15565

Predicting Many Properties of a Quantum System from Very Few Measurements

APA

(2020). Predicting Many Properties of a Quantum System from Very Few Measurements. The Simons Institute for the Theory of Computing. https://simons.berkeley.edu/talks/predicting-many-properties-quantum-system-very-few-measurements

MLA

Predicting Many Properties of a Quantum System from Very Few Measurements. The Simons Institute for the Theory of Computing, Mar. 30, 2020, https://simons.berkeley.edu/talks/predicting-many-properties-quantum-system-very-few-measurements

BibTex

          @misc{ scivideos_15565,
            doi = {},
            url = {https://simons.berkeley.edu/talks/predicting-many-properties-quantum-system-very-few-measurements},
            author = {},
            keywords = {},
            language = {en},
            title = {Predicting Many Properties of a Quantum System from Very Few Measurements},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2020},
            month = {mar},
            note = {15565 see, \url{https://scivideos.org/Simons-Institute/15565}}
          }
          
Richard Kueng (Caltech)
Talk number15565
Source RepositorySimons Institute

Abstract

Predicting 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. This is joint work with Hsin-Yuan Huang and John Preskill.