Quantum State Collapse with Adaptive Bias Fields

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum state collapse, a fundamental aspect of quantum mechanics, represents the irreversible loss of information about a quantum system's state. This phenomenon poses a significant obstacle to achieving reliable quantum computation. Traditional approaches often struggle with achieving high accuracy in measurement outcomes due to inherent uncertainties and sensitivity to environmental factors. This paper explores a novel quantum algorithm, Quantum State Collapse with Adaptive Bias Fields, designed to mitigate these challenges by dynamically adjusting bias fields during the collapse process. We present a system of precisely calibrated bias fields that subtly influence the quantum system's evolution, aiming to enhance the fidelity of measurement results. The algorithm's effectiveness is demonstrated through simulations and preliminary experimental investigations, showcasing a demonstrable improvement in measurement accuracy compared to baseline approaches.

DOI: 10.5281/zenodo.22183616

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