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arXiv 2311.03347quant-phphysics.chem-ph
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强关联系统的稀疏量子态制备

Sparse Quantum State Preparation for Strongly Correlated Systems

C. Feniou, O. Adjoua, B. Claudon, J. Zylberman, E. Giner, J. -P. Piquemal

AI总结:

本研究利用Hyperion GPU模拟器对多达28量子比特的强关联系统进行量子态制备,比较多种变分与非变分方法,发现Overlap-ADAPT-VQE算法在电路深度和经典复杂度上最具优势,适合近期应用。

摘要:

量子计算原则上允许将指数级扩展的多电子波函数编码到线性扩展的量子比特寄存器上,为克服传统量子化学方法的局限性提供了一种有前景的解决方案。基态量子算法要变得实用,一个基本要求是将量子比特初始化为所寻求基态的高质量近似。量子态制备(QSP)允许制备从经典计算获得的近似本征态,但它在量子信息中常被视为一个预言机。在本研究中,我们使用Hyperion GPU加速态矢量模拟器,对多达28个量子比特的原型强关联系统的基态进行QSP。我们比较了各种变分和非变分方法在电路深度和经典复杂度方面的表现。我们的结果表明,最近开发的Overlap-ADAPT-VQE算法在近期应用中提供了最具优势的性能。

英文摘要:

Quantum Computing allows, in principle, the encoding of the exponentially scaling many-electron wave function onto a linearly scaling qubit register, offering a promising solution to overcome the limitations of traditional quantum chemistry methods. An essential requirement for ground state quantum algorithms to be practical is the initialisation of the qubits to a high-quality approximation of the sought-after ground state. Quantum State Preparation (QSP) allows the preparation of approximate eigenstates obtained from classical calculations, but it is frequently treated as an oracle in quantum information. In this study, we conduct QSP on the ground state of prototypical strongly correlated systems, up to 28 qubits, using the Hyperion GPU-accelerated state-vector emulator. Various variational and non-variational methods are compared in terms of their circuit depth and classical complexity. Our results indicate that the recently developed Overlap-ADAPT-VQE algorithm offers the most advantageous performance for near-term applications.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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