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

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arXiv · 2110.02201

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

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Abstract

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 R\'enyi entropies, NQS looks more promising. Finally, we discuss the existence of a power law scaling for the initial growth of average two-site R\'enyi entropy.

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Vighnesh Naik, Varna Shenoy, Weibin Li, Rejish Nath. 2021-10-05. Benchmarking discrete truncated Wigner approximation and neural network quantum states with the exact dynamics in a Rydberg atomic chain. https://arxiv.org/abs/2110.02201

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