Please use this identifier to cite or link to this item:
Title: Probabilistic solving of NP-hard problems with bistable nonlinear optical networks
Authors: Kyriienko, O.
Sigurdsson, H.
Liew, Timothy Chi Hin
Keywords: Quantum Wells
Issue Date: 2019
Source: Kyriienko, O., Sigurdsson, H., & Liew, T. C. H. (2019). Probabilistic solving of NP-hard problems with bistable nonlinear optical networks. Physical Review B, 99(19). doi:10.1103/PhysRevB.99.195301
Series/Report no.: Physical Review B
Abstract: We study theoretically a lattice of locally bistable driven-dissipative nonlinear cavities. The system is found to resemble the classical Ising model and enables its effective simulation. First, we benchmark the performance of driven-dissipative nonlinear cavities for spin-glass problems, and study the scaling of the ground-state-energy deviation and success probability as a function of system size. Next, we show how an effective bias field can be included in an optical model and use it for probabilistic solving of optimization problems. As particular examples we consider NP-hard problems embedded in the Ising model, namely graph partitioning and the knapsack problem. Finally, we confirm that locally bistable polariton networks act as classical optimizers and can potentially provide an improvement within the exponential complexity class.
ISSN: 2469-9950
DOI: 10.1103/PhysRevB.99.195301
Rights: © 2019 American Physical Society (APS). All rights reserved. This paper was published in Physical Review B and is made available with permission of American Physical Society (APS).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

Files in This Item:
File Description SizeFormat 
Probabilistic solving of NP-hard problems with bistable nonlinear optical networks.pdf1.83 MBAdobe PDFThumbnail

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.