Search Publications

Compression method for solar polarization spectra collected from Hinode SOT/SP observations
DOI: 10.1016/j.ascom.2025.100929 Bibcode: 2025A&C....5100929B

Oba, T.; Iida, Y.; Iijima, H. +1 more

The rapidly increasing volume of observational solar spectral data poses challenges for efficient and accurate analysis. To address this issue, we present a deep learning-based compression technique using the deep autoencoder (DAE) and 1D-convolutional autoencoder (CAE) models, developed for use on the Hinode SOT/SP data. This technique focuses on…

2025 Astronomy and Computing
Hinode 1
Exo-MerCat v2.0.0: Updates and open-source release of the Exoplanet Merged Catalog software
DOI: 10.1016/j.ascom.2025.100936 Bibcode: 2025A&C....5100936A

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…

2025 Astronomy and Computing
Gaia 1
MAR: A Multiband Astronomical Reduction package
DOI: 10.1016/j.ascom.2024.100899 Bibcode: 2025A&C....5100899S

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…

2025 Astronomy and Computing
Gaia 0
Membership determination in open clusters using the DBSCAN Clustering Algorithm
DOI: 10.1016/j.ascom.2024.100826 Bibcode: 2024A&C....4700826R

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…

2024 Astronomy and Computing
Gaia 3
Using GMM in open cluster membership: An insight
DOI: 10.1016/j.ascom.2024.100792 Bibcode: 2024A&C....4600792M

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…

2024 Astronomy and Computing
Gaia 2
LCGCT: A light curve generator in customisable-time-bin based on time-series database
DOI: 10.1016/j.ascom.2024.100845 Bibcode: 2024A&C....4800845Z

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…

2024 Astronomy and Computing
Gaia 1
Reconstructing the mid-infrared spectra of galaxies using ultraviolet to submillimeter photometry and Deep Generative Networks
DOI: 10.1016/j.ascom.2024.100823 Bibcode: 2024A&C....4700823R

Efstathiou, A.; Rissaki, Agapi; Pavlou, O. +2 more

The mid-infrared spectra of galaxies are rich in features such as the Polycyclic Aromatic Hydrocarbon (PAH) and silicate dust features which give valuable information about the physics of galaxies and their evolution. For example they can provide information about the relative contribution of star formation and accretion from a supermassive black …

2024 Astronomy and Computing
Herschel 0
Classifying the clouds of Venus using unsupervised machine learning
DOI: 10.1016/j.ascom.2024.100884 Bibcode: 2024A&C....4900884M

Molaverdikhani, K.; Grassi, T.; Ercolano, B. +2 more

Because Venus is completely shrouded by clouds, they play an important role in the planet's atmospheric dynamics. Studying the various morphological features observed on satellite imagery of the Venusian clouds is crucial to understanding not only the dynamic atmospheric processes, but also interactions between the planet's surface structures and …

2024 Astronomy and Computing
VenusExpress 0
Planetary orbital mapping and mosaicking (POMM) integrated open source software environment
DOI: 10.1016/j.ascom.2024.100788 Bibcode: 2024A&C....4600788L

Logan, Thomas L.; Smyth, Michael M.; Calef, Fred J.

Several Open Source planetary orbital mapping and utility image processing software packages, including, VICAR, AFIDS, ISIS, GDAL, and GeoTIFF, have been integrated into a single software environment (POMM), where package programs can be run independently from a Linux command line, or combined in synergistic scripts that facilitate advanced trans-…

2024 Astronomy and Computing
MEx 0
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
DOI: 10.1016/j.ascom.2024.100787 Bibcode: 2024A&C....4600787G

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…

2024 Astronomy and Computing
Gaia 0