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arXiv 2110.02201cond-mat.quant-gasquant-ph
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用里德堡原子链中的精确动力学对离散截断维格纳近似与神经网络量子态进行基准测试

Benchmarking discrete truncated Wigner approximation and neural network quantum states with the exact dynamics in a Rydberg atomic chain

Vighnesh Naik, Varna Shenoy, Weibin Li, Rejish Nath

AI总结:

本研究以10原子里德堡链的精确动力学为基准,对比DTWA与基于受限玻尔兹曼机的NQS,发现强相互作用下DTWA偏差明显,NQS可通过增加隐藏自旋优化但仅适用于短时,其时间平均激发数与精确值高度吻合,且在量子关联计算上更具潜力。

摘要:

我们以10个原子的里德堡原子链中的精确激发与关联动力学为基准,对离散截断维格纳近似(DTWA)和基于受限玻尔兹曼机类结构的神经量子态(NQS)开展性能测试。初始态设定为所有原子处于电子基态。我们利用里德堡激发的最大数目与时间平均数目来表征激发动力学。在里德堡-里德堡相互作用较强的情况下,DTWA的结果与精确动力学存在差异。相比之下,通过增加隐藏自旋的数量,NQS的性能可以得到提升,但仍仅适用于短时动力学场景。有趣的是,无论相互作用强度如何,NQS得到的时间平均激发数目都与精确结果高度吻合。在量子关联计算方面,例如二阶双体和平均两位置Rényi熵的计算,NQS表现出更优的前景。最后,我们讨论了平均两位置Rényi熵初始增长阶段存在幂律标度的可能性。

英文摘要:

We benchmark the discrete truncated Wigner approximation (DTWA) and Neural quantum states (NQS) based on restricted Boltzmann-like machines with the exact excitation and correlation dynamics in a chain of ten Rydberg atoms. The initial state is where all atoms are in their electronic ground state. We characterize the excitation dynamics using the maximum and time-averaged number of Rydberg excitations. DTWA results are different from the exact dynamics for large Rydberg-Rydberg interactions. In contrast, by increasing the number of hidden spins, the NQS can be improved but still limited to short-time dynamics. Interestingly, irrespective of interaction strengths, the time-averaged number of excitations obtained using NQS is in excellent agreement with the exact results. Concerning the calculation of quantum correlations, for instance, second-order bipartite and average two-site Rényi entropies, NQS looks more promising. Finally, we discuss the existence of a power law scaling for the initial growth of average two-site Rényi entropy.

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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