Constraint-Based Quantum Simulation via Hybrid Algorithms

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum simulation is a vital tool for understanding complex quantum systems, but current methods often struggle with the computational cost, particularly for large and intricate systems. This paper proposes a novel hybrid algorithm for quantum simulation that seamlessly integrates classical and quantum computation, leveraging a dynamically adjusted resource allocation strategy. We demonstrate the effectiveness of this approach through the simulation of a parameterized quantum system, showcasing improved accuracy and scalability compared to traditional methods. The core mechanism involves a carefully designed hybrid algorithm that exploits the strengths of both classical and quantum processing, leading to a more efficient and reliable simulation process. This work introduces a framework for enhanced quantum simulation capabilities, offering a significant advancement in this field.

DOI: 10.5281/zenodo.22517157

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