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arXiv 2502.03410quant-ph
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无知的 thermodynamic 代价:利用单个辅助量子比特制备热态

The Thermodynamic Cost of Ignorance: Thermal State Preparation with One Ancilla Qubit

Matthew Hagan, Nathan Wiebe

AI总结:

本文提出用单个辅助量子比特随机相互作用实现热态制备,证明其在弱耦合下近似为以热态为不动点的 Markov 链,并给出模拟时间上界及无知与完全知识成本之比,同时推广了 Repeated Interactions 模型。

摘要:

在这项工作中,我们研究了一种热化模型,其中单个辅助量子比特随机地与待热化的系统相互作用。这不仅揭示了自然界中 Gibbs 态涌现的机制,也为在数字量子计算机上制备任意热态提供了一种例程。对于期望的 $β$ 和随机相互作用 $G$,该例程归结为时间无关的 Hamiltonian 模拟,并由信道 $Φ: ρ\mapsto \mathbb{E}_G {\rm Tr}_{\rm Env} \left[ e^{-i(H + αG)t} \left(ρ\otimes \frac{e^{-βH_E}}{\mathcal{Z}}\right) e^{i (H + αG)t} \right]$ 表示。我们严格证明了这些动力学在弱耦合区域中退化为一个 Markov 链过程,且热态是其近似不动点。我们根据 Markov 链谱隙 $λ_\star$ 给出了所需总模拟时间的上界,并在基态极限下精确计算了该谱隙。这些结果不依赖于系统的任何本征值知识,但我们进一步证明,如果已知本征值差 $λ_S(i) - λ_S(j)$,则总模拟时间将大幅缩短。完全无知模拟成本与完全知识模拟成本之比按 $\widetilde{O} \left({\frac{\\|{H_S}\\|^7}{δ_{\rm min}^7 ε^{3.5} λ_\star(β)^{3.5}}}\right)$ 缩放,其中 $δ_{\min}$ 与系统的本征值差有关。此外,我们针对单量子比特和谐振子系统给出了更具体的结果,并对氢链进行了数值实验。除了算法上的优点外,这些结果还可以被视为 Repeated Interactions 模型向具有未知相互作用的通用 Hamiltonian 的广泛推广,从而为量子系统的热化过程提供了完整的图景。

英文摘要:

In this work we investigate a model of thermalization wherein a single ancillary qubit randomly interacts with the system to be thermalized. This not only sheds light on the emergence of Gibbs states in nature, but also provides a routine for preparing arbitrary thermal states on a digital quantum computer. For desired $β$ and random interaction $G$ the routine boils down to time independent Hamiltonian simulation and is represented by the channel $Φ: ρ\mapsto \mathbb{E}_G {\rm Tr}_{\rm Env} \left[ e^{-i(H + αG)t} \left(ρ\otimes \frac{e^{-βH_E}}{\mathcal{Z}}\right) e^{i (H + αG)t} \right]$. We rigorously prove that these dynamics reduce to a Markov chain process in the weak-coupling regime with the thermal state as the approximate fixed point. We upper bound the total simulation time required in terms of the Markov chain spectral gap $λ_\star$, which we compute exactly in the ground state limit. These results are independent of any eigenvalue knowledge of the system, but we are further able to show that with knowledge of eigenvalue differences $λ_S(i) - λ_S(j)$, then the total simulation time is dramatically reduced. The ratio of the complete ignorance simulation cost to the perfect knowledge simulation cost scales as $\widetilde{O} \left({\frac{\|{H_S}\|^7}{δ_{\rm min}^7 ε^{3.5} λ_\star(β)^{3.5}}}\right)$, where $δ_{\min}$ is related to the eigenvalue differences of the system. Additionally, we provide more specific results for single qubit and harmonic oscillator systems as well as numeric experiments with hydrogen chains. In addition to the algorithmic merits, these results can be viewed as broad extensions of the Repeated Interactions model to generic Hamiltonians with unknown interactions, giving a complete picture of the thermalization process for quantum systems.

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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