量子コンピューティングを用いた量子化学の最適化(Unleashing Quantum Computing for Quantum Chemistry from Constrained Optimization)

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2025-05-23 パシフィック・ノースウェスト国立研究所(PNNL)

米国パシフィック・ノースウェスト国立研究所(PNNL)は、量子化学計算における制約付き最適化の課題を克服する新手法を開発した。従来の変分量子固有値ソルバー(VQE)に代わり、一般化固有値問題を解くことで、より厳密なエネルギー下限を導出し、バレンプラトー問題(勾配消失)を回避できる。さらに、非直交基底の線形展開を用いた適応的変換選択により、精度と効率を両立。この成果は励起状態の計算やハミルトニアンの縮小など量子化学の高精度応用に貢献する。

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制約条件付き最適化から解き放たれた量子化学のための量子コンピューティング:ジェネレーター座標に触発された方法を用いて Unleashed from constrained optimization: quantum computing for quantum chemistry employing generator coordinate inspired method

Muqing Zheng,Bo Peng,Ang Li,Xiu Yang & Karol Kowalski
npj Quantum Information  Published0:3 December 2024
DOI:https://doi.org/10.1038/s41534-024-00916-8

量子コンピューティングを用いた量子化学の最適化(Unleashing Quantum Computing for Quantum Chemistry from Constrained Optimization)

Abstract

Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.

1603情報システム・データ工学
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