Quantum Bayesian Drift (QBD)

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum Bayesian Drift (QBD) presents a novel approach to quantum mechanics by formally incorporating a Bayesian Drift framework. This framework proposes that quantum states continuously adjust to local environments through a probabilistic update, eliminating the need for a global wavefunction. This research explores the mathematical foundations of this drift, detailing a quantum state evolution algorithm that leverages Bayesian inference to dynamically adjust probabilities. The core claim is that QBD enables instantaneous adaptation of quantum states to local environments, offering a potential pathway toward truly adaptive quantum systems.

DOI: 10.5281/zenodo.22521839

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