Software & Data Downloads — TEAQC

Template Embeddings for Adiabatic Quantum Computation for Adiabatic Quantum Computation (TEAQC) for searching for an embedding of a problem graph into certain classes of minors of the Quantum Annealing hardware.

Quantum Annealing (QA) can be used to quickly obtain near-optimal solutions for Quadratic Unconstrained Binary Optimization (QUBO) problems. In QA hardware, each decision variable of a QUBO should be mapped to one or more adjacent qubits in such a way that pairs of variables defining a quadratic term in the objective function are mapped to some pair of adjacent qubits. However, qubits have limited connectivity in existing QA hardware. This software Python codes implementing integer linear programs to search for an embedding of the problem graph into certain classes of minors of the QA hardware, which we call template embeddings. In particular, we consider the template embedding that are minors of the Chimera graph used in D-Wave processors. The software implements the Bipartite TE (BTE) and the Quadripartite TE (QTE), as a generalization of BTE.

  •  Serra, T., Huang, T., Raghunathan, A., Bergman, D., "Template-based Minor Embedding for Adiabatic Quantum Optimization", INFORMS Journal on Computing, DOI: 10.1287/​ijoc.2021.1065, Vol. 34, No. 1, pp. 427–439, December 2020.
    BibTeX TR2020-181 PDF Data Software
    • @article{Serra2020dec,
    • author = {Serra, Thiago and Huang, Teng and Raghunathan, Arvind and Bergman, David},
    • title = {Template-based Minor Embedding for Adiabatic Quantum Optimization},
    • journal = {INFORMS Journal on Computing},
    • year = 2020,
    • volume = 34,
    • number = 1,
    • pages = {427–439},
    • month = dec,
    • doi = {10.1287/ijoc.2021.1065},
    • url = {https://www.merl.com/publications/TR2020-181}
    • }

Access software at https://github.com/merlresearch/TEAQC.

Access data at https://doi.org/10.5281/zenodo.7871403.