Efficiently embedding QUBO problems on adiabatic quantum computers
Abstract
Adiabatic quantum computers like the D-Wave 2000Q can approximately solve the QUBO problem, which is an NP-hard problem, and have been shown to outperform classical computers on several instances. Solving the QUBO problem literally means solving virtually any NP-hard problem like the traveling salesman problem, airline scheduling problem, protein folding problem, genotype imputation problem, thereby enabling significant scientific progress, and potentially saving millions/billions of dollars in logistics, airlines, healthcare and many other industries. Yet, before QUBO problems are solved on quantum computers, they must be embedded (or compiled) onto the hardware of quantum computers, which in itself is a very hard problem. Here, we propose an efficient embedding algorithm, that lets us embed QUBO problems fast, uses less qubits and gets the objective function value close to the global minimum value. We then compare the performance of our embedding algorithm to that of D-Wave’s embedding algorithm, which is the current state of the art, and show that our embedding algorithm convincingly outperforms D-Wave’s embedding algorithm. Our embedding approach works with perfect Chimera graphs, i.e., Chimera graphs with no missing qubits.
- Authors:
-
[1];
[2];
[2];
[2]
- Rensselaer Polytechnic Inst., Troy, NY (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- OSTI Identifier:
- 1557505
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Quantum Information Processing
- Additional Journal Information:
- Journal Volume: 18; Journal Issue: 4; Journal ID: ISSN 1570-0755
- Publisher:
- Springer
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; Adiabatic quantum computing; Embedding; Quadratic unconstrained binary optimization (QUBO)
Citation Formats
Date, Prasanna, Patton, Robert, Schuman, Catherine, and Potok, Thomas. Efficiently embedding QUBO problems on adiabatic quantum computers. United States: N. p., 2019.
Web. doi:10.1007/s11128-019-2236-3.
Date, Prasanna, Patton, Robert, Schuman, Catherine, & Potok, Thomas. Efficiently embedding QUBO problems on adiabatic quantum computers. United States. https://doi.org/10.1007/s11128-019-2236-3
Date, Prasanna, Patton, Robert, Schuman, Catherine, and Potok, Thomas. Tue .
"Efficiently embedding QUBO problems on adiabatic quantum computers". United States. https://doi.org/10.1007/s11128-019-2236-3. https://www.osti.gov/servlets/purl/1557505.
@article{osti_1557505,
title = {Efficiently embedding QUBO problems on adiabatic quantum computers},
author = {Date, Prasanna and Patton, Robert and Schuman, Catherine and Potok, Thomas},
abstractNote = {Adiabatic quantum computers like the D-Wave 2000Q can approximately solve the QUBO problem, which is an NP-hard problem, and have been shown to outperform classical computers on several instances. Solving the QUBO problem literally means solving virtually any NP-hard problem like the traveling salesman problem, airline scheduling problem, protein folding problem, genotype imputation problem, thereby enabling significant scientific progress, and potentially saving millions/billions of dollars in logistics, airlines, healthcare and many other industries. Yet, before QUBO problems are solved on quantum computers, they must be embedded (or compiled) onto the hardware of quantum computers, which in itself is a very hard problem. Here, we propose an efficient embedding algorithm, that lets us embed QUBO problems fast, uses less qubits and gets the objective function value close to the global minimum value. We then compare the performance of our embedding algorithm to that of D-Wave’s embedding algorithm, which is the current state of the art, and show that our embedding algorithm convincingly outperforms D-Wave’s embedding algorithm. Our embedding approach works with perfect Chimera graphs, i.e., Chimera graphs with no missing qubits.},
doi = {10.1007/s11128-019-2236-3},
journal = {Quantum Information Processing},
number = 4,
volume = 18,
place = {United States},
year = {Tue Mar 05 00:00:00 EST 2019},
month = {Tue Mar 05 00:00:00 EST 2019}
}
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