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Integer Factorization with Stochastic Spiking in Percolating Networks of Nanoparticles
Sofie J Studholme1, Simon A Brown1
1The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matu̅, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.
Abstract:
As growth in global demand for computing power continues to outpace ongoing improvements in transistor-based hardware, novel computing solutions are required. One promising approach employs stochastic nanoscale devices to accelerate probabilistic computing algorithms. Percolating Networks of Nanoparticles (PNNs) exhibit stochastic spiking, which is of particular interest as it meets criteria for criticality which is associated with a range of computational advantages. Here, we show several ways in which spiking PNNs can be used as the core stochastic components of coupled networks that allow successful factorization of integers up to 945. We demonstrate asynchronous operation and show that a single device is sufficient to solve all factorization tasks and to generate multiple solutions simultaneously.
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