An Application of Markov Chain Analysis to Integer Complexity
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The complexity $f(n)$ of an integer was introduced in 1953 by Mahler & Popken: it is defined as the smallest number of $1$'s needed in conjunction with arbitrarily many +, * and parentheses to write an integer $n$ (for example, $f(6) \leq 5$ since $6 = (1+1)(1+1+1)$). The best known bounds are $$ 3 \log_{3}{n} \leq f(n) \leq 3.635 \log_{3}{n}.$$ The lower bound is due to Selfridge (with equality for powers of 3); the upper bound was recently proven by Arias de Reyna & Van de Lune, and holds on a set of natural density one. We use Markov chain methods to analyze a large class of algorithms, including one found by David Bevan that improves the upper bound to $$ f(n) \leq 3.52 \log_{3}{n}$$ on a set of logarithmic density one.
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Upper and lower estimates for integer complexity
Integer complexity satisfies ||n|| ≤ C_avg log n + o(log n) implying lim sup ||n||/log n ≤ C_avg ≈ 3.236, plus the first nontrivial lower bound ||n|| ≥ 3.06 log_3 n for almost all n.
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