Title: Quantum State Collapse Optimization (QSCO)

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum state collapse is a fundamental process in quantum mechanics, and its optimization represents a significant challenge in quantum information processing. This paper introduces Quantum State Collapse Optimization (QSCO), a novel optimization technique designed to enhance fidelity collapses by explicitly modeling decoherence dynamics and employing a Bayesian approach to estimate collapse probabilities. The core mechanism of QSCO involves dynamically adjusting collapse parameters based on observed decoherence, while also incorporating a 'quantum memory' to preserve critical information. We demonstrate QSCO's effectiveness through simulations and analysis, showcasing a significant improvement in fidelity compared to existing collapse algorithms. This research addresses limitations in current approaches, particularly concerning the handling of complex decoherence patterns and the potential for achieving higher fidelity collapses.

DOI: 10.5281/zenodo.22221839

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