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Trapped Ion Quantum Computing Quantum Machine Learning

Probability vector representation of the Schrödinger equation and Leggett-Garg-type experiments

arXiv
Authors: Masahiro Hotta, Sebastian Murk

Year

2023

Paper ID

53050

Status

Preprint

Abstract Read

~2 min

Abstract Words

230

Citations

N/A

Abstract

Leggett-Garg inequalities place bounds on the temporal correlations of a system based on the principles of macroscopic realism textit{per se} and noninvasive measurability. Their conventional formulation relies on the ensemble-averaged products of observables measured at different instants of time. However, a complete description that enables a precise understanding and captures all physically relevant features requires the study of probability distributions associated with noncommuting observables. In this article, we propose a scheme to describe the dynamics of generic N-level quantum systems ("qudits") via a probability vector representation of the Schrödinger equation and define a precise notion of no-signaling in time (NSIT) for the probability distributions of noncommuting observables. This provides a systematic way of identifying the interferences responsible for nonclassical behavior. In addition, we introduce an interference witness measure to quantify violations of NSIT for arbitrary general probabilistic states. For single-qubit systems, we pinpoint the pivotal relation that establishes a connection between the disturbance of observables incurred during a measurement and the resulting NSIT violation. For large-N systems where a manual determination is infeasible, the classification of states as either NSIT-conforming or NSIT-violating may be performed by a machine learning algorithm. We present a proof-of-principle implementation of such an algorithm in which the classifier function is prepared via supervised learning using pseudorandomly generated training data sets composed of states whose corresponding classifications are known textit{a priori}.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • Leggett-Garg inequalities place bounds on the temporal correlations of a system based on the principles of macroscopic realism per se and noninvasive measurability.

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