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

2025/10/27 by Boutakka, Zakaria, Innan, Nouhaila, Shafique, Muhammed +2 · 2 citations
#FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Quantum Physics (quant-ph)

paper · doi:10.48550/arxiv.2510.23171

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.

Citations

• Interferometric single-shot parity measurement in InAs–Al hybrid devices
• Ground State Energy Estimation on Current Quantum Hardware Through The Variational Quantum Eigensolver: A Comprehensive Study
• Quantum error correction below the surface code threshold
• Towards Efficient Quantum Computation of Molecular Ground State Energies using Bayesian Optimization with Priors over Surface Topology
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• Variational Quantum Algorithms
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• Quantum Computing in the NISQ era and beyond
• Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals
• An overview of gradient descent optimization algorithms
• PubChem Substance and Compound databases
• Adam: A Method for Stochastic Optimization

Cited by

• Investigating Different Barren Plateaus Mitigation Strategies in Variational Quantum Eigensolver
• Accuracy-Cost Trade-offs for Reference VQE Calculations of H₂ on IBM Quantum Hardware

Related

• Ground State Energy Estimation on Current Quantum Hardware Through The Variational Quantum Eigensolver: A Comprehensive Study
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• Towards Efficient Quantum Computation of Molecular Ground State Energies using Bayesian Optimization with Priors over Surface Topology