Schreier-Sims algorithm

From Groupprops

This article describes an algorithm for the following problem: strong generating set-finding problem

Solution

Basic idea

The idea behind solving the order-finding problem for comes from the following descending chain of subgroups:

where .

By an easy coset counting argument:

Obstacles and overcoming them

We can readily compute a system of coset representatives for in by using the breadth-first search. Further information: minimal Schreier system

The problem, however, is: how do we get a generating set for starting from a generating set for , To solve this problem, we can use Schreier's lemma which provides a constructive approach to obtaining a generating set for the subgroup from a generating set for the whole group and a system of coset representatives (the more general problem is finding a generating set from a membership test).

This still leaves another problem: Each time we go downward on the chain, the size of the generating set may go up by a factor of (because the index of the subgroup is ). Thus, we need to keep the size of the subset small at every stage. This can be done using a small generating set-finding algorithm, such as the Sims filter or the Jerrum's filter.

Flow of the algorithm

Description of the step of the algorithm:

Start with: a generating set for

Do the following:

  1. Finding coset representatives: Using a breadth-first search, find a minimal Schreier system of coset representatives for in
  2. Finding the index: From this, obtain
  3. Finding a generating set: Using the coset representatives and the generating set , obtain a (possibly larger) generating set for . This uses Schreier's lemma
  4. Filtering the generating set: Apply a filter to trim the size, and call the filtered generating set .

Analysis of running time

  1. Finding coset representatives: This takes time since that is the number of edges in the graph.
  2. Finding the index: This comes for free
  3. Finding a generating set: This takes time since terms need to be computed and the computation of each requires multiplication operations (which take time).
  4. Filtering the generating set: This takes time dependent on the choice of filter. A naive analysis on Jerrum's filter reveals that the time taken is because the new generating set with which we start is itself of size . Similarly a naive analysis of the Sims filter reveals that the time it takes is .

Now, if we apply the filter right at the start, then at every step, is polynomially bounded. Thus:

Total time = Time taken to apply filter at the start + Time taken at each stage

Thus:

  • In the case of Jerrum's filter:
  • In the case of Sims filter: