Speedup for quantum optimal control from automatic differentiation based on graphics processing units

Nelson Leung, Mohamed Abdelhafez, Jens Koch, David Schuster

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

We implement a quantum optimal control algorithm based on automatic differentiation and harness the acceleration afforded by graphics processing units (GPUs). Automatic differentiation allows us to specify advanced optimization criteria and incorporate them in the optimization process with ease. We show that the use of GPUs can speedup calculations by more than an order of magnitude. Our strategy facilitates efficient numerical simulations on affordable desktop computers and exploration of a host of optimization constraints and system parameters relevant to real-life experiments. We demonstrate optimization of quantum evolution based on fine-grained evaluation of performance at each intermediate time step, thus enabling more intricate control on the evolution path, suppression of departures from the truncated model subspace, as well as minimization of the physical time needed to perform high-fidelity state preparation and unitary gates.

Original languageEnglish (US)
Article number042318
JournalPhysical Review A
Volume95
Issue number4
DOIs
StatePublished - Apr 13 2017

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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