Electro-photo-sensitive memristor for neuromorphic and arithmetic computing

P. Maier, F. Hartmann, M. Emmerling, C. Schneider, M. Kamp, S. Höfling, L. Worschech

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

We present optically and electrically tunable conductance modifications of a site-controlled quantum-dot memristor. The conductance of the device is tuned by electron localization on a quantum dot. The control of the conductance with voltage and low-power light pulses enables applications in neuromorphic and arithmetic computing. As in neural networks, applying pre- and postsynaptic voltage pulses to the memristor allows us to increase (potentiation) or decrease (depression) the conductance by tuning the time difference between the electrical pulses. Exploiting state-dependent thresholds for potentiation and depression, we are able to demonstrate a memory-dependent induction of learning. The discharging of the quantum dot can further be induced by low-power light pulses in the nanowatt range. In combination with the state-dependent threshold voltage for discharging, this enables applications as generic building blocks to perform arithmetic operations in bases ranging from binary to decimal with low-power optical excitation. Our findings allow the realization of optoelectronic memristor-based synapses in artificial neural networks with a memory-dependent induction of learning and enhanced functionality by performing arithmetic operations.

Original languageEnglish
Article number054011
Pages (from-to)1-9
Number of pages9
JournalPhysical Review Applied
Volume5
Issue number5
DOIs
Publication statusPublished - 17 May 2016

Keywords

  • Memristor
  • Artificial neural network
  • Metaplasticity
  • Synaptic plasticity
  • Quantum dot
  • Floating gate transistor

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