Even as the quantum computing community chases reliable systems, innovation continues around developing techniques that ‘mimic’ some of quantum computing’s capabilities but run on less complicated machines. Welcome to ‘probabilistic computing” or at least a step in that direction. Researchers from Purdue University and Tohoku University published a proof-of-concept study in Nature last week in which they created and used probabilistic bits (p-bits) to factorize integers up to 945.
The work, led by Kerem Casmari (Purdue) and Shunsuke Fukami (Tohoku), seems to be well suited for classes of optimization (energy cost) problems. If this sounds a bit like adiabatic quantum annealing, you’re correct, although the authors say it can be also used to emulate gate-based quantum computing.
The researchers write in their paper (Integer factorization using stochastic magnetic tunnel junctions):
“The key role is played by a probabilistic bit (a p-bit)—a robust, classical entity fluctuating in time between 0 and 1, which interacts with other p-bits in the same system using principles inspired by neural networks. Here we present a proof-of-concept experiment for probabilistic computing using spintronics technology, and demonstrate integer factorization, an illustrative example of the optimization class of problems addressed by adiabatic and gated quantum computing. Nanoscale magnetic tunnel junctions showing stochastic behavior are developed by modifying market-ready magnetoresistive random-access memory technology and are used to implement three-terminal p-bits that operate at room temperature.”
According to the paper, the p-bits are electrically connected to form a functional asynchronous network, to which a modified adiabatic quantum computing algorithm that implements three- and four-body interactions is applied. “Factorization of integers up to 945 is demonstrated with this rudimentary asynchronous probabilistic computer using eight correlated p-bits, and the results show good agreement with theoretical predictions.”
The authors note decoherence and the current requirement for cryogenic operation, “as well as the limited many-body interactions that can be implemented” all pose challenges for typical quantum computers. “Probabilistic computing,” they write, “is another unconventional computation scheme that shares similar concepts with quantum computing but is not limited by the above challenges.”
Link to paper: https://www.nature.com/articles/s41586-019-1557-9