eqs[i], {x=Point[1], y=Point[2]})*eval(Eqs[i], {x=OC[1], y=OC[2]})>0), i=1..n)], `and`);

end proc;

OC:=[add(L[i,1], i=1..n)/n, add(L[i,2], i=1..n)/n]; 

R:=0; point(Pt,[x,y]);

   for t in T do

     solve([distance(Pt,t[1])=distance(Pt,t[2]),      distance(Pt,t[2])=distance(Pt,t[3])],[x,y]);

     Sol:=map(a->[rhs(a[1]), rhs(a[2])], %);

     P0:=op(select(b->IsInside(b, OC, Eqs), Sol)); if P0<>NULL then R1:=distance(point(E,P0),      t[1]);

     if convert([seq(is(R1<=distance(E, i)), i=S minus t)], `and`) and is(R1>R) then R:=R1;      Circle:=[P0, R] fi; fi;

   od; 

Circle; 

end proc:

Code the 2nd procedure:

MinCoveringCircle:=proc(Set::{set, list}(list))

local S, T, t, d, A, B, C, P, R, R1, O1, Coord, L;

uses combinat, geometry; 

if type(Set, list) then S:=convert(Set, set) else S:=Set fi;

T:=choose(S, 2);

   for t in T do

      d:=simplify(distance(point(A, t[1]), point(B, t[2]))); midpoint(C, A, B);

      if convert([seq(is(distance(point(P, p), C)<=d/2), p in S minus {t[1], t[2]})], `and`)   then return            [coordinates(C), d/2] fi;

   od;

T:=choose(S, 3);

R:=infinity;

   for t in T do

      point(A, t[1]); point(B, t[2]); point(C, t[3]);

      if is(distance(A, B)^2<=distance(B, C)^2+distance(A, C)^2 and        distance(A,C)^2<=distance(B,        C)^2+distance(A, B)^2 and distance(B, C)^2 <= distance(A, C)^2 + distance(A, B)^2) then

      circle(c, [A,B,C],'centername'=O1); R1:=radius(c); Coord:=coordinates(O1);

      if convert([seq(is(distance(point(P, p), O1)<=R1), p in S minus {t[1], t[2], t[3]})], `and`) and is(R1<R) then    R:=R1; L:=[Coord, R] fi; fi;

   od; 

L; 

end proc: 

Examples of using the first procedure:

L:=[[0,2],[1,4],[4,4],[5,1],[3,0]]:

C:=LargestIncircle(L);

A:=plottools[disk](op(C), color=green):

B:=plottools[polygon](L, style=line, thickness=2):

plots[display](A,B, scaling=constrained);

The procedure can be used to find the largest circle inscribed in a convex shape, bounded by the curves, if these curves are approximated by broken lines:

L:=[seq([k,k^2], k=-1..2, 0.1)]:

C:=LargestIncircle(L);

A:=plottools[disk](op(C), color=green):

B:=plottools[polygon](L, style=line, thickness=2):

plots[display](A,B, scaling=constrained);

Examples of using the second procedure:

L:=[[0,2],[1,4],[4,4],[5,1],[3,0]]:

C:=MinCoveringCircle(L);

A:=plottools[circle](op(C), color=red, thickness=2):

B:=plottools[polygon](L, color=cyan):

plots[display](A,B);

The smallest circle covering 30 random points:

> roll:=rand(1..10):

L:=[seq([roll(), roll()], i=1..30)]:

C:=MinCoveringCircle(L);

A:=plottools[circle](op(C), color=red, thickness=2):

B:=seq(plottools[disk](L[i],0.07,color=blue), i=1..nops(L)):

C1:=plottools[disk](C[1], 0.07, color=red):

T:=plots[textplot]([C[1,1]-0.2, C[1,2]-0.2, "C"], font=[TIMES,ROMAN,16]):

plots[display](A, B, C1, T);

The attached presentation is the second one of a sequence of three that we want to do on Quantum Mechanics using Computer Algebra. The first presentation was about the equation for a quantum system of identical particles, the Gross-Pitaevskii equation (GPE). This second presentation is about the spectrum of its solutions. The level is that of an advanced undergraduate QM course. The novelty is again in the way these problems can be tackled nowadays in a computer algebra worksheet with Physics.

QuantumMechanics.pdf     Download QuantumMechanics2.mw

Edgardo S. Cheb-Terrab
Physics, Maplesoft

Hi,
Relevant developments in Physics happened during the last month and a 1/2, some of them of interest beyond the use of this package. Among the most exciting things I can mention:

1. The redefinition of the derivative rule for the complex components (abs, argument, conjugate, Im, Re, signum) together with the introduction of Wirtinger calculus, as an user-option to work with complex variables. In other words: it is now possible to compute taking z and its conjugate as independent variables and in equal footing.
2. Introduction of textbook mathematical display for all the inert functions of the mathematical language, also for unknown functions f(x).
3. New options in Physics:-Setup to indicate that some mathematical objects are real (different from assume(x, real), while integrated with `is` and `coulditbe`).
4. A rather large number of micro developments advancing the integration of Physics with simplify, expand and combine.
5. Another large number of micro developments for quantum mechanics.
6. New options in Physics:-Setup to redefine sum as Physics:-Library:-Add, and with that have access to multiindex summation directly from sum, for instance as in sum(f(i, j), i + j <= n), including related typesetting copy & paste.

As usual the latest version of the package is available for download in the Maplesoft Physics: Research & Development webpage  and in the zip there is a worksheet illustrating all these developments. Below I'm copying the section related to the new redefinesum option of Physics:-Setup and multiindex summation.

Thanks to everyone who provided feedback, it has been of great value and at the root of this new round of developments.

Download sum_in_physics.mw

Edgardo S. Cheb-Terrab
Physics, Maplesoft

The attached presentation is the first one of a sequence of three that we wanted to do on Quantum Mechanics using Computer Algebra. The level is that of an advanced undergraduate QM course. Tackling this topic within a computer algebra worksheet in the way it's done below, however, is an entire novelty, and illustrates well the kind of computations that can be done today with Maple & Physics.

Edgardo S. Cheb-Terrab
Physics, Maplesoft

Greetings to all.

As some of you may remember I made several personal story type posts concerning my progress in solving enumeration problems with the Polya Enumeration Theorem (PET). This theorem would seem to be among the most exciting in mathematics and it is of an amazing simplicity so that I never cease to suggest to mathematics teachers to present it to gifted students even before university. My previous efforts are documented at your site, namely at this MaplePrimes link I and this MaplePrimes link II.

I have been able to do another wonderful cycle index computation using Maple recently and I would like to share the Maple code for this problem, which is posted at Math StackExchange.com (this post includes the code) This time we are trying to compute the cycle index of the automorphism group of the 3-by-3-by-3 cube under rotations and reflections. I suggest you try this problem yourself before you look at my solution. Enjoy!

I mentioned in some of my other posts concerning PET that Maple really ought to come with a library of cycle indices and the functions to manipulate them. I hope progress has been made on this issue. I had positive feedback on this at the time here at your website. Do observe that you have an opportinuity here to do very attractive mathematics if you prepare a worksheet documenting cycle index facilities that you may eventually provide. This is good publicity owing to the fact that you can include images of the many geometric objects that appear which all look quite enticing and moreover potential readers get rewarded quickly as they discover that it takes little effort to master this theorem and proceed to work with symmetries themselves and investigate them. This sort of thing also makes nice slides.

With best wishes for happy combinatorics computing,

Marko Riedel

Napoleon_Triangle.mw

Here 'show triangle napoleon considering the sintaxis Maple, to be supplemented and explained with Math Apps.

Napoleon_Triangle.mw

Lenin Araujo Castillo

Hi
In connection with recent developments in the Physics package, we now have mathematical typesetting for all the inert functions of the mathematical language. Hey! This is within the Physics update available on the Maplesoft Physics: Research & Development webpage. 

I think this is an interesting development that will concretely change the computational experience with these functions: it is not the same to compute with something you see displayed as %exp(x) instead of the same computation but flowing with it nicely displayed as an exponential function with the e in grey, reflecting that Maple understands this object as the exponential inert function, with known properties (all those of the active exp function), and so Maple can compute with the inert one taking these properties into account while not executing the function itself - and this is the essence of the inert function behaviour.

Introducing mathematical display, copy and paste for all these inert functions of the mathematical language concretely increases the mathematical expressiveness of the system, for teaching, working and also for presenting ideas.

Attached is a brief illustration.

Edgardo S. Cheb-Terrab
Physics, Maplesoft

InertMathematicalFun.mw  InertMathematicalFun.pdf

Good morning to all our Mapleprimes members.

It is very helpful to many persons who are very passion and dedicated to teach Mathematics using Maple technology if the software package is loaded with updated maple procedures of all the topics.

I am being of them, request the technical authorities and the eminant professors to support and develop this requirement.It becomes an open door to many people to enter and aquire the immence knowledge in Maple.

With thanks & Regards

M.Anand

Assistant Professor in Mathematics

SR International Institute of Technology,

Hyderabad, Andhra Pradesh, INDIA.

The work consists of two independent procedures. The first procedure  IsConvex  checks the convexity of a polygon. The second procedure  IsSimple  verifies the simplicity of a polygon. Formal argument  X  is the list of vertices of the polygon.

Regarding the basic concepts, see  http://en.wikipedia.org/wiki/Polygon

IsConvex:=proc(X::listlist)

local n, Z, f, i, x, y;

n:=nops(X);

Z:=[op(X),X[1]];

f:=seq((x-Z[i,1])*(Z[i+1,2]-Z[i,2])-(y-Z[i,2])*(Z[i+1,1]-Z[i,1]),i=1..n);

   for i to n do

    if  convert([seq(is(subs(x=j[1],y=j[2],f[i])<=0), j in {op(X)} minus  {X[i],X[irem(i,n)+1]})],`or`) and      convert([seq(is(subs(x=j[1],y=j[2],f[i])>=0),

    j in {op(X)} minus {X[i],X[irem(i,n)+1]})], `or`) then break fi;

   od;

if i<=n then return false else true fi;

end proc:

IsSimple:=proc(X::listlist)

local n, Z, i, j, f, T, Q, x, y;

Z:=[op(X),X[1],X[2]]; n:=nops(X);

if n>nops({op(X)}) then   return false  fi;

   for i from 2 to nops(Z)-1 do

     if is((Z[i-1,1]-Z[i,1])*(Z[i+1,1]-Z[i,1])+(Z[i-1,2]-Z[i,2])*(Z[i+1,2]-Z[i,2]) =  sqrt((Z[i-1,1] -Z[i,1])^2+(Z[i-1,2]-Z[i,2])^2)*sqrt((Z[i+1,1]-Z[i,1])^2 +(Z[i+1,2]-Z[i,2])^2)) then return false fi;

   od;

f:=seq((x-Z[i,1])*(Z[i+1,2]-Z[i,2])-(y-Z[i,2])*(Z[i+1,1]-Z[i,1]),i=1..n);

_Envsignum0:= 0: 

   for i from 1 to n do

   T[i]:=[]; Q[i]:=[];

      for j from 1 to n do

      if modp(j-i,n)<>0 and modp(j-i,n)<>1 and modp(j-i,n)<>n-1 and                  not(signum(subs(x=Z[j,1],y=Z[j,2],f[i])*subs(x=Z[j+1,1],y=Z[j+1,2],f[i]))=-1 and             signum(subs(x=Z[i,1],y=Z[i,2],f[j])*subs(x=Z[i+1,1],y=Z[i+1,2],f[j]))=-1) then

      if (subs(x=Z[j,1],y=Z[j,2],f[i])=0 implies (signum((Z[j,1]-Z[i,1])*(Z[i+1,1]-Z[j,1]))=-1 or             signum((Z[j,2]-Z[i,2])*(Z[i+1,2]-Z[j,2]))=-1)) then

      T[i]:=[op(T[i]),1]; Q[i]:=[op(Q[i]),1] else  T[i]:=[op(T[i]),1]  fi; fi;   od;

       od; 

convert([seq(nops(T[i])=n-3,i=1..n), seq(nops(Q[i])=n-3,i=1..n)],`and`)  

end proc:

Examples:

X:=[[0,0],[1,0],[2,1],[3,0],[4,0],[2,2]]: IsConvex(X), IsSimple(X);

X:=[[0,0],[2,0],[1,1],[1,-1]]: IsConvex(X), IsSimple(X);

X:=[[0,0],[2,0],[1,1],[1,0], [-1,-1]]: IsConvex(X), IsSimple(X);

X:=[[0,0],[1,0],[1,2],[-2,2],[-2,-2],[3,-2],[3,4],[-4,4],[-4,-4],[5,-4],[5,6],[-6,6],[-6,-6],[7,-6],[7,8],[-6,8],[-6,7],[6,7],[6,-5],[-5,-5],[-5,5],[4,5],[4,-3],[-3,-3],[-3,3],[2,3],[2,-1],[-1,-1],[-1,1],[0,1]]: IsConvex(X), IsSimple(X);

X:=[seq([cos(2*Pi*k/17), sin(2*Pi*k/17)], k=0..16)]: IsConvex(X), IsSimple(X);

Testing_polygons.mws 

Edited: The variables  x  and  y  are made local.

La aplicacion de las matrices en su más claro ejemplo, dirigido explicitamente a la criptografia; solo hay que tener conocimiento de algebra de matrices y calculo de matriz inversa. (versión español).

The application of the matrices in its most obvious example, explicitly directed to cryptography; just have to have knowledge of matrix algebra and inverse matrix calculation. (version english).

Criptografia.mw

Lenin Araujo Castillo

Physics Pure

Computer Science

Well-known problem is the problem of placing eight shess queens on an 8×8 chessboard so that no two queens attack each other. In this post, we consider the same problem of placing  m  shess queens on an  n×n  chessboard. The problem has a solution if  n>3  and  m<=n .

Work consists of two procedures. The first procedure  Queens  returns the total number of solutions and saves a complete list of all solutions (global variable  S ). The second procedure  QueensPic  shows the user-defined solutions from the list  S  on the board. Formal argument  t  is the number of solutions in each row of the display. The second procedure should be used in the standard interface, rather than in the classic one, since in the latter it may not work properly.

Queens := proc (m::posint, n::posint)

local It, K, l, L, M, P;

global S, p, q;

It := proc (L)

local P, k, i, j;

M := []; k := nops(L[1]);

for i in L do

for j to n do

if convert([seq(j <> i[s, 2], s = 1 .. k)], `and`) and convert([seq(l[k+1]-i[s, 1] <> i[s, 2]-j, s = 1 .. k)], `and`) and convert([seq(l[k+1]-i[s, 1] <> j-i[s, 2], s = 1 .. k)], `and`) then M := [op(M), [op(i), [l[k+1], j]]]

fi;

od; od;

M;

end proc;

K := combinat:-choose([`$`(1 .. n)], m);

S := [];

for l in K do P := [];

L := [seq([[l[1], i]], i = 1 .. n)];

P := [op(P), op((It@@(m-1))(L))];

S := [op(S), op(P)]

od;

p := args[1]; q := args[2];

nops(S);

end proc:

QueensPic := proc (M, t::posint)

local m, n, HL, VL, T, A, N;

uses plottools, plots;

m := p; n := q; N := nops(args[1]);

HL := seq(line([.5, .5+k], [.5+n, .5+k], color = black, thickness = 2), k = 0 .. n);

VL := seq(line([.5+k, .5], [.5+k, .5+n], color = black, thickness = 2), k = 0 .. n);

T := [seq(textplot([seq([op(M[i, j]), Q], j = 1 .. m)], color = red, font = [TIMES, ROMAN, 24]), i = 1 .. N)];

if m <= n and 3 < n then

A := seq(display(HL, VL, T[k], axes = none, scaling = constrained), k = 1 .. N), seq(display(plot([[0, 0]]), axes = none, scaling = constrained), k = 1 .. t*ceil(N/t)-N);

Matrix(ceil(N/t), t, [A]);

display(%);

fi;

end proc:

Examples of work:

Queens(5, 6);  

S[70], S[140], S[210];

QueensPic([%], 3); 

                                                                            248

[[1, 5], [2, 3], [3, 6], [4, 4], [6, 1]], [[1, 3], [2, 5], [4, 1], [5, 4], [6, 2]], [[2, 1], [3, 4], [4, 2], [5, 5], [6, 3]]

Two solutions of classic problem:

Queens(8, 8); 

S[64..65];

QueensPic(%, 2);

                                                                                      92

[[[1, 5], [2, 8], [3, 4], [4, 1], [5, 7], [6, 2], [7, 6], [8, 3]], [[1, 6], [2, 1], [3, 5], [4, 2], [5, 8], [6, 3], [7, 7], [8, 4]]]

Queens_problem.mw

Voting is open for the next individual prize to be awarded as part of the Möbius App Challenge.  The winner will receive an iPad Prize Pack! 

Here are the finalist Apps:

• Parameterized Curves
• ODE Systems