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    • Quantum State Inference Via Permutations In Hidden Markov Models

    Metadata Updated: July 29, 2022

    This Python software package provides functionality for inference of the initial state of a Hidden Markov Model (HMM), when we have access to permutations of the underlying states. We provide both analytical calculations to compute the probability of correct inference, and functionality for Monte Carlo computations. Further details are provided in arxiv:xxxx.xxxxxx.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    Dates

    Metadata Created Date June 22, 2022
    Metadata Updated Date July 29, 2022

    Metadata Source

    Harvested from NIST

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date June 22, 2022
    Metadata Updated Date July 29, 2022
    Publisher National Institute of Standards and Technology
    Maintainer
    Identifier ark:/88434/mds2-2573
    Data First Published 2022-03-21
    Language en
    Data Last Modified 2022-03-08 00:00:00
    Category Physics:Quantum information science, Physics:Atomic, molecular, and quantum, Mathematics and Statistics:Statistical analysis, Mathematics and Statistics:Numerical methods and software
    Public Access Level public
    Bureau Code 006:55
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 3c15d5bb-aad0-4b04-b731-2e768c3d3739
    Harvest Source Id 74e175d9-66b3-4323-ac98-e2a90eeb93c0
    Harvest Source Title NIST
    Homepage URL https://github.com/usnistgov/perm_hmm
    License https://www.nist.gov/open/license
    Program Code 006:045
    Source Datajson Identifier True
    Source Hash 6581d1a708feff14193efed0ba0c5a9804b5cce2
    Source Schema Version 1.1

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