550 research outputs found
A Hybrid Search Algorithm for the Whitehead Minimization Problem
The Whitehead Minimization problem is a problem of finding elements of the
minimal length in the automorphic orbit of a given element of a free group. The
classical algorithm of Whitehead that solves the problem depends exponentially
on the group rank. Moreover, it can be easily shown that exponential blowout
occurs when a word of minimal length has been reached and, therefore, is
inevitable except for some trivial cases.
In this paper we introduce a deterministic Hybrid search algorithm and its
stochastic variation for solving the Whitehead minimization problem. Both
algorithms use search heuristics that allow one to find a length-reducing
automorphism in polynomial time on most inputs and significantly improve the
reduction procedure. The stochastic version of the algorithm employs a
probabilistic system that decides in polynomial time whether or not a word is
minimal. The stochastic algorithm is very robust. It has never happened that a
non-minimal element has been claimed to be minimal
Heuristics for The Whitehead Minimization Problem
In this paper we discuss several heuristic strategies which allow one to
solve the Whitehead's minimization problem much faster (on most inputs) than
the classical Whitehead algorithm. The mere fact that these strategies work in
practice leads to several interesting mathematical conjectures. In particular,
we conjecture that the length of most non-minimal elements in a free group can
be reduced by a Nielsen automorphism which can be identified by inspecting the
structure of the corresponding Whitehead Graph
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