変数量子回路の代替最適化
Erik J Gustafson1, Juha Tiihonen2, Diana Chamaki3
1Universities Space Research Association, Research Institute for Advanced Computer Science at NASA Ames Research Center, Moffett Field, CA 94035.
まとめ
この研究は,変数量子エイゲンソルバー (VQE) の性能を高めるための代替最適化アプローチを導入しています. クラシックシミュレータを使って ヘッシアンを近似することで 騒々しい量子計算の収束を加速します
科学分野:
- 量子コンピューティング
- 計算物理
- 最適化アルゴリズム
背景:
- 変数量子エイゲンソルバー (VQE) は近期量子アルゴリズムとして有望である.
- 現在のVQE方法は,騒々しい環境での最適化や,実用的な応用や量子優位性の主張を制限する課題に直面しています.
- 近期的な量子ハードウェアの能力の加速には 収束の改善が不可欠です
研究 の 目的:
- 変数量子アルゴリズムの新しい代替最適化アプローチを開発し,実証する.
- VQEのノイズの存在における最適化収束の課題に対処する.
- ハイブリッド量子-古典的な方法の効率と適用性を高める.
主な方法:
- モダンな回路シミュレーションと ストキャスティックな古典的な最適化技術を活用した.
- 量子処理ユニット (QPU) とクラシック (CPU/GPU) の近似状態ベクトルシミュレータを組み合わせた代替最適化アプローチを開発した.
- 量子または正確な回路シミュレータの入力として古典的シミュレーションで計算された近似のヘッシアンを使用し,QPU間の並列化を可能にします.
主要な成果:
- 量子回路の代替最適化方法を成功裏に実装しました
- 騒音のサンプリングやサンプリングなしでのアプローチの有効性を実証した.
- 40キビットの量子処理装置で 理論実証を行いました
結論:
- 代替最適化アプローチは,変数量子アルゴリズムの収束を大幅に改善します.
- この方法は,VQEやその他のハイブリッド最適化タスクの短期的な量子ハードウェア機能を加速するための実行可能な戦略を提供します.
- このアプローチの並列化性により,複数の量子処理ユニットでスケーリングするのに適しています.
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