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Optimizing counterdiabaticity by variational quantum circuits.

Dan SunPranav ChandaranaZi-Hua XinXi Chen
Published in: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences (2022)
Using counterdiabatic (CD) driving-aiming at suppression of diabatic transition-in digitized adiabatic evolution has garnered immense interest in quantum protocols and algorithms. However, improving the approximate CD terms with a nested commutator ansatz is a challenging task. In this work, we propose a technique of finding optimal coefficients of the CD terms using a variational quantum circuit. By classical optimization routines, the parameters of this circuit are optimized to provide the coefficients corresponding to the CD terms. Then their improved performance is exemplified in Greenberger-Horne-Zeilinger state preparation on the nearest-neighbour Ising model. Finally, we also show the advantage over the usual quantum approximation optimization algorithm, in terms of fidelity with bounded time. This article is part of the theme issue 'Shortcuts to adiabaticity: theoretical, experimental and interdisciplinary perspectives'.
Keyphrases
  • molecular dynamics
  • machine learning
  • nk cells
  • deep learning
  • energy transfer
  • monte carlo
  • neural network