A functionally reversible probabilistic computing architecture enabled by interactions of current-controlled magnetic devices

TL;DR

This paper introduces a novel magnetic device-based probabilistic computing architecture that enables reversible, bidirectional logic operations, including a full-adder, with improved speed and energy efficiency for solving complex problems.

Contribution

The authors develop a physical implementation using magnetic disks with geometry-dependent interactions to emulate logic gates and demonstrate a reversible full-adder, advancing probabilistic computing hardware.

Findings

Magnetic interactions enable logic gate emulation.

Chained gates perform reversible full-adder operations.

The system offers improved speed and energy efficiency.

Abstract

Probabilistic computers replace logic gates with networks of interacting random variables, creating bidirectional systems that can back-derive inputs from outputs. Such architectures enable efficient generation of random samples, implementations of novel algorithms, and natural solutions to classically hard problems such as prime factorization. We present a new physical implementation for these networks: ferromagnetic disks whose magnetization switching process is triggered by current pulses, skewed by external magnetic fields, and randomized by ambient thermal noise. We show that geometry-dependent magnetostatic interactions between these magnetic cells lead to system behavior that emulates deterministic logic gates. Furthermore, by chaining multiple "gates," we achieve a highly accurate bidirectional one-bit full-adder, a proof of concept for complex multi-gate logic functions with reversible information flow. This analog magnetic probabilistic computer methodology improves on other implementations in speed, tunability, and energy efficiency, thereby enabling a powerful new pathway towards practical solution of classically hard problems.