Litcius/Paper detail

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

Tae Joon Park, Kemal Selçuk, Haitian Zhang, Sukriti Manna, Rohit Batra, Qi Wang, Haoming Yu, Navid Anjum Aadit, Subramanian K. R. S. Sankaranarayanan, Hua Zhou, Kerem Y. Çamsarı, Shriram Ramanathan

2022Nano Letters34 citationsDOIOpen Access PDF

Abstract

Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. Here, we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.

Topics & Concepts

Probabilistic logicComputer scienceScalabilityPerovskite (structure)Distributed computingChemistryCrystallographyDatabaseArtificial intelligenceAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesMachine Learning in Materials Science