Repository for the paper Advanced unembedding techniques for quantum annealers
QUBO_Ising_formulation_generators.pycontains functions which can generate QUBOs or Isings for the four NP-Hard problems that are studied, given in an input Networkx graph.custom_Minimum_Vertex_Cover_unembed.pycontains all source code for the custom unembedding algorithm for quantum annealer samples from minor embedded Minimum Vertex Cover problemscustom_Graph_Partitioning_unembed.pycontains all source code for the custom unembedding algorithm for quantum annealer samples from minor embedded Graph Partitioning problemscustom_Maximum_Cut_unembed.pycontains all source code for the custom unembedding algorithm for quantum annealer samples from minor embedded Maximum Cut problemscustom_Minimum_Vertex_Cover_unembed.pycontains all source code for the custom unembedding algorithm for quantum annealer samples from minor embedded Maximum Clique problems
- Elijah Pelofske: Information Sciences, Los Alamos National Laboratory
- Georg Hahn: T.H. Chan School of Public Health, Harvard University
- Hristo Djidjev: Information Sciences, Los Alamos National Laboratory and Institute of Information and Communication Technologies, Sofia, Bulgaria
@article{Pelofske_2020_unembedding,
doi = {10.1109/icrc2020.2020.00001},
url = {https://doi.org/10.1109%2Ficrc2020.2020.00001},
archiveprefix = {arXiv},
eprint = {2009.05028},
year = {2020},
month = {dec},
publisher = {{IEEE}},
author = {Elijah Pelofske and Georg Hahn and Hristo Djidjev},
title = {Advanced unembedding techniques for quantum annealers},
booktitle = {2020 International Conference on Rebooting Computing ({ICRC})}
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