具有三态和拓扑激发的系统的可编程绝热消磁

IF 5.1 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
Quantum Pub Date : 2024-10-23 DOI:10.22331/q-2024-10-23-1505
Anne Matthies, Mark Rudner, Achim Rosch, Erez Berg
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引用次数: 0

摘要

我们提出了一种简单、稳健的协议,用于在量子计算机或可编程量子模拟器上制备任意哈密顿的低能态。该协议受绝热消磁技术的启发,该技术用于将固态系统冷却到极低的温度。一部分量子比特(或自旋)被用来模拟与系统耦合的自旋浴。通过作用于自旋浴的模拟泽曼场的绝热降温,从系统中提取能量和熵。然后测量浴池自旋并将其重置为极化状态,并重复该过程,直到收敛到低能量稳态。我们将该协议应用于量子伊辛模型。我们研究了该协议在存在噪声时的性能,并展示了如何利用测量浴池自旋的信息来监控冷却过程。该算法的性能取决于系统激发的性质;具有非局部(拓扑)激发的系统比具有局部激发的系统更难冷却。我们探讨了通过捕获拓扑激元来缓解这一问题的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Programmable adiabatic demagnetization for systems with trivial and topological excitations
We propose a simple, robust protocol to prepare a low-energy state of an arbitrary Hamiltonian on a quantum computer or programmable quantum simulator. The protocol is inspired by the adiabatic demagnetization technique, used to cool solid-state systems to extremely low temperatures. A fraction of the qubits (or spins) is used to model a spin bath that is coupled to the system. By an adiabatic ramp down of a simulated Zeeman field acting on the bath spins, energy and entropy are extracted from the system. The bath spins are then measured and reset to the polarized state, and the process is repeated until convergence to a low-energy steady state is achieved. We demonstrate the protocol via application to the quantum Ising model. We study the protocol's performance in the presence of noise and show how the information from the measurement of the bath spins can be used to monitor the cooling process. The performance of the algorithm depends on the nature of the excitations of the system; systems with non-local (topological) excitations are more difficult to cool than those with local excitations. We explore the possible mitigation of this problem by trapping topological excitations.
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来源期刊
Quantum
Quantum Physics and Astronomy-Physics and Astronomy (miscellaneous)
CiteScore
9.20
自引率
10.90%
发文量
241
审稿时长
16 weeks
期刊介绍: Quantum is an open-access peer-reviewed journal for quantum science and related fields. Quantum is non-profit and community-run: an effort by researchers and for researchers to make science more open and publishing more transparent and efficient.
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