Skip to main content

replacement - How to transform abstract finite group to permutation group?


It seems that Mathematica only has group functionality for permutation groups? Then there is a step to transform the abstract finite one to a permutation one.


As an example, consider the following problem



Suppose $G=$, try to compute $ab^2ab^2a$.



It can proceed by viewing the elements of group just as a string, and the rule of group can be view as a rule of string replace. Any way, I would like to use NonCommutativeMultiply instead:


Firstly, let us define the rule, basically, we only need to define the rule for $ab$ and $ba$, since whenever we know how to commute these two generators, then we can use the fact $a^2=1=b^3$ to simplify our expression. It is not hard to compute $ab=b^2a$, $ba=ab^2$:


rel = {c___ ** a ** a ** d___ :> c ** i ** d, 

c___ ** b ** b ** b ** d___ :> c ** i ** d,
c___ ** a ** b ** d___ :> c ** b ** b ** a ** d,
c___ ** b ** a ** d___ :> c ** a ** b ** b ** d , a___ ** i :> a,
i ** a___ :> a}

Now, let us define the set of group elements. Since $a$ is a order 2 element and $b$ is order $3$, we know that $G$ must be a subgroup of order $6=o(a)\times o(b)$, thus the elements can be expressed by


set = {i, a, b, b ** b, a ** b, b ** a}

Lastly, we can compute what's the results of $a$ multiply from left:


a ** # & /@ set/.rel


The problem: It seems my rule has not do the function of simplify the expression, as you can see the results is


{a, NonCommutativeMultiply[i], b ** b ** a, b ** b ** a ** b, i ** b, 
b ** b ** a ** a}

the element b**b**a**a should be b**b, so please help me to correct the rule?


The correct result should be


aset = {a, i, a ** b, b ** a, b, b ** b}

form which we can find the permutation by



FindPermutation[set, aset]

which gives


Cycles[{{1, 2}, {3, 5}, {4, 6}}]

Answer



For simplicity, let's set


ncm[a__] := NonCommutativeMultiply[a]

My recommendation for this problem is to choose a "normal order" for the group elements. That is, I would choose to represent the group elements in such a way that all the a's are to the left of the b's. To do this, we define our set of replacements in such a way that b's always move to the right:


rel = {ncm[c___, a, a, d___] :> ncm[c, i, d]

, ncm[c___, b, b, b, d___] :> ncm[c,i, d]
, ncm[c___, b, b, a, d___] :> ncm[c, a, b, d]
, ncm[c___, b, a, d___] :> ncm[c, a, b, b, d]
, ncm[a__, i] :> ncm[a]
, ncm[i, a__] :> ncm[a]
, ncm[a_] :> a
}

This guarantees that when we apply the rules repeatedly (which we have to do), the process will eventually terminate.


Then, we get the group elements into normal order by using ReplaceRepeated with the replacement rules rel:



set = {i, a, b, b ** b, a ** b, b ** a} //. rel
(* {i, a, b, b ** b, a ** b, a ** b ** b} *)

So, instead of using b ** a as one of the elements, we use the slightly more complicated (but it turns out easier to use) a ** b ** b.


Finally, then, multiplication on the left by a results in


aset = a ** # & /@ set //. rel
(* {a, i, a ** b, a ** b ** b, b, b ** b} *)

and


FindPermutation[set, aset]

(* Cycles[{{1, 2}, {3, 5}, {4, 6}}] *)



Brief explanation


To answer your questions:




  • NonCommutativeMultiply has very little rules associated with it. In particular, ncm[a] doesn't evaluate, i.e. it just evaluates to ncm[a]. So we have to add the rule that if we have ncm[i], for instance, this will evaluate to i.





  • _ is Blank. It is a pattern that will match any single expression. __ is BlankSequence. It is a pattern will match any sequence of one or more expressions. ___ is BlankNullSequence. It will match any sequence of expressions, including the Null Sequence. Meditate on the results of these three evaluations:


    {f[], f[a], f[a, b]} /. f[_] :> f[1]


    {f[], f[a], f[a, b]} /. f[__] :> f[1]


    {f[], f[a], f[a, b]} /. f[___] :> f[1]




Comments

Popular posts from this blog

plotting - Filling between two spheres in SphericalPlot3D

Manipulate[ SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, Mesh -> None, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], {n, 0, 1}] I cant' seem to be able to make a filling between two spheres. I've already tried the obvious Filling -> {1 -> {2}} but Mathematica doesn't seem to like that option. Is there any easy way around this or ... Answer There is no built-in filling in SphericalPlot3D . One option is to use ParametricPlot3D to draw the surfaces between the two shells: Manipulate[ Show[SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], ParametricPlot3D[{ r {Sin[t] Cos[1.5 Pi], Sin[t] Sin[1.5 Pi], Cos[t]}, r {Sin[t] Cos[0 Pi], Sin[t] Sin[0 Pi], Cos[t]}}, {r, 1, 2 - n}, {t, 0, Pi}, PlotStyle -> Yellow, Mesh -> {2, 15}]], {n, 0, 1}]

plotting - Plot 4D data with color as 4th dimension

I have a list of 4D data (x position, y position, amplitude, wavelength). I want to plot x, y, and amplitude on a 3D plot and have the color of the points correspond to the wavelength. I have seen many examples using functions to define color but my wavelength cannot be expressed by an analytic function. Is there a simple way to do this? Answer Here a another possible way to visualize 4D data: data = Flatten[Table[{x, y, x^2 + y^2, Sin[x - y]}, {x, -Pi, Pi,Pi/10}, {y,-Pi,Pi, Pi/10}], 1]; You can use the function Point along with VertexColors . Now the points are places using the first three elements and the color is determined by the fourth. In this case I used Hue, but you can use whatever you prefer. Graphics3D[ Point[data[[All, 1 ;; 3]], VertexColors -> Hue /@ data[[All, 4]]], Axes -> True, BoxRatios -> {1, 1, 1/GoldenRatio}]

plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1.