Results 11 to 20 of about 154,240 (279)

Classification of Exoplanetary Light Curves Using Artificial Intelligence

AI
In this article, we propose a robust star classification methodology leveraging light curves collected from 15 datasets within the Kepler field in the visible optical spectrum.
Leticia Flores-Pulido, Liliana Ibeth Barbosa-Santillán, Ma. Teresa Orozco-Aguilera, Bertha Patricia Guzman-Velázquez   +3 more
doaj   +3 more sources

Classification of Variable Star Light Curves with Convolutional Neural Network

Galaxies
The classification of variable stars is essential for understanding stellar evolution and dynamics. With the growing volume of light curve data from extensive surveys, there is a need for automated and accurate classification methods. Traditional methods
Almat Akhmetali, Timur Namazbayev, Gulnur Subebekova, Marat Zaidyn, Aigerim Akniyazova, Yeskendyr Ashimov, Nurzhan Ussipov   +6 more
doaj   +3 more sources

Light-curve classification with recurrent neural networks for GOTO: dealing with imbalanced data [PDF]

Monthly Notices of the Royal Astronomical Society, 2021
ABSTRACT The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream.
U F Burhanudin, J R Maund, T Killestein, K Ackley, M J Dyer, J Lyman, K Ulaczyk, R Cutter, Y-L Mong, D Steeghs, D K Galloway, V Dhillon, P O’Brien, G Ramsay, K Noysena, R Kotak, R P Breton, L Nuttall, E Pallé, D Pollacco, E Thrane, S Awiphan, P Chote, A Chrimes, E Daw, C Duffy, R Eyles-Ferris, B Gompertz, T Heikkilä, P Irawati, M R Kennedy, A Levan, S Littlefair, L Makrygianni, D Mata-Sánchez, S Mattila, J McCormac, D Mkrtichian, J Mullaney, U Sawangwit, E Stanway, R Starling, P Strøm, S Tooke, K Wiersema   +44 more
core   +10 more sources

Deep-learnt classification of light curves [PDF]

2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017
8 pages, 9 figures, 6 tables, 2 listings. Accepted to 2017 IEEE Symposium Series on Computational Intelligence (SSCI)
Mahabal, Ashish, Sheth, Kshiteej, Gieseke, Fabian, Pai, Akshay, Djorgovski, S. George, Drake, Andrew, Graham, Matthew, Collaboration, the CSS/CRTS/PTF   +7 more
core   +5 more sources

Identifying Exoplanets with Deep Learning. V. Improved Light-curve Classification for TESS Full-frame Image Observations

The Astronomical Journal, 2023
The TESS mission produces a large amount of time series data, only a small fraction of which contain detectable exoplanetary transit signals.
Evan Tey, Dan Moldovan, Michelle Kunimoto, Chelsea X. Huang, Avi Shporer, Tansu Daylan, Daniel Muthukrishna, Andrew Vanderburg, Anne Dattilo, George R. Ricker, S. Seager   +10 more
doaj   +2 more sources

Supernova light curve classification using attention and other techniques [PDF]

, 2023
Even in the era of deep-learning the huge amount of astronomical data available has not yet allowed us to solve the problem of Supernova (SN) light curve classification. These explosive transients are photometrically difficult to label not only because of their irregular sampling and noise, but also because of the dissimilarities that exist between ...
Ibsen, Amanda
openaire   +4 more sources

Real-time Light Curve Classification Framework for the Wide Field Survey Telescope Using Modified Semisupervised Variational Autoencoder

The Astronomical Journal
Modern time-domain astronomy will benefit from the vast data collected by survey telescopes. The 2.5 m Wide Field Survey Telescope (WFST), with its powerful capabilities, is promising to make significant contributions in the era of large sky surveys.
Yongling Tang, Lulu Fan, Zhen Wan, Yating Liu, Yan Lu   +4 more
doaj   +2 more sources

Deep Attention-based Supernovae Classification of Multiband Light Curves

The Astronomical Journal, 2022
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 scarcity, the processing of multiband light curves is a challenging task due to
Óscar Pimentel, Pablo A. Estévez, Francisco Förster   +2 more
doaj   +3 more sources

Superphot+: Real-time Fitting and Classification of Supernova Light Curves

The Astrophysical Journal
Photometric classifications of supernova (SN) light curves have become necessary to utilize the full potential of large samples of observations obtained from wide-field photometric surveys, such as the Zwicky Transient Facility (ZTF) and the Vera C ...
Kaylee M. de Soto, V. Ashley Villar, Edo Berger, Sebastian Gomez, Griffin Hosseinzadeh, Doug Branton, Sandro Campos, Melissa DeLucchi, Jeremy Kubica, Olivia Lynn, Konstantin Malanchev, Alex I. Malz   +11 more
doaj   +4 more sources

Observations and light curve solutions of the eclipsing binaries USNO-B1.0 1395-0370184 and USNO-B1.0 1395-0370731 [PDF]

Serbian Astronomical Journal, 2016
We present follow-up photometric observations in Sloan filters g', i' of the newly discovered eclipsing stars USNO-B1.0 1395-0370184 and USNO-B1.0 1395-0370731.
Kjurkchieva D., Popov V.A., Vasileva D., Petrov N.   +3 more
doaj   +2 more sources