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arXiv · 2510.23171

Benchmarking VQE Configurations: Architectures, Initializations, and Optimizers for Silicon Ground State Energy

Zakaria Boutakka·Nouhaila Innan·Muhammed Shafique·Mohamed Bennai·Z. Sakhi
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Abstract

Quantum computing presents a promising path toward precise quantum chemical simulations, particularly for systems that challenge classical methods. This work investigates the performance of the Variational Quantum Eigensolver (VQE) in estimating the ground-state energy of the silicon atom, a relatively heavy element that poses significant computational complexity. Within a hybrid quantum-classical optimization framework, we implement VQE using a range of ansatz, including Double Excitation Gates, ParticleConservingU2, UCCSD, and k-UpCCGSD, combined with various optimizers such as gradient descent, SPSA, and ADAM. The main contribution of this work lies in a systematic methodological exploration of how these configuration choices interact to influence VQE performance, establishing a structured benchmark for selecting optimal settings in quantum chemical simulations. Key findings show that parameter initialization plays a decisive role in the algorithm's stability, and that the combination of a chemically inspired ansatz with adaptive optimization yields superior convergence and precision compared to conventional approaches.

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Zakaria Boutakka, Nouhaila Innan, Muhammed Shafique, Mohamed Bennai, Z. Sakhi. 2025-10-27. Benchmarking VQE Configurations: Architectures, Initializations, and Optimizers for Silicon Ground State Energy. https://arxiv.org/abs/2510.23171

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