Measurement-Guided State Refinement for Shallow Feedback-Based Quantum Optimization Algorithm

• URL: http://arxiv.org/abs/2602.20407v1
• Date: Mon, 23 Feb 2026 23:07:11 GMT
• Title: Measurement-Guided State Refinement for Shallow Feedback-Based Quantum Optimization Algorithm
• Authors: Lucas A. M. Rattighieri, Pedro M. Prado, Marcos C. de Oliveira, Felipe F. Fanchini,
• Abstract summary: Limited circuit depth remains a central constraint for quantum optimization in noisy quantum regimes.<n>We introduce Measurement-Guided Initialization (MGI), an iterative strategy that uses measurement outcomes from previous executions.<n>We show that MGI improves the performance of shallow-depth circuits and enables iterative refinement toward high-quality solutions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Limited circuit depth remains a central constraint for quantum optimization in the noisy intermediate-scale quantum (NISQ) regime, where shallow unitary dynamics may fail to sufficiently concentrate probability on low-energy configurations. We introduce Measurement-Guided Initialization (MGI), an iterative strategy that uses measurement outcomes from previous executions to update the initialization of subsequent runs. The method extracts single-qubit marginal probabilities from dominant measurement outcomes and prepares a biased product-state initialization, allowing information obtained during optimization to be reused without introducing classical parameter optimization. We implement this approach in the context of the Feedback-Based Algorithm for Quantum Optimization (FALQON) and evaluate its performance on weighted MaxCut instances. Numerical results show that measurement-guided initialization improves the performance of shallow-depth circuits and enables iterative refinement toward high-quality solutions while preserving the non-variational structure of the algorithm. These results indicate that measurement statistics can be exploited to improve shallow quantum optimization protocols compatible with NISQ devices.

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