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Counterdiabatic, Better, Faster, Stronger: Optimal control for approximate counterdiabatic driving

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arxiv 2403.20267 v1 pith:BGDDJYX2 submitted 2024-03-29 quant-ph

classification quant-ph
keywords adiabaticcounterdiabaticcontroldrivingoptimalquantumdifficulteffects
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Adiabatic protocols are employed across a variety of quantum technologies, from implementing state preparation and individual operations that are building blocks of larger devices, to higher-level protocols in quantum annealing and adiabatic quantum computation. The main drawback of adiabatic processes, however, is that they require prohibitively long timescales. This generally leads to losses due to decoherence and heating processes. The problem of speeding up system dynamics while retaining the adiabatic condition has garnered a large amount of interest, resulting in a whole host of diverse methods and approaches made for this purpose. This thesis is dedicated to the discovery of new ways to combine optimal control techniques with a universal method from STA: counterdiabatic driving (CD). The CD approach offers perfect suppression of all non-adiabatic effects experienced by a system driven by a time-dependent Hamiltonian regardless of how fast the process occurs. In practice, however, exact CD is difficult to derive often even more difficult to implement. The main result presented in the thesis is thus the development of a new method called counterdiabatic optimized local driving (COLD), which implements optimal control techniques in tandem with \emph{approximations} of exact CD in a way that maximises suppression of non-adiabatic effects.

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  1. 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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