Quantum Manifold Learning

RESOURCE

Abstract

SAND2022-12600 O Quantum Manifold Learning is a Python code to perform manifold learning from point clouds. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Developers:
Sarovar, Mohan [1][2][3] Kumar, Akshat [4]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
  4. Omar Little Solutions
Release Date:
2022-08-04
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python3
Cuda
Version:
0.9
Licenses:
MIT License
Sponsoring Org.:
Code ID:
94975
Site Accession Number:
SCR #2809
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

RESOURCE

Citation Formats

Sarovar, Mohan, and Kumar, Akshat. Quantum Manifold Learning. Computer Software. https://github.com/sandialabs/QML. USDOE. 04 Aug. 2022. Web. doi:10.11578/dc.20240910.4.
Sarovar, Mohan, & Kumar, Akshat. (2022, August 04). Quantum Manifold Learning. [Computer software]. https://github.com/sandialabs/QML. https://doi.org/10.11578/dc.20240910.4.
Sarovar, Mohan, and Kumar, Akshat. "Quantum Manifold Learning." Computer software. August 04, 2022. https://github.com/sandialabs/QML. https://doi.org/10.11578/dc.20240910.4.
@misc{ doecode_94975,
title = {Quantum Manifold Learning},
author = {Sarovar, Mohan and Kumar, Akshat},
abstractNote = {SAND2022-12600 O Quantum Manifold Learning is a Python code to perform manifold learning from point clouds. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.},
doi = {10.11578/dc.20240910.4},
url = {https://doi.org/10.11578/dc.20240910.4},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240910.4}},
year = {2022},
month = {aug}
}