Probabilistic computing with p-bits

Digital computers store information in the form of bits that can take on one of two values 0 and 1, while quantum computers are based on qubits that are described by a complex wavefunction, whose squared magnitude gives the probability of measuring either 0 or 1. Here, we make the case for a probabilistic computer based on p-bits, which take on values 0 and 1 with controlled probabilities and can be implemented with specialized compact energy-efficient hardware. We propose a generic architecture for such p-computers and emulate systems with thousands of p-bits to show that they can significantly accelerate randomized algorithms used in a wide variety of applications including but not limited to Bayesian networks, optimization, Ising models, and quantum Monte Carlo.(c) 2021 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)

Automated summary

The article discusses a probabilistic computer based on p-bits that can accelerate randomized algorithms used in various applications, such as Bayesian networks, optimization, Ising models, and quantum Monte Carlo. A generic architecture for p-computers and simulations with thousands of p-bits are proposed to demonstrate their potential for significant speedup.