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Statistical Aspects of the Quantum Supremacy Demonstration

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arxiv 2008.05177 v3 pith:EDDQ5JJV submitted 2020-08-12 quant-ph cs.CCmath.STstat.TH

classification quant-phcs.CCmath.STstat.TH
keywords quantumstatisticalgooglenoisesupremacyaspectscircuitcomputer
verification ladder T0 review T1 audit T2 compute T3 formal
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The notable claim of quantum supremacy presented by Google's team in 2019 consists of demonstrating the ability of a quantum circuit to generate, albeit with considerable noise, bitstrings from a distribution that is considered hard to simulate on classical computers. Verifying that the generated data is indeed from the claimed distribution and assessing the circuit's noise level and its fidelity is a purely statistical undertaking. The objective of this paper is to explain the relations between quantum computing and some of the statistical aspects involved in demonstrating quantum supremacy in terms that are accessible to statisticians, computer scientists, and mathematicians. Starting with the statistical analysis in Google's demonstration, which we explain, we study various estimators of the fidelity, and different approaches to testing the distributions generated by the quantum computer. We propose different noise models, and discuss their implications. A preliminary study of the Google data, focusing mostly on circuits of 12 and 14 qubits is discussed throughout the paper.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Generalized Cross-Entropy Benchmarking for Random Circuits with Ergodicity

    quant-ph 2025-02 conditional novelty 5.0 of 10

    Random circuits satisfy an ergodicity condition for positive-coefficient polynomials, and its deviation can benchmark quantum chip fidelity, recovering and generalizing linear cross-entropy benchmarking.

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