Conductance-dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914305286340608 |
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| author | Weilenmann, Christoph He, Hanglin Mladenović, Marko Zellweger, Till Portner, Kevin Bauer, Klemens Bellec, Guillaume Luisier, Mathieu Emboras, Alexandros |
| author_facet | Weilenmann, Christoph He, Hanglin Mladenović, Marko Zellweger, Till Portner, Kevin Bauer, Klemens Bellec, Guillaume Luisier, Mathieu Emboras, Alexandros |
| contents | Modern computers perform pre-defined operations using static memory components, whereas biological systems learn through inherently dynamic, time-dependent processes in synapses and neurons. The biological learning process also relies on global signals - neuromodulators - who influence many synapses at once depending on their dynamic, internal state. In this study, using optical radiation as a global neuromodulatory signal, we investigate nanoscale SrTiO3 (STO) memristors that can act as solid-state synapses. Via diverse sets of measurements, we demonstrate that the memristor's photoresponse depends on the electrical conductance state, following a well-defined square root relation. Additionally, we show that the conductance decays after photoexcitation with time constants in the range of 1 - 10 s and that this effect can be reliably controlled using an electrical bias. These properties in combination with our device's low power operation (< 1pJ per optical pulse) and small measurement variability may pave the way for space- and energy-efficient implementations of complex biological learning processes in electro-optical hardware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22767 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Conductance-dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing Weilenmann, Christoph He, Hanglin Mladenović, Marko Zellweger, Till Portner, Kevin Bauer, Klemens Bellec, Guillaume Luisier, Mathieu Emboras, Alexandros Emerging Technologies Modern computers perform pre-defined operations using static memory components, whereas biological systems learn through inherently dynamic, time-dependent processes in synapses and neurons. The biological learning process also relies on global signals - neuromodulators - who influence many synapses at once depending on their dynamic, internal state. In this study, using optical radiation as a global neuromodulatory signal, we investigate nanoscale SrTiO3 (STO) memristors that can act as solid-state synapses. Via diverse sets of measurements, we demonstrate that the memristor's photoresponse depends on the electrical conductance state, following a well-defined square root relation. Additionally, we show that the conductance decays after photoexcitation with time constants in the range of 1 - 10 s and that this effect can be reliably controlled using an electrical bias. These properties in combination with our device's low power operation (< 1pJ per optical pulse) and small measurement variability may pave the way for space- and energy-efficient implementations of complex biological learning processes in electro-optical hardware. |
| title | Conductance-dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2509.22767 |