Volume 26, Issue 3
Quantum Annealing with Anneal Path Control: Application to 2-SAT Problems with Known Energy Landscapes

Ting-Jui Hsu, Fengping Jin, Christian Seidel, Florian Neukart, Hans De Raedt & Kristel Michielsen

Commun. Comput. Phys., 26 (2019), pp. 928-946.

Published online: 2019-04

[An open-access article; the PDF is free to any online user.]

Preview Full PDF 30 1317
Export citation
  • Abstract

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.

  • Keywords

2-SAT, D-Wave, anneal offset, quantum annealing, adiabatic quantum computing

  • AMS Subject Headings

03.65.-w, 02.50.Cw

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • References
  • Hide All
    View All

  • BibTex
  • RIS
  • TXT
@Article{CiCP-26-928, author = {}, title = {Quantum Annealing with Anneal Path Control: Application to 2-SAT Problems with Known Energy Landscapes}, journal = {Communications in Computational Physics}, year = {2019}, volume = {26}, number = {3}, pages = {928--946}, abstract = {

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.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2018-0257}, url = {http://global-sci.org/intro/article_detail/cicp/13153.html} }
TY - JOUR T1 - Quantum Annealing with Anneal Path Control: Application to 2-SAT Problems with Known Energy Landscapes JO - Communications in Computational Physics VL - 3 SP - 928 EP - 946 PY - 2019 DA - 2019/04 SN - 26 DO - http://dor.org/10.4208/cicp.OA-2018-0257 UR - https://global-sci.org/intro/cicp/13153.html KW - 2-SAT, D-Wave, anneal offset, quantum annealing, adiabatic quantum computing AB -

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.

Ting-Jui Hsu, Fengping Jin, Christian Seidel, Florian Neukart, Hans De Raedt & Kristel Michielsen. (2019). Quantum Annealing with Anneal Path Control: Application to 2-SAT Problems with Known Energy Landscapes. Communications in Computational Physics. 26 (3). 928-946. doi:10.4208/cicp.OA-2018-0257
Copy to clipboard
The citation has been copied to your clipboard