Algorithmic Complexity Theory for Quantum Simulations

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum simulations are increasingly important for scientific discovery, particularly in fields like materials science and drug discovery. However, these simulations face significant challenges due to the inherent complexity of quantum systems. Traditional complexity analysis methods often struggle to accurately estimate the computational resources required for large-scale simulations, hindering progress. This paper proposes a novel algorithmic approach, 'Quantum Complexity Estimator' (QCE), designed specifically to address these challenges by dynamically modeling resource consumption and identifying critical bottlenecks. We present a framework that automatically estimates the complexity of a quantum simulation by analyzing its structure and implementing a sophisticated optimization strategy. The QCE aims to provide a more practical and scalable method for assessing the feasibility of quantum simulations, enabling researchers to focus their efforts on the most computationally demanding aspects. The paper details the algorithm's design, implementation, and preliminary results demonstrating its effectiveness in estimating complexity for several benchmark quantum simulations.

DOI: 10.5281/zenodo.22272501

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