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Robust Simulations of Many-Body Symmetry-Protected Topological Phase Transitions on a Quantum Processor

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arxiv 2503.08776 v1 pith:SEYBPURA submitted 2025-03-11 quant-ph cond-mat.str-el

classification quant-phcond-mat.str-el
keywords quantumentanglementmany-bodyphasestopologicalcharacteristiccriticaledge
verification ladder T0 review T1 audit T2 compute T3 formal
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Topology and symmetry play critical roles in characterizing quantum phases of matter. Recent advancements have unveiled symmetry-protected topological (SPT) phases in many-body systems as a unique class of short-range entangled states, notable for their nontrivial edge modes and characteristic ground-state entanglement gap. In this study, we demonstrate the robust simulation of many-body ground states of an Ising-cluster model on a quantum computer. By employing the method of quantum imaginary-time evolution (QITE) combined with enhanced zero-noise extrapolation techniques, we achieve accurate measurements of the transition between trivial and cluster SPT phases. Furthermore, we measured the characteristic edge modes and their associated topological entanglement properties, such as the second R\'enyi entropy, reduced density matrix, and entanglement spectral gap. Our work demonstrates the potential of using QITE in investigating sophisticated quantum phase transitions and critical phenomena on quantum computers.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Circuit structure-preserving error mitigation for High-Fidelity Quantum Simulations

    quant-ph 2025-05 conditional novelty 5.0 of 10

    A structure-preserving error mitigation technique that inverts a noise matrix measured from an identity-equivalent circuit is demonstrated on variational simulations of a non-Hermitian Ising chain, showing improved ag...

  2. Benchmarking Quantum Solvers in Noisy Digital Simulations for Financial Portfolio Optimization

    quant-ph 2025-08 reject novelty 4.0 of 10

    On small synthetic portfolio problems, noiseless QAOA fits the known ground-state energy well, but noisy QAOA fails while QITE, pretrained on noiseless simulators, still identifies the optimal portfolio on IBM hardware.

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