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Universal Self-Correcting Computing with Disordered Exciton-Polariton Neural Networks

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We show theoretically that neural networks based on disordered exciton-polariton systems allow the realization of Toffoli gates. Noise in input signals is self-corrected by the networks, such that the obtained… Click to show full abstract

We show theoretically that neural networks based on disordered exciton-polariton systems allow the realization of Toffoli gates. Noise in input signals is self-corrected by the networks, such that the obtained Toffoli gates are in principle cascadable, where their universality would allow for arbitrary circuits without the need of additional error-correcting codes. We further find that the exciton-polariton reservoir computers can directly simulate composite circuits, such that they are a highly efficient platform allowing circuits to operate in a single step, minimizing the delay of signal transport between elements and error-correction overhead.

Keywords: neural networks; polariton; exciton polariton; universal self; self correcting; disordered exciton

Journal Title: Physical review applied
Year Published: 2020

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