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Adaptive Noise Shaping in Quantum Field Theory

Jincheng Zhang

Published Sep 6, 2026• 0 citations
Publisher

Abstract

This paper investigates the challenges and opportunities presented by quantum field theory simulations, particularly concerning the inherent noise present within the system. We propose a novel adaptive noise shaping mechanism utilizing a feedback loop to dynamically adjust noise parameters in response to simulation output, aiming to minimize errors and enhance the precision of quantum field calculations. The core claim is that this design will significantly improve the accuracy and reliability of simulations, addressing a critical limitation in current approaches. This work introduces a framework for automatically optimizing noise shaping based on simulation results, representing a fundamental shift in how we manage and mitigate noise in quantum field calculations.

DOI
10.5281/zenodo.22525760

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Quantum simulation, a powerful tool for understanding complex quantum systems, faces significant challenges due to inherent noise. This paper investigates the use of Adaptive Noise-Resonance (ANR) to mitigate these errors, offering a novel approach to enhance the accuracy and stability of quantum simulations. We propose a technique that dynamically adjusts noise levels during the simulation process, effectively reducing errors by leveraging the feedback loop between the simulation and the noise. The core mechanism centers on creating a resonant frequency within the simulation, where noise is strategically introduced to counteract errors. The paper details the theoretical framework, implementation of ANR, and preliminary experimental results demonstrating its efficacy. The significance of this research lies in its potential to significantly improve the reliability and speed of quantum simulations, opening doors to more complex and accurate models.
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