Noise robust detection of quantum phase transitions

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the study of ground-states of condensed matter models, and the transitions between them. However, current levels of hardware noise can require extensive application of error-mitigation techniques to achieve reliable computations. In this work, we use several IBM devices to explore a finite-size spin model with multiple “phaselike” regions characterized by distinct ground-state configurations. Using preoptimized Variational Quantum Eigensolver (VQE) solutions, we demonstrate that in contrast to calculating the energy, where zero-noise extrapolation is required in order to obtain qualitatively accurate yet still unreliable results, calculations of the energy derivative, two-site spin correlation functions, and the fidelity susceptibility yield accurate behavior across multiple regions, even with minimal or no application of error-mitigation approaches. Taken together, these sets of observables could be used to identify level crossings in a simple, noise-robust manner which is agnostic to the method of ground state preparation. This work shows promising potential for near-term application to identifying quantum phase transitions, including avoided crossings and nonadiabatic conical intersections in electronic structure calculations. Published by the American Physical Society 2024

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Publication Details

Journal
Physical Review Research
Published
2024-12-10
DOI
https://doi.org/10.1103/physrevresearch.6.043254
Citations
7
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
2.43

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article

Noise robust detection of quantum phase transitions

Kevin Lively, Benedikt Fauseweh, Tim Bode, Jian‐Xin Zhu et al.
7 citations
Physical Review Research
Quantum Computing Algorithms and Architecture
2.43
article

Noise robust detection of quantum phase transitions

Kevin Lively, Benedikt Fauseweh, Tim Bode, Jian‐Xin Zhu, Jochen Szangolies
article en
7 citations

Abstract

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the study of ground-states of condensed matter models, and the transitions between them. However, current levels of hardware noise can require extensive application of error-mitigation techniques to achieve reliable computations. In this work, we use several IBM devices to explore a finite-size spin model with multiple “phaselike” regions characterized by distinct ground-state configurations. Using preoptimized Variational Quantum Eigensolver (VQE) solutions, we demonstrate that in contrast to calculating the energy, where zero-noise extrapolation is required in order to obtain qualitatively accurate yet still unreliable results, calculations of the energy derivative, two-site spin correlation functions, and the fidelity susceptibility yield accurate behavior across multiple regions, even with minimal or no application of error-mitigation approaches. Taken together, these sets of observables could be used to identify level crossings in a simple, noise-robust manner which is agnostic to the method of ground state preparation. This work shows promising potential for near-term application to identifying quantum phase transitions, including avoided crossings and nonadiabatic conical intersections in electronic structure calculations. Published by the American Physical Society 2024

Physical Review ResearchVol. 6(4)
Los Alamos National Laboratory (US), Forschungszentrum Jülich (DE), TU Dortmund University (DE), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Center for Integrated Nanotechnologies (US)
U.S. Department of Energy, International Business Machines Corporation, Center for Integrated Nanotechnologies, Laboratory Directed Research and Development, Los Alamos National Laboratory
Openalex Percentile: Top 9%
Quantum Computing Algorithms and Architecture
2.43
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