Combining the synergistic control capabilities of modeling and experiments: Illustration of finding a minimum-time quantum objective

Qi Ming Chen, Xiaodong Yang, Christian Arenz, Re Bing Wu, Xinhua Peng, István Pelczer, Herschel Rabitz

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

A common way to manipulate a quantum system, for example spins or artificial atoms, is to use properly tailored control pulses. In order to accomplish quantum information tasks before coherence is lost, it is crucial to implement the control in the shortest possible time. Here we report the near time-optimal preparation of a Bell state with fidelity higher than 99% in an NMR experiment, which is feasible by combining the synergistic capabilities of modeling and experiments operating in tandem. The pulses preparing the Bell state are found by experiments that are recursively assisted with a gradient-based optimization algorithm working with a model. Thus, we exploit the interplay between model-based numerical optimal design and experimental-based learning control. Utilizing the balanced synergism between the dual approaches, as dictated by the case specific capabilities of each approach, should have broad applications for accelerating the search for optimal quantum controls.

Original languageEnglish (US)
Article number032313
JournalPhysical Review A
Volume101
Issue number3
DOIs
StatePublished - Mar 2020

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Combining the synergistic control capabilities of modeling and experiments: Illustration of finding a minimum-time quantum objective'. Together they form a unique fingerprint.

Cite this