Search Publications
Exo-MerCat v2.0.0: Updates and open-source release of the Exoplanet Merged Catalog software
Zinzi, Angelo; Carleo, Ilaria; Mandell, Avi +8 more
Exoplanet research is at the forefront of contemporary astronomy recommendations. As more and more exoplanets are discovered and vetted, databases and catalogs are built to collect information. Various resources are available to scientists for this purpose, though every one of them has different scopes and notations. In Alei et al. (2020) we descr…
MAR: A Multiband Astronomical Reduction package
Sodré, L.; Menéndez-Delmestre, K.; Perottoni, H. D. +9 more
The Multiband Astronomical Reduction (MAR) is a multithreaded data reduction pipeline designed to handle raw astronomical images from the Southern Photometric Local Universe Survey, transforming them into frames that are ready for source extraction, photometry and flux calibration. MAR is a complete software written almost entirely in Python, with…
Membership determination in open clusters using the DBSCAN Clustering Algorithm
Hasan, P.; Raja, M.; Mahmudunnobe, Md. +2 more
In this paper, we apply the machine learning clustering algorithm Density Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of stars in twelve open clusters (NGC 2264, NGC 2682, NGC 2244, NGC 3293, NGC 6913, NGC 7142, IC 1805, NGC 6231, NGC 2243, NGC 6451, NGC 6005 and NGC 6583) based on Gaia DR3 Data. This sampl…
Using GMM in open cluster membership: An insight
Hasan, P.; Raja, M.; Hasan, S. N. +2 more
The unprecedented precision of Gaia has led to a paradigm shift in membership determination of open clusters where a variety of machine learning (ML) models can be employed. In this paper, we apply the unsupervised Gaussian Mixture Model (GMM) to a sample of thirteen clusters with varying ages (log t ≈ 6.38-9.64) and distances (441-5183 pc) from G…
LCGCT: A light curve generator in customisable-time-bin based on time-series database
Xu, Y.; Cui, C.; Fan, D. +1 more
In the era of time-domain astronomy, scientists often need to generate light curves with varying time-bin. However, an increase in time resolution typically leads to a substantial increase in data transmission. To enhance the data processing efficiency in time-domain astronomy, we propose a novel time-series data model for storing time-series obse…
The effect of baseline on the uncertainties of range determination performed by two-site astrometric observations. A sample case for the triangulation method: TURKSAT 3A and TURKSAT 4A
Gökay, H. G.; Özdemi̇r, S.; Bağıran, M. N. +1 more
The uncertainties in range determination depending on two-site locations for GEO satellites were calculated and shown that the uncertainty in the range depends not only on linear baseline distance between the locations but also both latitude and longitude of geographic coordinates of the sites. By taking the first observing site as fixed and chang…
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…
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…