2006/08/11 by S. N. Coppersmith, Coppersmith, S. N.
Computer Science · Mathematics · Physics and Astronomy · #Computational Complexity (cs.CC) #F.1.3 #FOS: Computer and information sciences #FOS: Physical sciences #Markov Chains and Monte Carlo Methods #Statistical Mechanics (cond-mat.stat-mech) #Stochastic processes and statistical mechanics #Theoretical and Computational Physics #cond-mat.stat-mech #cs.CC
paper · pdf · doi:10.48550/arxiv.cs/0608053
Original version had a conjecture that is known to be false. Revised version corrects this error
openalex publication_date 2006/08/11 · arxiv created 2006/10/01 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper argues that the ideas underlying the renormalization group technique used to characterize phase transitions in condensed matter systems could be useful for distinguishing computational complexity classes. The paper presents a renormalization group transformation that maps an arbitrary Boolean function of N Boolean variables to one of N-1 variables. When this transformation is applied repeatedly, the behavior of the resulting sequence of functions is different for a generic Boolean function than for Boolean functions that can be written as a polynomial of degree ξ with ξ≪ N as well as for functions that depend on composite variables such as the arithmetic sum of the inputs. Being able to demonstrate that functions are non-generic is of interest because it suggests an avenue for constructing an algorithm capable of demonstrating that a given Boolean function cannot be computed using resources that are bounded by a polynomial of N.