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Quantum counterdiabatic driving with local control

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arxiv 2403.01854 v1 pith:LILTKC6Z submitted 2024-03-04 quant-ph cond-mat.stat-mechphysics.app-phphysics.atom-ph

classification quant-phcond-mat.stat-mechphysics.app-phphysics.atom-ph
keywords localadiabaticdrivingquantumcounterdiabaticperformanceadiabaticitycontrol
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Suppression of diabatic transitions in quantum adiabatic evolution stands as a significant challenge for ground state preparations. Counterdiabatic driving has been proposed to compensate for diabatic losses and achieve shortcut to adiabaticity. However, its implementation necessitates the generation of adiabatic gauge potential, which requires knowledge of the spectral gap of instantaneous Hamiltonians and involves highly non-local drivings in many-body systems. In this work, we consider local counterdiabatic (LCD) driving with approximate adiabatic gauge potential. Using transverse-field Ising model as an example, we present an in-depth study of the performance and optimization of LCD protocols. We then propose a novel two-step protocol based on LCD and simple local single-body control to further improve the performance. The optimization of these LCD-based protocols does not require knowledge of instantaneous Hamiltonians, and only additional local driving is involved. To benchmark the performance of LCD and the proposed local control-enhanced LCD technique, we experimentally implement digitized adiabatic quantum evolution in a trapped-ion system. We characterize the quality of the prepared states and explore the scaling behavior with system size up to 14 qubits. Our demonstration of quantum shortcut to adiabaticity opens a path towards preparing ground states of complex systems with accessible local controls.

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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. Shortcuts to Analog Preparation of Non-Equilibrium Quantum Lakes

    quant-ph 2025-02 conditional novelty 6.0 of 10

    Approximate counterdiabatic driving naturally targets the hemidiabatic 'quantum lakes' state and speeds up its preparation by nearly an order of magnitude in a Rydberg ruby lattice model.

  2. Improving adiabatic quantum factorization via chopped random-basis optimization

    quant-ph 2025-05 conditional novelty 4.0 of 10

    Applying CRAB schedule optimization to adiabatic factorization Hamiltonians raises final-state fidelity for integers 21 to 2479, with a performance threshold near the quantum speed limit, and the improvement survives ...

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