Level-p-complexity of Boolean Functions using Thinning, Memoization, and Polynomials
Julia Jansson, Patrik Jansson

TL;DR
This paper introduces a functional library to compute level-p-complexity of Boolean functions, applying it to two-level iterated majority, and improves on previous complexity bounds using polynomial techniques.
Contribution
It presents a novel functional library leveraging thinning, memoization, and polynomials to efficiently compute level-p-complexity of Boolean functions.
Findings
Successfully computed complexity for two-level iterated majority
Improved previous bounds on level-p-complexity for specific functions
Demonstrated efficiency of polynomial-based methods in complexity calculations
Abstract
This paper describes a purely functional library for computing level--complexity of Boolean functions, and applies it to two-level iterated majority. Boolean functions are simply functions from bits to one bit, and they can describe digital circuits, voting systems, etc. An example of a Boolean function is majority, which returns the value that has majority among the input bits for odd . The complexity of a Boolean function measures the cost of evaluating it: how many bits of the input are needed to be certain about the result of . There are many competing complexity measures but we focus on level--complexity -- a function of the probability that a bit is 1. The level--complexity is the minimum expected cost when the input bits are independent and identically distributed with Bernoulli() distribution. We specify the problem as choosing the…
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Taxonomy
TopicsFormal Methods in Verification · semigroups and automata theory · Advanced Algebra and Logic
