Related papers: ALeRCE light curve classifier: Tidal disruption ev…

With the exponential growth of time-domain surveys, the volume of light curves has increased rapidly. However, many survey projects, such as Gaia, still rely on offline batch-processing workflows in which data are calibrated, merged, and…

The laborious process of labeling data often bottlenecks projects that aim to leverage the power of supervised machine learning. Active Learning (AL) has been established as a technique to ameliorate this condition through an iterative…

In recent years, impressive performance of deep learning technology has been recognized in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR). Since a large amount of annotated data is required in this technique, it poses a…

The ALICE experiment at CERN is preparing for a major upgrade for the third phase of data taking run (Run 3), when the high luminosity phase of the Large Hadron Collider (LHC) starts. The increase in the beam luminosity will result in high…

This study presents an advanced system for detecting blue lights on emergency vehicles, developed using ABLDataset, a curated dataset that includes images of European emergency vehicles under various climatic and geographic conditions. The…

(Abridged) A new method is presented to identify transient candidates in large-scale surveys based on the variability pattern in their light curves. The method is based on the Abbe value, that estimates the smoothness of a light curve, and…

Context. To date, three nuclear transients have been associated with high-energy neutrino events. These transients are generally thought to be powered by tidal disruptions of stars (TDEs) by massive black holes. However, AT2019aalc, hosted…

AGILE is a space mission launched in 2007 to study X-ray and gamma-ray astronomy. The AGILE team developed real-time analysis pipelines to detect transient phenomena such as Gamma-Ray Bursts (GRBs) and to react to external science alerts…

Tidal disruption events (TDEs) are powerful probes of supermassive black hole (SMBH) properties and accretion physics. The existing light curve fitting tools assume that the disrupted stars are on parabolic orbits, which may introduce…

In view of Run 4 at the LHC, presently scheduled from 2029 onwards, ALICE is pursuing several upgrades to further extend its physics reach. In order to improve heavy-flavor hadron and dielectron measurements which rely on secondary…

The increasing data rates in modern high-energy physics experiments such as ALICE at the LHC and the upcoming ePIC experiment at the Electron-Ion Collider (EIC) present significant challenges in real-time event selection and data storage.…

Tidal disruption events (TDEs) occur when a star orbiting a massive black hole is sufficiently close to be tidally ripped apart by the black hole. AT 2022cmc is the first relativistic TDE that was observed (and discovered) as an optically…

The rates and properties of tidal disruption events (TDEs) provide valuable insights into their host galaxy central stellar densities and the demographics of their central supermassive black holes (SMBHs). TDEs have been observed only at…

Federated learning (FL) enables collaborative model training without exposing clients' private data, but its deployment is often constrained by the communication cost of transmitting gradients between clients and the central server,…

There has been profound progress in visual saliency thanks to the deep learning architectures, however, there still exist three major challenges that hinder the detection performance for scenes with complex compositions, multiple salient…

Over the past decade wide-field optical time-domain surveys have increased the discovery rate of transients to the point that $\lesssim 10\%$ are being spectroscopically classified. Despite this, these surveys have enabled the discovery of…

State-of-the-art text classification models are becoming increasingly reliant on deep neural networks (DNNs). Due to their black-box nature, faithful and robust explanation methods need to accompany classifiers for deployment in real-life…

The ATLAS Transition Radiation Tracker (TRT) is the outermost of the three sub-systems of the ATLAS Inner Detector at the Large Hadron Collider at CERN. In addition to its tracking capabilities, the TRT provides particle identification…

Anomaly detection underpins critical applications from network security and intrusion detection to fraud prevention, where recognizing aberrant patterns rapidly is indispensable. Progress in this area is routinely impeded by two obstacles:…

We present and analyse a new tidal disruption event (TDE), AT2017eqx at redshift z=0.1089, discovered by Pan-STARRS and ATLAS. The position of the transient is consistent with the nucleus of its host galaxy; it peaks at a luminosity of $L…