Adaptive Quantum Circuit Compilation via Variational Quantum Eigensolver Optimization

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper presents a novel approach to quantum circuit compilation that leverages the feedback capabilities of the Variational Quantum Eigensolver (VQE) to achieve adaptive optimization. Traditional quantum compilation methods are static, assuming a known and consistent noise profile for the target quantum hardware. However, real quantum devices exhibit significant noise variations, leading to suboptimal circuit execution. Our strategy addresses this challenge by dynamically adjusting compilation parameters based on the VQE's error estimations during runtime. The core idea is to implement a real-time optimization loop where the VQE provides error estimates for individual gate operations, and the compiler subsequently modifies the circuit topology and gate choices to minimize overall error. This adaptive compilation scheme allows the quantum circuit to 'learn' the noise characteristics of the hardware, leading to a reduction in gate count and improved fidelity. The presented framework offers a pathway towards more robust and efficient quantum computation, particularly relevant as quantum hardware matures and noise mitigation techniques become more sophisticated. We outline the key components of the system, including the VQE integration, the compilation algorithm, and a discussion of potential challenges and future research directions.

DOI: 10.5281/zenodo.22337995

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