Capturing strong correlation effects on a quantum annealer: calculation of avoided crossing in the H$_4$ molecule using the quantum annealer eigensolver

• URL: http://arxiv.org/abs/2412.20464v3
• Date: Thu, 27 Mar 2025 05:35:23 GMT
• Title: Capturing strong correlation effects on a quantum annealer: calculation of avoided crossing in the H$_4$ molecule using the quantum annealer eigensolver
• Authors: Aashna Anil Zade, Kenji Sugisaki, Matthias Werner, Ana Palacios, Jordi Riu, Jan Nogue, Artur Garcia-Saez, Arnau Riera, V. S. Prasannaa,
• Abstract summary: We extend the scope of the Quantum Annealer Eigensolver (QAE) algorithm.<n>We consider the classic example of the H$_4$ molecule in a rectangular geometry.<n>We find that we can predict avoided crossings within about 1.2% of the FCI value on real quantum hardware.
• Score: 0.0522403833979862
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We broaden the scope of the Quantum Annealer Eigensolver (QAE) algorithm, an underexplored noisy intermediate scale quantum (NISQ) era approach for calculating atomic and molecular properties, to predict avoided crossings, where strong correlation effects are at play. For this purpose, we consider the classic example of the H$_4$ molecule in a rectangular geometry. Our results are obtained on the 5000-qubit D-Wave Advantage system 4.1 quantum computer. We benchmark our quantum annealing results with full configuration interaction (FCI) as well as with those obtained using simulated annealing. We find that we can predict avoided crossings within about 1.2% of the FCI value on real quantum hardware. We carry out analyses on the effect of the number of shots, anneal time, and the choice of Lagrange multiplier on our obtained results. Since the QAE algorithm provides information on the wave function as its output, we also check the quality of the computed wave function by calculating the fidelity, and find it to be 99.886%. Finally, we qualitatively discuss the strengths and weaknesses of the QAE algorithm relative to its gate-based NISQ algorithm counterpart, the celebrated Variational Quantum Eigensolver (VQE).

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