Predicting many properties of a quantum system from very few measurements

Predicting the properties of complex, large-scale quantum systems is essential for developing quantum technologies. We present an efficient method for constructing an approximate classical description of a quantum state using very few measurements of the state. This description, called a ‘classical...

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Published inNature physics Vol. 16; no. 10; pp. 1050 - 1057
Main Authors Huang, Hsin-Yuan, Kueng, Richard, Preskill, John
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 01.10.2020
Nature Publishing Group
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Abstract Predicting the properties of complex, large-scale quantum systems is essential for developing quantum technologies. We present an efficient method for constructing an approximate classical description of a quantum state using very few measurements of the state. This description, called a ‘classical shadow’, can be used to predict many different properties; order log ( M ) measurements suffice to accurately predict M different functions of the state with high success probability. The number of measurements is independent of the system size and saturates information-theoretic lower bounds. Moreover, target properties to predict can be selected after the measurements are completed. We support our theoretical findings with extensive numerical experiments. We apply classical shadows to predict quantum fidelities, entanglement entropies, two-point correlation functions, expectation values of local observables and the energy variance of many-body local Hamiltonians. The numerical results highlight the advantages of classical shadows relative to previously known methods. An efficient method has been proposed through which the properties of a complex, large-scale quantum system can be predicted without fully characterizing the quantum state.
AbstractList Predicting the properties of complex, large-scale quantum systems is essential for developing quantum technologies. We present an efficient method for constructing an approximate classical description of a quantum state using very few measurements of the state. This description, called a ‘classical shadow’, can be used to predict many different properties; order log ( M ) measurements suffice to accurately predict M different functions of the state with high success probability. The number of measurements is independent of the system size and saturates information-theoretic lower bounds. Moreover, target properties to predict can be selected after the measurements are completed. We support our theoretical findings with extensive numerical experiments. We apply classical shadows to predict quantum fidelities, entanglement entropies, two-point correlation functions, expectation values of local observables and the energy variance of many-body local Hamiltonians. The numerical results highlight the advantages of classical shadows relative to previously known methods. An efficient method has been proposed through which the properties of a complex, large-scale quantum system can be predicted without fully characterizing the quantum state.
Predicting the properties of complex, large-scale quantum systems is essential for developing quantum technologies. We present an efficient method for constructing an approximate classical description of a quantum state using very few measurements of the state. This description, called a ‘classical shadow’, can be used to predict many different properties; order log(M) measurements suffice to accurately predict M different functions of the state with high success probability. The number of measurements is independent of the system size and saturates information-theoretic lower bounds. Moreover, target properties to predict can be selected after the measurements are completed. We support our theoretical findings with extensive numerical experiments. We apply classical shadows to predict quantum fidelities, entanglement entropies, two-point correlation functions, expectation values of local observables and the energy variance of many-body local Hamiltonians. The numerical results highlight the advantages of classical shadows relative to previously known methods.An efficient method has been proposed through which the properties of a complex, large-scale quantum system can be predicted without fully characterizing the quantum state.
Author Kueng, Richard
Preskill, John
Huang, Hsin-Yuan
Author_xml – sequence: 1
  givenname: Hsin-Yuan
  orcidid: 0000-0001-5317-2613
  surname: Huang
  fullname: Huang, Hsin-Yuan
  email: hsinyuan@caltech.edu
  organization: Institute for Quantum Information and Matter, California Institute of Technology, Department of Computing and Mathematical Sciences, California Institute of Technology
– sequence: 2
  givenname: Richard
  surname: Kueng
  fullname: Kueng, Richard
  organization: Institute for Quantum Information and Matter, California Institute of Technology, Department of Computing and Mathematical Sciences, California Institute of Technology, Institute for Integrated Circuits, Johannes Kepler University Linz
– sequence: 3
  givenname: John
  surname: Preskill
  fullname: Preskill, John
  organization: Institute for Quantum Information and Matter, California Institute of Technology, Department of Computing and Mathematical Sciences, California Institute of Technology, Walter Burke Institute for Theoretical Physics, California Institute of Technology
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PublicationTitle Nature physics
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Snippet Predicting the properties of complex, large-scale quantum systems is essential for developing quantum technologies. We present an efficient method for...
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SubjectTerms 639/705
639/766/259
639/766/483
639/766/483/481
639/766/483/640
Approximation
Atomic
Circuits
Classical and Continuum Physics
Complex Systems
Condensed Matter Physics
Entropy
Hamiltonian functions
Information theory
Lower bounds
Mathematical and Computational Physics
Molecular
Optical and Plasma Physics
Physics
Physics and Astronomy
Properties (attributes)
Quantum entanglement
Quantum theory
Shadows
Theoretical
Tomography
Title Predicting many properties of a quantum system from very few measurements
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