University of Bordeaux

About: University of Bordeaux is a education organization based out in Bordeaux, France. It is known for research contribution in the topics: Population & Laser. The organization has 28811 authors who have published 55536 publications receiving 1619635 citations. The organization is also known as: UB.

Learning through ferroelectric domain dynamics in solid-state synapses.

Abstract: In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport and atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.

Comparison of GEANT4 very low energy cross section models with experimental data in water.

Abstract: Purpose: TheGEANT4 general-purpose Monte Carlo simulation toolkit is able to simulate physical interaction processes of electrons, hydrogen and helium atoms with charge states ( H 0 , H + ) and ( He 0 , He + , He 2 + ), respectively, in liquid water, the main component of biological systems, down to the electron volt regime and the submicrometer scale, providing GEANT4 users with the so-called “GEANT4-DNA” physics models suitable for microdosimetry simulation applications. The corresponding software has been recently re-engineered in order to provide GEANT4 users with a coherent and unique approach to the simulation of electromagnetic interactions within the GEANT4 toolkit framework (since GEANT4 version 9.3 beta). This work presents a quantitative comparison of these physics models with a collection of experimental data in water collected from the literature. Methods: An evaluation of the closeness between the total and differential cross section models available in theGEANT4 toolkit for microdosimetry and experimental reference data is performed using a dedicated statistical toolkit that includes the Kolmogorov–Smirnov statistical test. The authors used experimental data acquired in water vapor as direct measurements in the liquid phase are not yet available in the literature. Comparisons with several recommendations are also presented. Results: The authors have assessed the compatibility of experimental data withGEANT4microdosimetry models by means of quantitative methods. The results show that microdosimetric measurements in liquid water are necessary to assess quantitatively the validity of the software implementation for the liquid water phase. Nevertheless, a comparison with existing experimental data in water vapor provides a qualitative appreciation of the plausibility of the simulation models. The existing reference data themselves should undergo a critical interpretation and selection, as some of the series exhibit significant deviations from each other. Conclusions: TheGEANT4-DNA physics models available in the GEANT4 toolkit have been compared in this article to available experimental data in the water vapor phase as well as to several published recommendations on the mass stopping power. These models represent a first step in the extension of the GEANT4 Monte Carlo toolkit to the simulation of biological effects of ionizing radiation.