Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

  • Tae Joon Park*
  • , Kemal Selcuk
  • , Hai Tian Zhang*
  • , Sukriti Manna
  • , Rohit Batra
  • , Qi Wang
  • , Haoming Yu
  • , Navid Anjum Aadit
  • , Subramanian K.R.S. Sankaranarayanan
  • , Hua Zhou
  • , Kerem Y. Camsari*
  • , Shriram Ramanathan*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)8654-8661
Number of pages8
JournalNano Letters
Volume22
Issue number21
DOIs
StatePublished - 9 Nov 2022

Keywords

  • complex oxide
  • hydrogen
  • metal−insulator transition
  • neuromorphic computing
  • perovskite nickelates
  • probabilistic computing

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