Related papers: AtomNeb: IDL Library and Python Package for Atomic…
Determining molecular abundances in astrophysical environments is crucial for interpreting observational data and constraining physical conditions in these regions. Chemical modelling tools are essential for simulating the complex processes…
Planetary Nebulae (PNe) abundance patterns have long been used to note signatures of nuclear processing and to trace the distribution of metals throughout galaxies. We present abundance gradients and heavy element ratios based upon newly…
Complex optical design is hindered by conventional piecewise setup, which prevents modularization and therefore abstraction of subsystems at the circuit level. This limits multiple fields that require complex optics systems, including…
In this article I present IEAD, a new interface for astronomical science databases. It is based on a powerful, yet simple, syntax designed to completely abstract the user from the structure of the underlying database. The programming…
Motivated by possible atomic origins of the unidentified emission line detected at 3.55 keV to 3.57 keV in a stacked spectrum of galaxy clusters (Bulbul et al. 2014), an electron beam ion trap (EBIT) was used to investigate the resonant…
[Abridged] Investigations of neutron(n)-capture element nucleosynthesis and chemical evolution have largely been based on stellar spectroscopy. However, the recent detection of these elements in several planetary nebulae (PNe) indicates…
The study of DNA charge dynamics is a highly interdisciplinary field that bridges physics, chemistry, biology, and medicine, and plays a critical role in processes such as DNA damage detection, protein-DNA interactions, and DNA-based…
We present a new software tool to enable astronomers to easily compare observations of emission line ratios with those determined by photoionization and shock models, ITERA, the IDL Tool for Emission-line Ratio Analysis. This tool can plot…
The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory. IDTxl provides functionality to…
Spectroscopy of planetary nebulae (PNe) provides the means to investigate s-process enrichments of neutron(n)-capture elements that cannot be detected in asymptotic giant branch (AGB) stars. However, accurate abundance determinations of…
Machine learning interatomic potentials (MLIPs) enable atomistic simulations with near ab initio accuracy at significantly reduced computational cost, but their broader adoption is often limited by fragmented tooling, limited scalability,…
We present Aurora, an open-source package for particle transport, neutrals and radiation modeling in magnetic confinement fusion plasmas. Aurora's modern multi-language interface enables simulations of 1.5D impurity transport within…
Radionuclide identification is a radioanalytical method employed in various scientific disciplines that utilize alpha-particle or gamma-ray spectrometric assays, ranging from astrophysics to nuclear medicine. Radionuclide libraries in…
We have written a reference manual to use JUDE (Jayant's UVIT data Explorer) data pipeline software for processing and reducing the Ultraviolet Imaging Telescope (UVIT) Level~1 data into event lists and images -- Level~2 data. The JUDE…
Information about the physical properties of astrophysical objects cannot be measured directly but is inferred by interpreting spectroscopic observations in the context of atomic physics calculations. Ratios of emission lines, for example,…
We develop a Python-based open-source package to analyze the results stemming from ab initio molecular-dynamics simulations of fluids. The package is best suited for applications on natural systems, like silicate and oxide melts,…
Incorporation of machine learning (ML) techniques into atomic-scale modeling has proven to be an extremely effective strategy to improve the accuracy and reduce the computational cost of simulations. It also entails conceptual and practical…
Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machine learning models. While most existing GNN models for…
We present spatially resolved high-resolution spectrophotometric data for the planetary nebulae PB8, NGC2867, and PB6. We have analyzed two knots in NGC2867 and PB6 and one in PB8. The three nebulae are ionized by [WC] type nuclei: early…
We report detailed analyses of deep, high-resolution spectra of three Galactic planetary nebulae (PNe) with high abundance discrepancy factors (ADFs), Hf2-2, M1-42 and NGC6153, obtained with the Ultraviolet and Visual Echelle Spectrograph…