Integer complexity: algorithms and computational results
Abstract
Define to be the complexity of , the smallest number of ones needed to write using an arbitrary combination of addition and multiplication. Define to be stable if for all , we have . In [7], this author and Zelinsky showed that for any , there exists some such that is stable; however, the proof there provided no upper bound on or any way of computing it. In this paper, we describe an algorithm for computing , and thereby also show that the set of stable numbers is a computable set. The algorithm is based on considering the defect of a number, defined by , building on the methods presented in [3]. As a side benefit, this algorithm also happens to allow fast evaluation of the complexities of powers of ; we use it to verify that for and arbitrary (excluding the case ), providing more evidence for the conjecture that whenever and are not both zero. An implementation of these algorithms in Haskell is available.
Cite
@article{arxiv.1606.03635,
title = {Integer complexity: algorithms and computational results},
author = {Harry Altman},
journal= {arXiv preprint arXiv:1606.03635},
year = {2018}
}
Comments
34 pages, 2 figures