Related papers: SNGuess: A method for the selection of young extra…
The ongoing Zwicky Transient Facility (ZTF) survey is generating a massive alert rate from a variety of optical transients and variable stars, which are being filtered down to subsets meeting user-specified criteria by broker systems such…
We report results from an investigation at hard X-rays (above 18 keV) and soft X-rays (below 10 keV) of a sample of X-ray transients located on the Galactic plane and detected with the bursticity method, as reported in the latest 1,000…
We describe the development of a system for an automated, iterative, real-time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly…
The increasing data volume of high-energy space monitors necessitates real-time, automated transient classification for multi-messenger follow-up. Conventional methods rely on empirical features like hardness ratios and reliable…
The KiDS Strongly lensed QUAsar Detection project (KiDS-SQuaD) aims at finding as many previously undiscovered gravitational lensed quasars as possible in the Kilo Degree Survey. This is the second paper of this series where we present a…
We present the results of spectroscopic observations of targets discovered during the first two years of the ESSENCE project. The goal of ESSENCE is to use a sample of ~200 Type Ia supernovae (SNe Ia) at moderate redshifts (0.2 < z < 0.8)…
Gesture recognition on wearable devices is extensively applied in human-computer interaction. Electromyography (EMG) has been used in many gesture recognition systems for its rapid perception of muscle signals. However, analyzing EMG…
Superluminous supernovae (SLSNe) are a new class of transients with luminosities $\sim10 -100$ times larger than the usual core-collapse supernovae (SNe). Their origin is still unclear and one widely discussed scenario involves a…
Machine learning has become essential for automated classification of astronomical transients, but current approaches face significant limitations: classifiers trained on simulations struggle with real data, models developed for one survey…
We present a novel pipeline that uses a convolutional neural network (CNN) to improve the detection capability of near-Earth asteroids (NEAs) in the context of planetary defense. Our work aims to minimize the dependency on human…
Detecting gravitationally lensed supernovae is among the biggest challenges in astronomy. It involves a combination of two very rare phenomena: catching the transient signal of a stellar explosion in a distant galaxy and observing it…
The Zwicky Transient Facility (ZTF), a state-of-the-art optical robotic sky survey, registers on the order of a million transient events - such as supernova explosions, changes in brightness of variable sources, or moving object detections…
The current data acquisition rate of astronomical transient surveys and the promise for significantly higher rates during in the next decade necessitate the development of novel approaches to analyze astronomical data sets and promptly…
This is a follow-up sensitivity study on r-mode gravitational wave signals from newborn neutron stars illustrating the applicability of machine learning algorithms for the detection of long-lived gravitational-wave transients. In this…
We present an overview of the Weighing Halos Accurately, Locally, and Efficiently with Supernovae (WHALES) survey, the first to discover and measure Type Ia supernovae (SNe Ia) in and around galaxy superclusters. By building a sample of…
Strong gravitationally lensed supernovae (glSNe) are a powerful probe to obtain a measure of the expansion rate of the Universe, but they are also extremely rare. To date, only two glSNe with multiple images strongly lensed by galaxies have…
Amongst the population of TeV gamma-ray sources detected with the High Energy Stereoscopic System (H.E.S.S.) in the Galactic plane, clearly identified supernova remnant (SNR) shells constitute a small but precious source class. TeV-selected…
Large photometric surveys provide a rich source of observations of quiescent galaxies, including a surprisingly large population at z>1. However, identifying large, but clean, samples of quiescent galaxies has proven difficult because of…
We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R $\sim100$) data. The goal of SNIascore is fully automated classification of SNe Ia with…
We provide elements for a discussion of the expected neutrino signal from Supernova Remnants (SNR) in the Milky Way. After recalling why SNR are interesting and certain remarkable achievements of H.E.S.S., we describe a simple and…