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Bibliographic Details
Main Authors: Lam, William T., Joshi, Manoj K., França, Daniel Stilck, Vermersch, Benoît
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.26953
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author Lam, William T.
Joshi, Manoj K.
França, Daniel Stilck
Vermersch, Benoît
author_facet Lam, William T.
Joshi, Manoj K.
França, Daniel Stilck
Vermersch, Benoît
contents We review and numerically study a protocol for Liouvillian learning based on randomized Pauli states and measurements. In particular, in the two-body, long-range interactions, and single-body noise setting, we describe the complete workflow to obtain the coefficients of the Liouvillian in an efficient and pairwise manner, meaning that the required classical memory is independent of the system size. We also provide guidelines for choosing the parameters for data acquisition and postprocessing that minimize the total reconstruction error.
format Preprint
id arxiv_https___arxiv_org_abs_2605_26953
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Pairwise Liouvillian learning from randomized measurements: practical aspects and guidelines for operating the protocol in large-scale experiments
Lam, William T.
Joshi, Manoj K.
França, Daniel Stilck
Vermersch, Benoît
Quantum Physics
We review and numerically study a protocol for Liouvillian learning based on randomized Pauli states and measurements. In particular, in the two-body, long-range interactions, and single-body noise setting, we describe the complete workflow to obtain the coefficients of the Liouvillian in an efficient and pairwise manner, meaning that the required classical memory is independent of the system size. We also provide guidelines for choosing the parameters for data acquisition and postprocessing that minimize the total reconstruction error.
title Pairwise Liouvillian learning from randomized measurements: practical aspects and guidelines for operating the protocol in large-scale experiments
topic Quantum Physics
url https://arxiv.org/abs/2605.26953