Feedback-Driven Ground-State Search in Coupled Laser Arrays
Rajneesh Fulara, Fabien Bretenaker, Vishwa Pal

TL;DR
This paper introduces a feedback-driven annealing method in semiconductor laser arrays that enhances the ability to find ground states in complex energy landscapes, offering a scalable approach for solving hard optimization problems.
Contribution
It demonstrates a novel intrinsic feedback mechanism in laser arrays that enables effective escape from local minima during ground-state searches, with tunable timescales controlling defect suppression.
Findings
Nearly 100% ground-state probability achieved in experiments.
Defect suppression governed by the ratio of amplitude stabilization and phase locking timescales.
Identical timescale ratios lead to similar defect probabilities, independent of specific parameters.
Abstract
Optimisation problems, which appear in numerous fields of science and industry, are challenging to solve even with modern supercomputers. Many such problems can be mapped onto ground-state searches of spin Hamiltonians, implemented on various physical platforms whose intrinsic dynamics are analogous to spin systems. However, the complex energy landscape of spin Hamiltonians often traps the system in local minima, preventing the system from reaching the ground-state (global minimum). We demonstrate an intrinsic feedback-driven annealing mechanism in class-B semiconductor laser arrays arising from the interplay of internal () and external () coupling. The instantaneous phase configuration self-modulates amplitude fluctuations, which act as an effective temperature, dynamically reshaping the potential and enabling the system to escape from local minima. Using a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeural Networks and Reservoir Computing · Quantum Computing Algorithms and Architecture · Quantum Information and Cryptography
