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Inferring physical properties of symmetric states from the fewest copies

Authors :
Zhang, Da-Jian
Tong, D. M.
Publication Year :
2023

Abstract

Learning physical properties of high-dimensional states is crucial for developing quantum technologies but usually consumes an exceedingly large number of samples which are difficult to afford in practice. In this Letter, we use the methodology of quantum metrology to tackle this difficulty, proposing a strategy built upon entangling measurements for dramatically reducing sample complexity. The strategy, whose characteristic feature is symmetrization of observables, is powered by the exploration of symmetric structures of states which are ubiquitous in physics. It is provably optimal under some natural assumption, efficiently implementable in a variety of contexts, and capable of being incorporated into existing methods as a basic building block. We apply the strategy to different scenarios motivated by experiments, demonstrating exponential reductions in sample complexity.<br />throughly revised, 4+8 pages, 1 figure

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....0ac6c767510e5417c72e06507cca77d2