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    Improved entanglement entropy estimates from filtered bitstring probabilities

    Avi Kaufman1, James Corona1, Zane Ozzello1, Blake Senseman1, Muhammad Asaduzzaman1,2, and Yannick Meurice1

    Phys. Rev. A 112, 032430 – Published 19 September, 2025

    DOI: https://doi.org/10.1103/lbv3-2z7r

    Abstract

    Using the bitstring probabilities of ground states of bipartitioned ladders of Rydberg atoms, we calculate the mutual information, which is a lower bound on the corresponding bipartite von Neumann quantum entanglement entropy SAvN. We show that in many cases these lower bounds can be improved by removing the bitstrings with a probability lower than some value pmin and renormalizing the remaining probabilities (filtering). We propose a heuristic based on the change of the conditional entropy under filtering that very effectively improves the estimate of SAvN. We consider various sizes, lattice spacings, and bipartitions. Our numerical investigation suggest that the filtered mutual information obtained with samples having just a few thousand bitstrings can provide reasonably close estimates of SAvN. We briefly discuss practical implementations with QuEra's Aquila device.

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