Efficiently Computing Conjugacy Classes in GL(n,Fp)

In summary, the conversation discusses finding an efficient algorithm for computing conjugacy classes in subgroups of the general linear group GL(n,\mathbb{F}_p). The goal is to find a method that can handle subgroups generated by a small number of matrices, and can either sort the elements into conjugacy classes or generate them directly. The difficulty lies in the mathematical aspect rather than the programming aspect, and the conversation mentions using the normalizer to find the conjugacy classes. However, this approach may not be efficient due to the large size of the normalizer compared to the subgroup. The request for suggestions on a method that can work for any given n, p, and generating matrices is also mentioned.
  • #1
simba31415
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0

Homework Statement


As the title says, I'm trying to find an efficient algorithm in order to write a program for computing conjugacy classes in subgroups of the general linear group [itex]GL(n,\mathbb{F}_p)[/itex] (n x n matrices over a finite field of p elements, p prime) efficiently. In particular, I am looking at conjugacy classes of subgroups of [itex]GL(n,\mathbb{F}_p)[/itex] generated by a small number of elements (say 2 or 3 generating matrices, though I'd like to be able to theoretically do it for arbitrarily many).

Is there an especially nice/clever/efficient way to compute the conjugacy classes? Whilst I am writing a program for this (so I can't really take a method which is ad hoc for lots of different situations), I believe the maths and not the programming is where the difficulty lies; I want a good reasonably fast algorithm which guarantees me all the elements in the subgroup generated by a small number of matrices, and also either then sorts them into conjugacy classes or (certainly preferable:) actually generates all the elements of the subgroup in their conjugacy classes, eliminating the need to sort them afterwards (which I'm not sure how I'd go about doing anyway). I can easily calculate the order of the generating matrices if that's any use, though since we can combine even just 2 matrices in many different ways I'm not sure it will be. At any rate, I'll either need to be able to figure out the total order of the subgroup of [itex]GL(n,\mathbb{F}_p)[/itex], so I can tell when I'm done calculating the conjugacy classes, or perhaps more preferably the process will automatically stop generating the cclasses when done and I can just add up their sizes to get the size of the subgroup - but how do even I approach this this? Say the group [itex]H \subset GL(n,\mathbb{F}_p)[/itex] is generated by [itex]M_1,\,...,\,M_t[/itex], how do we determine the conjugacy classes in a way which works for any given n, p and generating matrices? Could anyone suggest anything?

I'm happy with mathematical ideas of any complexity so don't hold back, though I would prefer the programming to be relatively simple, as I'm not going to rely on lots of prewritten programs to figure things out for me! Thanks very much in advance. -Simba
 
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  • #2
Homework Equations N/AThe Attempt at a Solution My attempt so far has been to use the fact that the conjugacy classes of subgroups H \subset GL(n,\mathbb{F}_p) are in bijection with the cosets of the normalizer N_G(H) in GL(n,\mathbb{F}_p), where G is the general linear group. I then thought that I could calculate the normalizer (which I can do in polynomial time using the orbit-stabilizer theorem) and then use the coset decomposition to get the conjugacy classes, but this doesn't really help me because the normalizer is usually much larger than the subgroup itself and so the number of cosets is much larger than the number of conjugacy classes I actually want. Is there a way to get around this bottleneck? Note that any algorithm should work for arbitrary n and p, as this is a problem in computational group theory.
 

1. What is GL(n,Fp) and why is it important in computing?

GL(n,Fp) is the general linear group of degree n over the finite field with p elements. It is important in computing because it represents a set of linear transformations that can be efficiently computed and used in various mathematical and scientific applications.

2. What are conjugacy classes in GL(n,Fp)?

Conjugacy classes in GL(n,Fp) are sets of elements that are considered equivalent under a certain transformation. In other words, two elements in a conjugacy class can be transformed into each other by a linear transformation in GL(n,Fp).

3. How can conjugacy classes in GL(n,Fp) be computed efficiently?

Conjugacy classes in GL(n,Fp) can be efficiently computed using the canonical form algorithm. This algorithm reduces the problem of finding conjugacy classes to finding the Jordan canonical form of a matrix, which can be done efficiently using various mathematical techniques.

4. What are some applications of efficiently computing conjugacy classes in GL(n,Fp)?

Efficiently computing conjugacy classes in GL(n,Fp) has various applications in mathematics, physics, and computer science. It can be used in solving systems of linear equations, analyzing the structure of groups and rings, and designing efficient algorithms for various computational problems.

5. Are there any limitations to efficiently computing conjugacy classes in GL(n,Fp)?

The complexity of computing conjugacy classes in GL(n,Fp) depends on the size of the finite field and the degree of the general linear group. As these values increase, the computational complexity also increases, making it more difficult to efficiently compute the conjugacy classes.

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