Search Publications
Machine learning methods for the search for L&T brown dwarfs in the data of modern sky surveys
Avdeeva, A.
According to various estimates, brown dwarfs (BD) should account for up to 25 percent of all objects in the Galaxy. However, few of them are discovered and well-studied, both individually and as a population. Homogeneous and complete samples of brown dwarfs are needed for these kinds of studies. Due to their weakness, spectral studies of brown dwa…
HILIGT, upper limit servers I-Overview
Gabriel, C.; Kretschmar, P.; Kuulkers, E. +10 more
The advent of all-sky facilities, such as the Neil Gehrels Swift observatory, the All Sky Automated Search for Supernovae (ASAS-SN), eROSITA and Gaia has led to a new appreciation of the importance of transient sources in solving outstanding astrophysical questions. Identification and catalogue cross-matching of transients has been eased over the …
HILIGT, Upper Limit Servers II - Implementing the data servers
Freyberg, M. J.; Wilms, J.; Savchenko, V. +7 more
The High-Energy Lightcurve Generator (HILIGT) is a new web-based tool which allows the user to generate long-term lightcurves of X-ray sources. It provides historical data and calculates upper limits from image data in real-time. HILIGT utilizes data from twelve satellites, both modern missions such as XMM-Newton and Swift, and earlier facilities …
Using multiple instance learning for explainable solar flare prediction
Melchior, M.; Huwyler, C.
In this work we leverage a weakly-labeled dataset of spectral data from NASA's IRIS satellite for the prediction of solar flares using the Multiple Instance Learning (MIL) paradigm. While standard supervised learning models expect a label for every instance, MIL relaxes this and only considers bags of instances to be labeled. This is ideally suite…
1-DREAM: 1D Recovery, Extraction and Analysis of Manifolds in noisy environments
Smith, R.; Peletier, R.; Mastropietro, M. +7 more
Filamentary structures (one-dimensional manifolds) are ubiquitous in astronomical data sets. Be it in particle simulations or observations, filaments are always tracers of a perturbation in the equilibrium of the studied system and hold essential information on its history and future evolution. However, the recovery of such structures is often com…
Sensitivity estimation for dark matter subhalos in synthetic Gaia DR2 using deep learning
Benito, M.; Bazarov, A.; Hütsi, G. +3 more
The abundance of dark matter subhalos orbiting a host galaxy is a generic prediction of the cosmological framework, and is a promising way to constrain the nature of dark matter. In this paper, we investigate the use of machine learning-based tools to quantify the magnitude of phase-space perturbations caused by the passage of dark matter subhalos…
The Gaia AVU-GSR parallel solver: Preliminary studies of a LSQR-based application in perspective of exascale systems
Lattanzi, M. G.; Becciani, U.; Bucciarelli, B. +6 more
The Gaia Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver aims to find the astrometric parameters for ∼ 108 stars in the Milky Way, the attitude and the instrumental specifications of the Gaia satellite, and the global parameter γ of the post Newtonian formalism. The code iteratively solves a system o…
Solar activity classification based on Mg II spectra: Towards classification on compressed data
Ivanov, S.; Tsizh, M.; Ullmann, D. +2 more
Although large volumes of solar data are available for investigation and study, the vast majority of these data remain unlabeled and are therefore not amenable to modern supervised machine learning methods. Having a way to accurately and automatically classify spectra into categories related to the degree of solar activity is highly desirable and …
The Open Universe VOU-Blazars tool
Giommi, P.; Chang, Y. -L.; Brandt, C. H.
Blazars are a remarkable type of Active Galactic Nuclei (AGN) that are playing an important and rapidly growing role in today's multi-frequency and multi-messenger astrophysics. In the past several years, blazars have been discovered in relatively large numbers in radio, microwave, X-ray and gamma-ray surveys, and more recently have been associate…
Data Lab-A community science platform
Nikutta, R.; Fitzpatrick, M.; Scott, A. +1 more
Data Lab is an open-access science platform developed and operated by the Community and Science Data Center (CSDC) at NSF's National Optical-Infrared Astronomy Research Laboratory (NOIRLab). It serves public photometric survey datasets, provides interactive and programmatic data access, and SQL/ADQL query capabilities via TAP. Users also receive g…