Learning the dynamics of open quantum systems from their steady states

Abstract

Recent works have shown that generic local Hamiltonians can be efficiently inferred from local measurements performed on their eigenstates or thermal states. Realistic quantum systems are often affected by dissipation and decoherence due to coupling to an external environment. This raises the question whether the steady states of such open quantum systems contain sufficient information allowing for full and efficient reconstruction of the system’s dynamics. We find that such a reconstruction is possible for generic local Markovian dynamics. We propose a recovery method that uses only local measurements; for systems with finite-range interactions, the method recovers the Lindbladian acting on each spatial domain using only observables within that domain. We numerically study the accuracy of the reconstruction as a function of the number of measurements, type of open-system dynamics and system size. Interestingly, we show that couplings to external environments can in fact facilitate the reconstruction of Hamiltonians composed of commuting terms.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 01, 2020
Source ID
10.1088/1367-2630/ab73cd

Entities

People

  • Chu Guo
  • Dario Poletti
  • Eyal Bairey
  • Itai Arad
  • Netanel H. Lindner

Organizations

  • Defense Advanced Research Projects Agency
  • Israel Science Foundation
  • Marie Skłodowska-Curie Actions

Tags

Fields of Study

  • Physics

Readers

  • Control Systems Engineering.
  • Neural Network Machine Learning.
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Quantum Computing