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Physical Science and Quantum Computing Adaptive Simulation Algorithm

Jincheng Zhang

Published Sep 1, 2026• 0 citations
Publisher

Abstract

This paper introduces an adaptive simulation algorithm designed to enhance the accuracy and efficiency of physical simulations, leveraging the combined strengths of physics and quantum computing. The core mechanism centers around a "Physics Adaptive Simulation" system, which dynamically adjusts simulation parameters based on the algorithm's output, ensuring a more precise and robust model. Traditional physical simulation methods rely on manual parameter tuning, which is often time-consuming and requires expert knowledge. This algorithm automates this process, leading to improved simulation capabilities. The paper details the algorithm's design, implementation, and preliminary results, demonstrating its potential to revolutionize the field of physical simulation.

DOI
10.5281/zenodo.22219567

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This paper introduces a novel quantum simulation algorithm based on an adaptive quantum field. Traditional quantum simulation methods often require manual parameter adjustment, limiting automation and potentially impacting accuracy. Our algorithm dynamically adjusts the quantum field parameters during the simulation process, achieving significantly improved simulation fidelity and efficiency. We demonstrate the effectiveness of this approach through a series of carefully chosen simulations, highlighting its potential to revolutionize quantum simulation workflows. The core mechanism focuses on automated parameter tuning through a self-adjusting field, allowing for a more robust and accurate simulation.
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