Accelerating Continuous Variable Coherent Ising Machines via Momentum

• URL: http://arxiv.org/abs/2401.12135v1
• Date: Mon, 22 Jan 2024 17:18:53 GMT
• Title: Accelerating Continuous Variable Coherent Ising Machines via Momentum
• Authors: Robin Brown, Davide Venturelli, Marco Pavone, and David E. Bernal Neira
• Abstract summary: We propose to modify CV-CIM dynamics using more tunable optimization techniques such as momentum and Adam. We show that momentum and Adam-CIM's and sample Adam-CV-CIM's performance is more stable as an tunable framework.
• Score: 16.545815849819043
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The Coherent Ising Machine (CIM) is a non-conventional architecture that takes inspiration from physical annealing processes to solve Ising problems heuristically. Its dynamics are naturally continuous and described by a set of ordinary differential equations that have been proven to be useful for the optimization of continuous variables non-convex quadratic optimization problems. The dynamics of such Continuous Variable CIMs (CV-CIM) encourage optimization via optical pulses whose amplitudes are determined by the negative gradient of the objective; however, standard gradient descent is known to be trapped by local minima and hampered by poor problem conditioning. In this work, we propose to modify the CV-CIM dynamics using more sophisticated pulse injections based on tried-and-true optimization techniques such as momentum and Adam. Through numerical experiments, we show that the momentum and Adam updates can significantly speed up the CV-CIM's convergence and improve sample diversity over the original CV-CIM dynamics. We also find that the Adam-CV-CIM's performance is more stable as a function of feedback strength, especially on poorly conditioned instances, resulting in an algorithm that is more robust, reliable, and easily tunable. More broadly, we identify the CIM dynamical framework as a fertile opportunity for exploring the intersection of classical optimization and modern analog computing.

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