Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

Tae Joon Park

doi:10.1021/acs.nanolett.2c03223

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

2022-10-31

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Subramanian K. R. S. Sankaranarayanan

DOI：10.1021/acs.nanolett.2c03223

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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.

Keywords:

metal-insulator transition

perovskite nickelates

probabilistic computing

hydrogen

complex oxide

neuromorphic computing

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

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