Feedback-based quantum algorithm inspired by counterdiabatic driving

In recent quantum algorithmic developments, a feedback-based approach has shown promise for preparing quantum many-body system ground states and solving combinatorial optimization problems. This method utilizes quantum Lyapunov control to iteratively construct quantum circuits. Here, we propose a substantial enhancement by implementing a protocol that uses ideas from quantum Lyapunov control and the counterdiabatic driving protocol, a key concept from quantum adiabaticity. Our approach introduces an additional control field inspired by counterdiabatic driving. We apply our algorithm to prepare ground states in one-dimensional quantum Ising spin chains. Comprehensive simulations demonstrate a remarkable acceleration in population transfer to low-energy states within a significantly reduced time frame compared to conventional feedback-based quantum algorithms. This acceleration translates to a reduced quantum circuit depth, a critical metric for potential quantum computer implementation. We validate our algorithm on the IBM cloud computer, highlighting its efficacy in expediting quantum computations for many-body systems and combinatorial optimization problems. Published by the American Physical Society 2024

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Publication Details

Journal
Physical Review Research
Published
2024-10-25
DOI
https://doi.org/10.1103/physrevresearch.6.043068
Citations
11
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
3.82

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article

Feedback-based quantum algorithm inspired by counterdiabatic driving

Hongye Yu, Rajesh K. Malla, Hiroki Sukeno, Tzu-Chieh Wei et al.
11 citations
Physical Review Research
Quantum Computing Algorithms and Architecture
3.82
article

Feedback-based quantum algorithm inspired by counterdiabatic driving

Hongye Yu, Rajesh K. Malla, Hiroki Sukeno, Tzu-Chieh Wei, Robert Konik, Andreas Weichselbaum
article en
11 citations

Abstract

In recent quantum algorithmic developments, a feedback-based approach has shown promise for preparing quantum many-body system ground states and solving combinatorial optimization problems. This method utilizes quantum Lyapunov control to iteratively construct quantum circuits. Here, we propose a substantial enhancement by implementing a protocol that uses ideas from quantum Lyapunov control and the counterdiabatic driving protocol, a key concept from quantum adiabaticity. Our approach introduces an additional control field inspired by counterdiabatic driving. We apply our algorithm to prepare ground states in one-dimensional quantum Ising spin chains. Comprehensive simulations demonstrate a remarkable acceleration in population transfer to low-energy states within a significantly reduced time frame compared to conventional feedback-based quantum algorithms. This acceleration translates to a reduced quantum circuit depth, a critical metric for potential quantum computer implementation. We validate our algorithm on the IBM cloud computer, highlighting its efficacy in expediting quantum computations for many-body systems and combinatorial optimization problems. Published by the American Physical Society 2024

Physical Review ResearchVol. 6(4)
Brookhaven National Laboratory (US), Stony Brook University (US)
U.S. Department of Energy, International Business Machines Corporation, Office of Science, Basic Energy Sciences, Brookhaven National Laboratory
Affordable and clean energy
Openalex Percentile: Top 6%
Quantum Computing Algorithms and Architecture
3.82
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Feedback-based quantum algorithm inspired by counterdiabatic driving — Hongye Yu, Rajesh K. Malla, et al. · Physical Review Research (2024) | TGRS Research Map | TGRS