arXiv subjects

Felix Weber

Publications and source records attributed to Felix Weber.

4 recordsLinked to original sources

arXiv2026

Detecting the Axion-Photon Conversion Background

The potential to detect axion dark matter through astrophysical processes has shown high promise in recent years. We therefore expand on previous work studying the axion-to-photon conversion efficacy of neutron stars and the interstellar medium (ISM) in this endeavor, respectively. For neutron stars (NS), we examine the possibility of a background signal emanating from all NS magnetospheres in the galaxy. Using a heuristic Galactic model, we find a significant background signal emanating from such magnetospheres in the Milky Way. This signal, while weak in absolute power ($\gtrsim 1$ mJy sr$^{-1}$ from the Galactic Center, at 2 GHz), can be detected through new statistical techniques with current instrumentation like the Atacama Large Millimeter Array (ALMA) at high radio frequencies (200 - 950 GHz). These techniques make use of higher order statistics like spectrally-limited ($\sim 300$ km s$^{-1}$) increases in confusion noise levels and kurtoses of survey images, and also show promise for general population estimation techniques. For the ISM, we consider Primakoff processes between free electrons and axions, and derive typical signal strengths of $10^{-15}$ Jy sr$^{-1}$ $\cdot$ $m_a$/eV, with a local, cosmological upper bound of $10^{-8}$ Jy sr$^{-1}$ $\cdot$ $m_a$/eV. Hence, we find that any diffuse axion signal from the ISM and other, large-scale, astrophysical plasmas to be too weak to be detected with modern technologies. We therefore find that the best avenue towards detecting a potential quantum chromodynamics (QCD) axion dark-matter particle is through the radio imaging of large swaths of the Galactic Center and other regions where we expect large numbers of pulsars and neutron stars.

astro-ph.HE↗

arXiv2025

The Capriccio method as a versatile tool for quantifying the fracture properties of glassy materials under complex loading conditions with chemical specificity

Molecular dynamics (MD) simulations are widely used to provide insights into fracture mechanisms while maintaining chemical specificity. However, particle-based techniques such as MD are limited in terms of accessible length scales and applicable boundary conditions, which restricts the investigation of fracture phenomena in typical engineering settings. In an attempt to overcome these limitations, we apply the partitioned-domain Capriccio method to couple atomistic MD samples representing silica glass with the finite element (FE) method. With this approach, we perform mode I (rectangular panel under tension, three-, and four-point bending), mode II as well as mode III (rectangular panel under in-plane or out-of-plane shear) simulations. Thereby, we investigate multiple criteria to identify the onset of crack propagation based on the virial stress, the number of pair interactions, the kinetic energy/temperature, the crack velocity, and the crack opening displacement. The approach presented provides quantitatively plausible results for the critical stress intensity factors KIc, KIIc, and KIIIc. This contribution shows that the Capriccio method is a flexible means of performing fracture simulations that take into account boundary conditions typical of experimental test setups with atomistic specificity near the crack tip. While also pointing out the current limitations of the Capriccio method, we demonstrate its potential to integrate atomistic insights into FE models with significantly larger overall dimensions.

cond-mat.mtrl-sci↗

arXiv2020

Simplified ResNet approach for data driven prediction of microstructure-fatigue relationship

The heterogeneous microstructure in metallic components results in locally varying fatigue strength. Metal fatigue strongly depends on size and shape of non-metallic inclusions and pores, commonly referred to as "defects". Nodular cast iron (NCI) contains graphite inclusions (nodules) whose shape and frequency influence the fatigue strength. Fatigue strength can be simulated by micromechanical finite element models. The drawback of these models are the large computational costs. Therefore, we employ a data-driven machine learning methodology. More precisely, we utilize the simplified residual neural network (SimResNet) which was recently introduced (Herty et al., Kinetic Theory for Residual Neural Networks, 2020) to predict fatigue strength from metallographic data. For the training, we use fatigue data which is simulated with a micromechanical model and the shakedown theorem. The micromechanical models are derived directly from micrographs of nodular cast iron, respectively. The application of SimResNet shows a good performance to predict fatigue strength by local microstructures of nodular cast iron. We show several test cases. The simplified character of SimResNet enables fast predictions of fatigue by microstructures, even in comparision to classical residual neural networks.

cs.CE↗

arXiv2020

Detection of missing low-lying atomic states in actinium

Two lowest-energy odd-parity atomic levels of actinium, 7s^27p 2P^o_1/2, 7s^27p 2P^o_3/2, were observed via two-step resonant laser-ionization spectroscopy and their respective energies were measured to be 7477.36(4) cm^-1 and 12 276.59(2) cm^-1. The lifetimes of these states were determined as 668(11) ns and 255(7) ns, respectively. In addition, these properties were calculated using a hybrid approach that combines configuration interaction and coupled-cluster methods in good agreement. The data are of relevance for understanding the complex atomic spectra of actinides and for developing efficient laser-cooling and ionization schemes for actinium, with possible applications for high-purity medicalisotope production and future fundamental physics experiments with this atom.

physics.atom-ph↗