Quantum Information Bottleneck with Adaptive Constraint Propagation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel quantum information bottleneck paradigm centered on dynamically adaptive constraint propagation. Traditional quantum computation often relies on static constraints, which can limit the exploration of the quantum state space and hinder algorithm performance. We propose a "Constraint Propagation" algorithm leveraging quantum entanglement to iteratively refine a constraint on a quantum system, optimizing for error mitigation and enabling fundamentally new quantum algorithms. This approach shifts the focus from static constraint application to a dynamic, adaptive process, potentially unlocking significant improvements in fidelity and computational power. The core mechanism involves using entanglement to iteratively adjust the constraints, effectively "steering" the quantum system towards a more stable and informative state. This work demonstrates the potential of this paradigm through theoretical analysis and preliminary experimental validation, showcasing improved error mitigation and the development of novel quantum algorithms.

DOI: 10.5281/zenodo.22199396

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