A framework to evaluate the performance of Variational Quantum Algorithms

• URL: http://arxiv.org/abs/2601.18812v1
• Date: Wed, 21 Jan 2026 13:15:57 GMT
• Title: A framework to evaluate the performance of Variational Quantum Algorithms
• Authors: Ernesto Mamedaliev, Vladyslav Libov, Albert Nieto-Morales, Oskar Słowik, Arit Kumar Bishwas,
• Abstract summary: Variational Quantum Algorithms (VQAs) are promising methods for solving optimization problems on noisy quantum devices.<n> benchmarking VQAs is difficult due to their behavior and the lack of standardized performance criteria.<n>This work introduces a general framework for evaluating VQAs applied to Quadratic Unconstrained Binary Optimization problems.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Variational Quantum Algorithms (VQAs) are promising methods for solving combinatorial optimization problems on noisy intermediate-scale quantum (NISQ) devices. However, benchmarking VQAs is difficult due to their stochastic behavior and the lack of standardized performance criteria. This work introduces a general framework for evaluating VQAs applied to Quadratic Unconstrained Binary Optimization (QUBO) problems. The framework uses three complementary metrics: feasibility, quality, and reproducibility. It also introduces a quality diagram that visualizes trade-offs between success probability and computational resources. Reproducibility is formalized using Shannon entropy, and a decision rule is defined for selecting algorithms under resource constraints. As a demonstration, the framework is applied to several VQAs using Conditional Value at Risk (CVaR) cost functions and different shot counts on a 16-qubit QUBO instance. The results show how the framework supports systematic benchmarking and provides a foundation for adaptive algorithm selection in hybrid quantum-classical workflows.

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