Programmable simulations of molecules and materials with reconfigurable quantum processors

IF 17.6 1区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
Nishad Maskara, Stefan Ostermann, James Shee, Marcin Kalinowski, Abigail McClain Gomez, Rodrigo Araiza Bravo, Derek S. Wang, Anna I. Krylov, Norman Y. Yao, Martin Head-Gordon, Mikhail D. Lukin, Susanne F. Yelin
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Abstract

Simulations of quantum chemistry and quantum materials are believed to be among the most important applications of quantum information processors. However, realizing practical quantum advantage for such problems is challenging because of the prohibitive computational cost of programming typical problems into quantum hardware. Here we introduce a simulation framework for strongly correlated quantum systems represented by model spin Hamiltonians that uses reconfigurable qubit architectures to simulate real-time dynamics in a programmable way. Our approach also introduces an algorithm for extracting chemically relevant spectral properties via classical co-processing of quantum measurement results. We develop a digital–analogue simulation toolbox for efficient Hamiltonian time evolution using digital Floquet engineering and hardware-optimized multi-qubit operations to accurately realize complex spin–spin interactions. As an example, we propose an implementation based on Rydberg atom arrays. In addition, we show how detailed spectral information can be extracted from the dynamics through snapshot measurements and single-ancilla control, enabling the evaluation of excitation energies and finite-temperature susceptibilities from a single dataset. To illustrate the approach, we show how to use the method to compute key properties of a polynuclear transition-metal catalyst and two-dimensional magnetic materials. Quantum simulations of chemistry and materials are challenging due to the complexity of correlated systems. A framework based on reconfigurable qubit architectures and digital–analogue simulations provides a hardware-efficient path forwards.

Abstract Image

Abstract Image

可编程模拟分子和材料与可重构量子处理器
量子化学和量子材料的模拟被认为是量子信息处理器最重要的应用之一。然而,实现此类问题的实际量子优势是具有挑战性的,因为将典型问题编程到量子硬件中的计算成本令人望而却步。在这里,我们引入了一个由模型自旋哈密顿子表示的强相关量子系统的仿真框架,该框架使用可重构量子比特架构以可编程的方式模拟实时动力学。我们的方法还介绍了一种通过量子测量结果的经典协同处理提取化学相关光谱特性的算法。我们开发了一个数字模拟仿真工具箱,利用数字Floquet工程和硬件优化的多量子位运算来实现高效的哈密顿时间演化,以精确实现复杂的自旋-自旋相互作用。作为一个例子,我们提出了一个基于里德伯原子阵列的实现。此外,我们展示了如何通过快照测量和单辅助控制从动力学中提取详细的光谱信息,从而能够从单个数据集中评估激发能和有限温度敏感性。为了说明这种方法,我们展示了如何使用该方法来计算多核过渡金属催化剂和二维磁性材料的关键性质。
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来源期刊
Nature Physics
Nature Physics 物理-物理:综合
CiteScore
30.40
自引率
2.00%
发文量
349
审稿时长
4-8 weeks
期刊介绍: Nature Physics is dedicated to publishing top-tier original research in physics with a fair and rigorous review process. It provides high visibility and access to a broad readership, maintaining high standards in copy editing and production, ensuring rapid publication, and maintaining independence from academic societies and other vested interests. The journal presents two main research paper formats: Letters and Articles. Alongside primary research, Nature Physics serves as a central source for valuable information within the physics community through Review Articles, News & Views, Research Highlights covering crucial developments across the physics literature, Commentaries, Book Reviews, and Correspondence.
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