Stochastic Thermodynamics of Non-Linear Electronic Circuits: A Realistic Framework for Computing around kT

TL;DR

This paper develops a comprehensive thermodynamic framework for modeling non-linear electronic circuits with stochastic dynamics, enabling analysis of their non-equilibrium behavior and fluctuations relevant for computing at thermal noise levels.

Contribution

It introduces a realistic, thermodynamically consistent stochastic modeling approach for complex electronic circuits, including devices like tunnel junctions and transistors, and applies it to probabilistic computing.

Findings

Stochastic models reveal non-equilibrium fluctuations cause deviations from deterministic transfer functions.

The framework identifies thermodynamic potentials and entropy production in non-linear circuits.

A CMOS-based probabilistic bit design exploits intrinsic noise for stochastic computing.

Abstract

We present a general formalism for the construction of thermodynamically consistent stochastic models of non-linear electronic circuits. The devices constituting the circuit can have arbitrary I-V curves and may include tunnel junctions, diodes, and MOS transistors in subthreshold operation, among others. We provide a full analysis of the stochastic non-equilibrium thermodynamics of these models, identifying the relevant thermodynamic potentials, characterizing the different contributions to the irreversible entropy production, and obtaining different fluctuation theorems. Our work provides a realistic framework to study thermodynamics of computing with electronic circuits. We demonstrate this point by constructing a stochastic model of a CMOS inverter. We find that a deterministic analysis is only compatible with the assumption of equilibrium fluctuations, and analyze how the non-equilibrium fluctuations induce deviations from its deterministic transfer function. Finally, building on the CMOS inverter, we propose a full-CMOS design for a probabilistic bit (or binary stochastic neuron) exploiting intrinsic noise.