WO2023167707A3 - System and method for quantum computing to generate joint probability distributions - Google Patents

System and method for quantum computing to generate joint probability distributions Download PDF

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Publication number
WO2023167707A3
WO2023167707A3 PCT/US2022/040415 US2022040415W WO2023167707A3 WO 2023167707 A3 WO2023167707 A3 WO 2023167707A3 US 2022040415 W US2022040415 W US 2022040415W WO 2023167707 A3 WO2023167707 A3 WO 2023167707A3
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WO
WIPO (PCT)
Prior art keywords
probability distributions
joint probability
quantum
variables
computation
Prior art date
Application number
PCT/US2022/040415
Other languages
French (fr)
Other versions
WO2023167707A2 (en
Inventor
Sonika Johri
David Bacon
Original Assignee
IonQ, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US17/888,077 external-priority patent/US20230051669A1/en
Application filed by IonQ, Inc. filed Critical IonQ, Inc.
Priority to CN202280056413.4A priority Critical patent/CN117859138A/en
Publication of WO2023167707A2 publication Critical patent/WO2023167707A2/en
Publication of WO2023167707A3 publication Critical patent/WO2023167707A3/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N10/00—Quantum computing, i.e. information processing based on quantum-mechanical phenomena
    • G06N10/60—Quantum algorithms, e.g. based on quantum optimisation, quantum Fourier or Hadamard transforms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N10/00—Quantum computing, i.e. information processing based on quantum-mechanical phenomena
    • G06N10/20—Models of quantum computing, e.g. quantum circuits or universal quantum computers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0475—Generative networks

Abstract

Aspects of the present disclosure relate generally to systems and methods for use in the implementation and/or operation of quantum information processing (QIP) systems, and more particularly, to the computation of joint probability distributions with quantum computers. Improvements in the computation of joint probability distributions are described by designing quantum machine learning algorithms to model copulas. Moreover, any copula is shown to be naturally mapped to a multipartite maximally entangled state. A variational ansatz referred to herein as a "qopula" creates arbitrary correlations between variables while maintaining the copula structure starting from a set of Bell pairs for two variables, or Greenberger-Home-Zeilinger (GHZ) states for multiple variables. Generative learning algorithms may be demonstrated on quantum computers, and more particularly, in trapped-ion quantum computers. The approach described herein is shown to have advantages over classical models.
PCT/US2022/040415 2021-08-16 2022-08-16 System and method for quantum computing to generate joint probability distributions WO2023167707A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202280056413.4A CN117859138A (en) 2021-08-16 2022-08-16 System and method for quantum computation to generate joint probability distributions

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US202163233537P 2021-08-16 2021-08-16
US63/233,537 2021-08-16
US17/888,077 2022-08-15
US17/888,077 US20230051669A1 (en) 2021-08-16 2022-08-15 System and method for quantum computing to generate joint probability distributions

Publications (2)

Publication Number Publication Date
WO2023167707A2 WO2023167707A2 (en) 2023-09-07
WO2023167707A3 true WO2023167707A3 (en) 2023-11-23

Family

ID=87557853

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2022/040415 WO2023167707A2 (en) 2021-08-16 2022-08-16 System and method for quantum computing to generate joint probability distributions

Country Status (1)

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WO (1) WO2023167707A2 (en)

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
ELTON YECHAO ZHU ET AL: "Generative Quantum Learning of Joint Probability Distribution Functions", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 13 September 2021 (2021-09-13), XP091053259 *
HAO TANG ET AL: "Quantum Computation for Pricing the Collateral Debt Obligations", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 6 August 2020 (2020-08-06), XP081736145 *
JANUSZ MILEK: "Quantum Implementation of Risk Analysis-relevant Copulas", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 18 February 2020 (2020-02-18), XP081602079 *
KRZYSZTOF DOMINO: "Selected Methods for non-Gaussian Data Analysis", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 23 November 2018 (2018-11-23), XP081018145 *

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