Counterdiabatic optimized driving in quantum phase sensitive models

Fuente: arXiv
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Auteurs principaux: Barone, Francesco Pio, Kiss, Oriel, Grossi, Michele, Vallecorsa, Sofia, Mandarino, Antonio
Format: Preprint
Publié: 2023
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author Barone, Francesco Pio
Kiss, Oriel
Grossi, Michele
Vallecorsa, Sofia
Mandarino, Antonio
author_facet Barone, Francesco Pio
Kiss, Oriel
Grossi, Michele
Vallecorsa, Sofia
Mandarino, Antonio
contents State preparation plays a pivotal role in numerous quantum algorithms, including quantum phase estimation. This paper extends and benchmarks counterdiabatic driving protocols across three one-dimensional spin systems characterized by phase transitions: the axial next-nearest neighbor Ising (ANNNI), XXZ, and Haldane-Shastry (HS) models. We perform quantum optimal control protocols by optimizing the energy cost function, which can always be evaluated as opposed to the fidelity one requiring the exact state. Moreover, we incorporate Bayesian optimization within a code package for computing various adiabatic gauge potentials. This protocol consistently surpasses standard annealing schedules, often achieving performance improvements of several orders of magnitude. Notably, the ANNNI model stands out as a notable example, where fidelities exceeding 0.5 are attainable in most cases. Furthermore, the optimized paths exhibits promising generalization capabilities to higher-dimensional systems, allowing for the extension of parameters from smaller models. This opens up possibilities for applying the protocol to higher-dimensional systems. However, our investigations reveal limitations in the case of the XXZ and HS models, particularly when transitioning away from the ferromagnetic phase. This suggests that finding optimal diabatic gauge potentials for specific systems remains an important research direction.
format Preprint
id arxiv_https___arxiv_org_abs_2311_04282
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Counterdiabatic optimized driving in quantum phase sensitive models
Barone, Francesco Pio
Kiss, Oriel
Grossi, Michele
Vallecorsa, Sofia
Mandarino, Antonio
Quantum Physics
Other Condensed Matter
State preparation plays a pivotal role in numerous quantum algorithms, including quantum phase estimation. This paper extends and benchmarks counterdiabatic driving protocols across three one-dimensional spin systems characterized by phase transitions: the axial next-nearest neighbor Ising (ANNNI), XXZ, and Haldane-Shastry (HS) models. We perform quantum optimal control protocols by optimizing the energy cost function, which can always be evaluated as opposed to the fidelity one requiring the exact state. Moreover, we incorporate Bayesian optimization within a code package for computing various adiabatic gauge potentials. This protocol consistently surpasses standard annealing schedules, often achieving performance improvements of several orders of magnitude. Notably, the ANNNI model stands out as a notable example, where fidelities exceeding 0.5 are attainable in most cases. Furthermore, the optimized paths exhibits promising generalization capabilities to higher-dimensional systems, allowing for the extension of parameters from smaller models. This opens up possibilities for applying the protocol to higher-dimensional systems. However, our investigations reveal limitations in the case of the XXZ and HS models, particularly when transitioning away from the ferromagnetic phase. This suggests that finding optimal diabatic gauge potentials for specific systems remains an important research direction.
title Counterdiabatic optimized driving in quantum phase sensitive models
topic Quantum Physics
Other Condensed Matter
url https://arxiv.org/abs/2311.04282