The relationship between the thermodynamic and computational properties of physical
systems has been a major theoretical interest since at least the 19th century. It has also …

While digital computers rely on software-generated pseudo-random number generators,
hardware-based true random number generators (TRNGs), which employ the natural …

Probabilistic (p-) computing is a physics-based approach to addressing computational
problems which are difficult to solve by conventional von Neumann computers. A key …

The convergence of spintronics and traditional semiconductor technology marks a critical
juncture in the evolution of computing architectures, for which the development of foundation …

Abstract Compute-in-memory (CIM) accelerators based on emerging memory devices are of
potential use in edge artificial intelligence and machine learning applications due to their …

Probabilistic computing has emerged as a viable approach to treat optimization problems.
To achieve superior computing performance, the key aspect during computation is massive …

Telegraph noise caused by frequent switching of the magnetization in small magnetic
devices has become a useful resource for probabilistic computing. Conventional theories …

An emerging paradigm in modern electronics is that of CMOS+ X requiring the integration of
standard CMOS technology with novel materials and technologies denoted by X. In this …

Stochastic magnetic tunnel junctions (SMTJs) using low-barrier nanomagnets have shown
promise as fast, energy-efficient, and scalable building blocks for probabilistic computing …

Probabilistic computing is a computing scheme that offers a more efficient approach than
conventional complementary metal-oxide–semiconductor (CMOS)-based logic in a variety of …