Circuit complexity and functionality: a thermodynamic perspective
Claudio Chamon, Andrei E. Ruckenstein, Eduardo R. Mucciolo, Ran Canetti

TL;DR
This paper explores the relationship between circuit complexity and thermodynamics, proposing a physics-inspired framework that offers new insights into program obfuscation and the structure of circuit spaces.
Contribution
It introduces a thermodynamic perspective on circuit complexity, linking it to thermalization and ergodicity, and discusses implications for cryptography and computational class separations.
Findings
Thermodynamic framework models circuit obfuscation as thermalization.
Fragmentation of circuit space limits ergodicity and connectivity.
Implications for NP vs coNP complexity classes.
Abstract
Circuit complexity, defined as the minimum circuit size required for implementing a particular Boolean computation, is a foundational concept in computer science. Determining circuit complexity is believed to be a hard computational problem [1,2,3]. Recently, in the context of black holes, circuit complexity has been promoted to a physical property, wherein the growth of complexity is reflected in the time evolution of the Einstein-Rosen bridge (``wormhole'') connecting the two sides of an AdS ``eternal'' black hole [4]. Here we are motivated by an independent set of considerations and explore links between complexity and thermodynamics for functionally-equivalent circuits, making the physics-inspired approach relevant to real computational problems, for which functionality is the key element of interest. In particular, our thermodynamic framework provides a new perspective on the…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Quantum Computing Algorithms and Architecture · Cellular Automata and Applications
