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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…