377 citations · 3k across the 52 of their papers we have counts for
16 papers · 1 filter
Querying an astronomical database using large language models: the ALeRCE text-to-SQL system
P. A. Estevez, J. Espejo-Moreira, S. Sanfeliu-Alvarez +10
We develop a text-to-SQL (structured query language) system based on large language models (LLMs) using in-context learning and apply it to the Automatic Learning for the Rapid Cla…
Temporal Stamp Classifier: Classifying Short Sequences of Astronomical Alerts
Daniel Neira O., Pablo A. Estévez, Francisco Förster
In this work, we propose a deep learning-based classification model of astronomical objects using alerts reported by the Zwicky Transient Facility (ZTF) survey. The model takes as…
Domain Adaptation via Minimax Entropy for Real/Bogus Classification of Astronomical Alerts
Guillermo Cabrera-Vives, César Bolivar, Francisco Förster +3
Time domain astronomy is advancing towards the analysis of multiple massive datasets in real time, prompting the development of multi-stream machine learning models. In this work,…
Multi-scale stamps for real-time classification of alert streams
Ignacio Reyes-Jainaga, Francisco Förster, Alejandra M. Muñoz Arancibia +15
In recent years, automatic classifiers of image cutouts (also called "stamps") have shown to be key for fast supernova discovery. The Vera C. Rubin Observatory will distribute abou…
DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multi-resolution Images
Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes +25
We present DELIGHT, or Deep Learning Identification of Galaxy Hosts of Transients, a new algorithm designed to automatically and in real-time identify the host galaxies of extragal…
Deep Attention-Based Supernovae Classification of Multi-Band Light-Curves
Óscar Pimentel, Pablo A. Estévez, Francisco Förster
In astronomical surveys, such as the Zwicky Transient Facility, supernovae (SNe) are relatively uncommon objects compared to other classes of variable events. Along with this scarc…
The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker
F. Förster, G. Cabrera-Vives, E. Castillo-Navarrete +37
We introduce the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self--consistent classifica…
Alert Classification for the ALeRCE Broker System: The Real-time Stamp Classifier
Rodrigo Carrasco-Davis, Esteban Reyes, Camilo Valenzuela +20
We present a real-time stamp classifier of astronomical events for the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker. The classifier is based on a convo…
Design and operation of the ATLAS Transient Science Server
K. W. Smith, S. J. Smartt, D. R. Young +19
The Asteroid Terrestrial impact Last Alert System (ATLAS) system consists of two 0.5m Schmidt telescopes with cameras covering 29 square degrees at plate scale of 1.86 arcsec per p…
Fast algorithms for slow moving asteroids: constraints on the distribution of Kuiper Belt Objects
Peter J. Whidden, J. Bryce Kalmbach, Andrew J. Connolly +11
We introduce a new computational technique for searching for faint moving sources in astronomical images. Starting from a maximum likelihood estimate for the probability of the det…
The High Cadence Transient Survey (HITS): Compilation and characterization of light-curve catalogs
Jorge Martínez-Palomera, Francisco Förster, Pavlos Protopapas +12
The High Cadence Transient Survey (HiTS) aims to discover and study transient objects with characteristic timescales between hours and days, such as pulsating, eclipsing and explod…
Enhanced Rotational Invariant Convolutional Neural Network for Supernovae Detection
Esteban Reyes, Pablo A. Estévez, Ignacio Reyes +4
In this paper, we propose an enhanced CNN model for detecting supernovae (SNe). This is done by applying a new method for obtaining rotational invariance that exploits cyclic symme…
Deep Learning for Image Sequence Classification of Astronomical Events
Rodrigo Carrasco-Davis, Guillermo Cabrera-Vives, Francisco Förster +6
We propose a new sequential classification model for astronomical objects based on a recurrent convolutional neural network (RCNN) which uses sequences of images as inputs. This ap…
Robust period estimation using mutual information for multi-band light curves in the synoptic survey era
Pablo Huijse, Pablo A. Estevez, Francisco Forster +5
The Large Synoptic Survey Telescope (LSST) will produce an unprecedented amount of light curves using six optical bands. Robust and efficient methods that can aggregate data from m…
Deep-HiTS: Rotation Invariant Convolutional Neural Network for Transient Detection
Guillermo Cabrera-Vives, Ignacio Reyes, Francisco Förster +2
We introduce Deep-HiTS, a rotation invariant convolutional neural network (CNN) model for classifying images of transients candidates into artifacts or real sources for the High ca…
Scheduling in Targeted Transient Surveys and a New Telescope for CHASE
Francisco Förster, Nicolás López, José Maza +2
We present a method for scheduling observations in small field-of-view transient targeted surveys. The method is based on maximizing the probability of detection of transient event…