This title appears in the Scientific Report :
2019
Please use the identifier:
http://dx.doi.org/10.4208/cicp.OA-2018-0257 in citations.
Quantum Annealing with Anneal Path Control: Application to 2-SAT Problems with Known Energy Landscapes
Quantum Annealing with Anneal Path Control: Application to 2-SAT Problems with Known Energy Landscapes
We study the effect of the anneal path control per qubit, a new user control feature offered on the D-Wave 2000Q quantum annealer, on the performance of quantum annealing for solving optimization problems by numerically solving the timedependent Schr ¨odinger equation for the time-dependent Hamilton...
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Personal Name(s): | Hsu, Ting-Jui |
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Jin, Fengping / Seidel, Christian / Neukart, Florian / Raedt, Hans De / Michielsen, Kristel (Corresponding author) | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Published in: | Communications in computational physics, 26 (2019) 3, S. 928 - 946 |
Imprint: |
Hong Kong
Global Science Press
2019
|
DOI: |
10.4208/cicp.OA-2018-0257 |
Document Type: |
Journal Article |
Research Program: |
Computational Science and Mathematical Methods |
Publikationsportal JuSER |
We study the effect of the anneal path control per qubit, a new user control feature offered on the D-Wave 2000Q quantum annealer, on the performance of quantum annealing for solving optimization problems by numerically solving the timedependent Schr ¨odinger equation for the time-dependent Hamiltonian modeling the annealing problems. The anneal path control is thereby modeled as a modified linear annealing scheme, resulting in an advanced and retarded scheme. The considered optimization problems are 2-SAT problems with 12 Boolean variables, a known unique ground state and a highly degenerate first excited state. We show that adjustment of the anneal path control can result in a widening of the minimal spectral gap by one or two orders of magnitude and an enhancement of the success probability of finding the solution of the optimization problem. We scrutinize various iterative methods based on the spin floppiness, the average spin value, and on the average energy and describe their performance in boosting the quantum annealing process. |