Related papers: Nano-scale simulation of neuronal damage by galact…
Real-time simulation of a large-scale biologically representative spiking neural network is presented, through the use of a heterogeneous parallelisation scheme and SpiNNaker neuromorphic hardware. A published cortical microcircuit model is…
While cosmic rays $(E\gtrsim 1\,\mathrm{GeV})$ are well coupled to a galaxy's interstellar medium (ISM) at scales of $L>100\,\mathrm{pc}$, adjusting stratification and driving outflows, their impact on small scales is less clear. Based on…
We introduce GausSim, a novel neural network-based simulator designed to capture the dynamic behaviors of real-world elastic objects represented through Gaussian kernels. We leverage continuum mechanics and treat each kernel as a Center of…
Energetic ions lose their energy in tissue mainly by ionising its molecules. This produces secondary electrons which transport this energy radially away from the ion path. The ranges of most of these electrons do not exceed a few…
Neural networks have emerged as a powerful tool for modeling physical systems, offering the ability to learn complex representations from limited data while integrating foundational scientific knowledge. In particular, neuro-symbolic…
The north-south (NS) anisotropy of galactic cosmic rays (GCRs) is dominated by a diamagnetic drift flow of GCRs in the interplanetary magnetic field (IMF), allowing us to derive key parameters of cosmic-ray propagation, such as the density…
The bulk propagation speed of GeV-energy cosmic rays is limited by frequent scattering off hydromagnetic waves. Most galaxy evolution simulations that account for this confinement assume the gas is fully ionized and cosmic rays are…
We used the GEANT4 Monte Carlo MC Toolkit to simulate carbon ion beams incident on water, tissue, and bone, taking into account nuclear fragmentation reactions. Upon increasing the energy of the primary beam, the position of the Bragg-Peak…
Newtonian N-body simulations have been employed successfully over the past decades for the simulation of the cosmological large-scale structure. Such simulations usually ignore radiation perturbations (photons and massless neutrinos) and…
Extracting stimulus features from neuronal ensembles is of great interest to the development of neuroprosthetics that project sensory information directly to the brain via electrical stimulation. Machine learning strategies that optimize…
Spintronic neurons which emit sharp voltage spikes are required for the realization of hardware neural networks enabling fast data processing with low-power consumption. In many neuroscience and computer science models, neurons are…
Multi-frequency radio polarimetry of the diffuse Galactic synchrotron background gives new viewpoints on the Galactic magnetic field. Rotation measure maps reveal magnetic structures on arcminute to degree scales, such as a ring in…
We compute the contribution from clusters of galaxies to the diffuse neutrino and $\gamma-$ray background. Due to their unique magnetic-field configuration, cosmic rays (CRs) with energy $\leq10^{17}$ eV can be confined within these…
Context. Nanoflares are small impulsive bursts of energy that blend with and possibly make up much of the solar background emission. Determining their frequency and energy input is central to understanding the heating of the solar corona.…
The secondary/primary cosmic-ray ratios and the diffuse backgrounds of gamma rays and neutrinos provide us with complementary information about the transport of Galactic cosmic rays~(CRs). We used the recent measurement of the diffuse gamma…
Challenging the Nvidia monopoly, dedicated AI-accelerator chips have begun emerging for tackling the computational challenge that the inference and, especially, the training of modern deep neural networks (DNNs) poses to modern computers.…
We present a Graph Neural Network (GNN) that accurately simulates a multidisperse suspension of interacting spherical particles. Our machine learning framework is built upon the recent work of Sanchez-Gonzalez et al. ICML, PMLR, 119,…
We present a detailed investigation of the near-field optical response of core-shell nanoparticles using Fourier-demodulated full-wave simulations, revealing significant modifications to established contrast mechanisms in scattering-type…
We analyze the properties of Large Scale Shocks in a cosmological volume of size 103Mpc/h simulated with the public 1.0.1 release of the ENZO code. Different methods to identify and characterize shocks in post processing are discussed…
Network analysis is rapidly becoming a standard tool for studying functional magnetic resonance imaging (fMRI) data. In this framework, different brain areas are mapped to the nodes of a network, whose links depict functional dependencies…