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20162019
most citedLow-Energy Truly Random Number Generation with Superparamagnetic Tunnel Junctions for Unconventional Computing

175 citations · 180 across the 4 of their papers we have counts for

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5 papers · 1 filter

physics.app-ph2019

Designing large arrays of interacting spin-torque nano-oscillators for microwave information processing

Philippe Talatchian, Miguel Romera, Flavio Abreu Araujo +6

Arrays of spin-torque nano-oscillators are promising for broadband microwave signal detection and processing, as well as for neuromorphic computing. In many of these applications,…

physics.app-ph2019

Microwave neural processing and broadcasting with spintronic nano-oscillators

P. Talatchian, M. Romera, S. Tsunegi +14

Can we build small neuromorphic chips capable of training deep networks with billions of parameters? This challenge requires hardware neurons and synapses with nanometric dimension…

physics.app-ph2018

Nano-oscillator-based classification with a machine learning-compatible architecture

Damir Vodenicarevic, Nicolas Locatelli, Julie Grollier +1

Pattern classification architectures leveraging the physics of coupled nano-oscillators have been demonstrated as promising alternative computing approaches, but lack effective lea…

physics.app-ph2018

Circuit-Level Evaluation of the Generation of Truly Random Bits with Superparamagnetic Tunnel Junctions

Damir Vodenicarevic, Nicolas Locatelli, Alice Mizrahi +4

Many emerging alternative models of computation require massive numbers of random bits, but their generation at low energy is currently a challenge. The superparamagnetic tunnel ju…

physics.app-ph2017175 cited

Low-Energy Truly Random Number Generation with Superparamagnetic Tunnel Junctions for Unconventional Computing

Damir Vodenicarevic, Nicolas Locatelli, Alice Mizrahi +10

Low-energy random number generation is critical for many emerging computing schemes proposed to complement or replace von Neumann architectures. However, current random number gene…