The Discrete Langevin Machine: Bridging the Gap Between Thermodynamic and Neuromorphic Systems
Neural and Evolutionary Computing
2021-04-08 v3 High Energy Physics - Lattice
Computational Physics
Abstract
A formulation of Langevin dynamics for discrete systems is derived as a class of generic stochastic processes. The dynamics simplify for a two-state system and suggest a network architecture which is implemented by the Langevin machine. The Langevin machine represents a promising approach to compute successfully quantitative exact results of Boltzmann distributed systems by LIF neurons. Besides a detailed introduction of the dynamics, different simplified models of a neuromorphic hardware system are studied with respect to a control of emerging sources of errors.
Keywords
Cite
@article{arxiv.1901.05214,
title = {The Discrete Langevin Machine: Bridging the Gap Between Thermodynamic and Neuromorphic Systems},
author = {Lukas Kades and Jan M. Pawlowski},
journal= {arXiv preprint arXiv:1901.05214},
year = {2021}
}
Comments
25 pages, 16 figures