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.

中文翻译：

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可编程绝热消磁，适用于具有微小和拓扑励磁的系统


我们提出了一种简单、健壮的协议，用于在量子计算机或可编程量子模拟器上准备任意哈密顿量的低能量状态。该协议的灵感来自绝热退磁技术，用于将固态系统冷却到极低的温度。一小部分量子比特（或自旋）用于对耦合到系统的自旋浴进行建模。通过作用在浴槽自旋上的模拟塞曼场的绝热斜坡下降，能量和熵从系统中提取出来。然后测量浴液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。我们通过应用于量子 Ising 模型来演示该协议。我们研究了该协议在存在噪音下的性能，并展示了如何使用浴液旋转测量的信息来监测冷却过程。算法的性能取决于系统激励的性质;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。我们探索了通过捕获拓扑激发来缓解这个问题的可能方法。