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We present a constructive SAT-based algorithm to determine the multiplicative complexity of a Boolean function, i.e., the smallest number of AND gates in any logic network that consists of 2-input AND gates, 2-input XOR gates, and inverters. In order to speed-up solving time, we make use of several symmetry breaking constraints; these exploit properties of XAGs that may be useful beyond the proposed SAT-based algorithm. We further propose a heuristic post-optimization algorithm to reduce the number of XOR gates once the optimum number of AND gates has been obtained, which also makes use of SAT solvers. Our algorithm is capable to find all optimum XAGs for representatives of all 5-input affine-equivalent classes, and for a set of frequently occurring 6-input functions.
The {em Total Influence} ({em Average Sensitivity) of a discrete function is one of its fundamental measures. We study the problem of approximating the total influence of a monotone Boolean function ifnumplusminus=1 $f: {pm1}^n longrightarrow {pm1}$,
We provide two sufficient and necessary conditions to characterize any $n$-bit partial Boolean function with exact quantum 1-query complexity. Using the first characterization, we present all $n$-bit partial Boolean functions that depend on $n$ bits
The k-regret query aims to return a size-k subset S of a database D such that, for any query user that selects a data object from this size-k subset S rather than from database D, her regret ratio is minimized. The regret ratio here is modeled by the
Limits on the number of satisfying assignments for CNS instances with n variables and m clauses are derived from various inequalities. Some bounds can be calculated in polynomial time, sharper bounds demand information about the distribution of the n
For Boolean satisfiability problems, the structure of the solution space is characterized by the solution graph, where the vertices are the solutions, and two solutions are connected iff they differ in exactly one variable. For this implicitly define