Optimization by Quantum Annealing: Lessons from hard 3-SAT cases

Details Optimization by Quantum Annealing: Lessons from hard 3-SAT cases Optimization by Quantum Annealing: Lessons from hard 3-SAT cases

2005-02-18

arxiv.org/abs/cond-mat/0502468v1

Phys. Rev. E 71, 066707 (2005)

Physics

Condensed Matter

Disordered Systems and Neural Networks

10 pages, 6 figures, submitted to PRE

Scientific paper

10.1103/PhysRevE.71.066707

The Path Integral Monte Carlo simulated Quantum Annealing algorithm is applied to the optimization of a large hard instance of the Random 3-SAT Problem (N=10000). The dynamical behavior of the quantum and the classical annealing are compared, showing important qualitative differences in the way of exploring the complex energy landscape of the combinatorial optimization problem. At variance with the results obtained for the Ising spin glass and for the Traveling Salesman Problem, in the present case the linear-schedule Quantum Annealing performance is definitely worse than Classical Annealing. Nevertheless, a quantum cooling protocol based on field-cycling and able to outperform standard classical simulated annealing over short time scales is introduced.

Affiliated with

Also associated with

No associations

Rating

Optimization by Quantum Annealing: Lessons from hard 3-SAT cases does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Optimization by Quantum Annealing: Lessons from hard 3-SAT cases, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optimization by Quantum Annealing: Lessons from hard 3-SAT cases will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-387828