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Quantum State Inference Via Permutations In Hidden Markov Models
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.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Scott Glancy",
"hasEmail": "mailto:scott.glancy@nist.gov"
}
|
| description | 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. |
| distribution |
[
{
"title": "Github Repository",
"format": "Python code",
"accessURL": "https://github.com/usnistgov/perm_hmm",
"description": "Github repository of Python code for quantum state inference via permutations in Hidden Markov Models"
}
]
|
| identifier | ark:/88434/mds2-2573 |
| issued | 2022-03-21 |
| keyword |
[
"hidden markov model",
"quantum information theory",
"quantum measurement",
"trapped ion"
]
|
| landingPage | https://github.com/usnistgov/perm_hmm |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2022-03-08 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| theme |
[
"Mathematics and Statistics:Numerical methods and software",
"Mathematics and Statistics:Statistical analysis",
"Physics:Atomic, molecular, and quantum",
"Physics:Quantum information science"
]
|
| title | Quantum State Inference Via Permutations In Hidden Markov Models |
