Related papers: Material Identification using Multi-Modal Intrinsi…
Automated classification of supernovae (SNe) based on optical photometric light curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin…
At very high densities, electrons react with protons to form neutron rich matter. This material is central to many fundamental questions in nuclear physics and astrophysics. Moreover, neutron rich matter is being studied with an…
Identifying model Hamiltonians is a vital step toward creating predictive models of materials. Here, we combine Bayesian optimization with the EDRIXS numerical package to infer Hamiltonian parameters from resonant inelastic X-ray scattering…
Neutron/gamma discrimination has been intensively researched in recent years, due to its unique scientific value and widespread applications. With the advancement of detection materials and algorithms, nowadays we can achieve fairly good…
Based on the precise nuclei data released by AMS-02, we study the spectra hardening of both the primary (proton, helium, carbon, oxygen, and the primary component of nitrogen) and the secondary (anti-proton, lithium, beryllium, boron and…
Multi-energy radiography is a new direction in non-destructive testing. Its specific feature is separate detection of penetrating radiation in several energy channels. Multi-energy radiography allows quantitative determination of the atomic…
Pulse shape discrimination (PSD) is widely used in particle and nuclear physics. Specifically in liquid scintillator detectors, PSD facilitates the classification of different particle types based on their energy deposition patterns. This…
Moire patterns in van der Waals bilayer materials complicate the analysis of atomic-resolution images, hindering the atomic-scale insight typically attainable with scanning transmission electron microscopy. Here, we report a method to…
Organic scintillators using a solid polyurethane (PU) matrix have been introduced to combine the robustness of a construction material with scintillating properties that allow gamma rays and fast neutrons to be detected efficiently and at…
Some inverse problems in high-energy physics, neutron diffraction and NMR spectroscopy are discussed. To solve them, the Fourier integrated transformation method and the Maximum Entropy Technique (MENT) were used. The integrated images of…
The CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) prototype using Glass Resistive Plate Chambers as a sensitive medium is the first technological prototype of a family of high-granularity calorimeters developed by the CALICE…
Development of next-generation electronic devices for applications call for the discovery of quantum materials hosting novel electronic, magnetic, and topological properties. Traditional electronic structure methods require expensive…
We present an assessment of a multi-method approach based on ion beam analysis to obtain high-resolution depth profiles of the total chemical composition of complex alloy systems. As a model system we employ an alloy based on several…
A proof-of-concept framework for identifying molecules of unknown elemental composition and structure using experimental rotational data and probabilistic deep learning is presented. Using a minimal set of input data determined…
Nuclear Magnetic Resonance (NMR) spectroscopy leverages nuclear magnetization to probe molecules' chemical environment, structure, and dynamics, with applications spanning from pharmaceuticals to the petroleum industry. Despite its utility,…
The early detection of terrorist threats, such as guns and knives, through improved metal detection, has the potential to reduce the number of attacks and improve public safety and security. To achieve this, there is considerable potential…
Indian Scintillator Matrix for Reactor Anti-Neutrinos (ISMRAN), a plastic scintillator array (10$\times$10), is being constructed for the purpose of electron anti-neutrino ($\overline\nuup_{e}$) detection for reactor monitoring…
Detecting and analyzing the local environment is crucial for investigating the dynamical processes of crystal nucleation and shape colloidal particle self-assembly. Recent developments in machine learning provide a promising avenue for…
The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a…
Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and…