Hot Jupiters and their atmospheres are prime targets for transmission spectroscopy due to their extended atmospheres and the corresponding large signal-to-noise, providing the best possible constraints for the atmospheric carbon-to-oxygen (C/O) ratio and metallicity of exoplanets. Within BOWIE-ALIGN, we aim to compare JWST spectra of a sample of

Radio pulsating white dwarf (WD) systems, known as WD pulsars, are binary systems where the rapidly spinning WD interacts with a low-mass companion, producing pulsed non-thermal emission observed across the entire electromagnetic spectrum. Only two such systems are known: AR Sco and eRASSU J191213.9–441044. Here, we present the discovery of a third

Seyfert galaxies are emerging as a promising source class of high-energy neutrinos. The Seyfert galaxies NGC 4151 and NGC 1068 have respectively come up as the most promising counterparts of a 3σ and of a 4.2σ neutrino excesses detected by IceCube in the TeV energy range. Constraining the very high energy (VHE) emission associated with the neutrino

In this second paper on our variability survey of central stars of planetary nebulae (CSPNe) using the Zwicky Transient Facility (ZTF), we report 11 long-timescale variables with variability timescales ranging from months to years. We also present preliminary analyses based on spectroscopic and/or photometric follow-up observations for six of them

The Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) galaxy and quasar clustering data represents a significant expansion of data from Data Release 1 (DR1), providing improved statistical precision in baryon acoustic oscillation (BAO) constraints across multiple tracers, including bright galaxies, luminous red galaxies, emission

The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as part of this pipeline originally trained using data from the Baryon Oscillation Spectroscopic Survey (BOSS). In this paper we implement an active learning algorithm to