most citedMachine learning the effects of many quantum measurements

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quant-ph2026

Climbing the Fusion Tree: Center Ordering and Decoding Hierarchy in Non-Abelian Mixed States

Pablo Sala, Vlad Temkin, Cenke Xu +2

We develop an operational approach to strong-to-weak spontaneous symmetry breaking (sw-SSB) of a non-Abelian symmetry group G. We formulate it as the decoding task of distinguishin…

quant-ph2026

Entanglement transitions in translation-invariant tensor networks

Yi-Cheng Wang, Samuel J. Garratt, Ehud Altman

We study the complexity of approximately contracting translation-invariant tensor networks. The computational cost of row-by-row tensor network contraction, which defines a discret…

quant-ph2025

Charge-Informed Quantum Error Correction

Vlad Temkin, Zack Weinstein, Ruihua Fan +2

We investigate the statistical physics of quantum error correction in symmetry-enriched topological quantum memories. Starting from a phenomenological error model of c…

quant-ph2025

Stability of quantum chaos against weak non-unitarity

Yi-Cheng Wang, Ehud Altman, Samuel J. Garratt

We study the quantum dynamics generated by the repeated action of a non-unitary evolution operator on a system of qubits. Breaking unitarity can lead to the purification of mixed i…

quant-ph2025★ 1 cited

Machine learning the effects of many quantum measurements

Wanda Hou, Samuel J. Garratt, Norhan M. Eassa +4

Measurements are essential for the processing and protection of information in quantum computers. They can also induce long-range entanglement between unmeasured qubits. However, w…