Results 61 to 70 of about 486 (135)

ABC-SN: Attention-based Classifier for Supernova Spectra

The Astrophysical Journal
While significant advances have been made in photometric classification ahead of the millions of transient events and hundreds of supernovae (SNe) each night that the Vera C.
Willow Fox Fortino, Federica B. Bianco, Pavlos Protopapas, Daniel Muthukrishna, Austin Brockmeier   +4 more
doaj   +1 more source

Polka-dotted Stars: A Hierarchical Model for Mapping Stellar Surfaces Using Occultation Light Curves and the Case of TOI-3884

The Astrophysical Journal
We present StarryStarryProcess , a novel hierarchical Bayesian framework for mapping stellar surfaces using exoplanet transit light curves. While previous methods relied solely on stellar rotational light curves—which contain limited information about ...
Sabina Sagynbayeva, Will M. Farr, Brett M. Morris, Rodrigo Luger   +3 more
doaj   +1 more source

Astro2020 Science White Paper: The Next Decade of Astroinformatics and Astrostatistics

, 2019
Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quality data from new telescopes, and especially with the advent of deep and large astronomical surveys, it is becoming clear that future advances will also rely heavily on how ...
Siemiginowska, A., Eadie, G., Czekala, I., Feigelson, E., Ford, E. B., Kashyap, V., Kuhn, M., Loredo, T., Ntampaka, M., Stevens, A., Avelino, A., Borne, K., Budavari, T., Burkhart, B., Cisewski-Kehe, J., Civano, F., Chilingarian, I., van Dyk, D. A., Fabbiano, G., Finkbeiner, D. P., Foreman-Mackey, D., Freeman, P., Fruscione, A., Goodman, A. A., Graham, M., Guenther, H. M., Hakkila, J., Hernquist, L., Huppenkothen, D., James, D. J., Law, C., Lazio, J., Lee, T., López-Morales, M., Mahabal, A. A., Mandel, K., Meng, X. L., Moustakas, J., Muna, D., Peek, J. E. G., Richards, G., Portillo, S. K. N., Scargle, J., de Souza, R. S., Speagle, J. S., Stassun, K. G., Stenning, D. C., Taylor, S. R., Tremblay, G. R., Trimble, V., Yanamandra-Fisher, P. A., Young, C. A.   +51 more
openaire   +2 more sources

A Multi-Level Validation and Traceability Framework for AI-Generated Telescope Scheduling Decisions

With the gradual introduction of AI into telescope scheduling, AI-based decision-making has shown advantages in handling complex multi-constraint problems.
Chuanjun Wang, Hengchu Xiao
core   +1 more source

Stellar Classification with Vision Transformer and SDSS Photometric Images

With the development of large-scale sky surveys, an increasing number of stellar photometric images have been obtained. However, most stars lack spectroscopic data, which hinders stellar classification.
Xin Li, Yi Yang
core   +1 more source

paired: A Statistical Framework for Detecting Stellar Binarity with Gaia RVs. I. Sensitivity to Unresolved Binaries

The Astrophysical Journal
Data Release 3 (DR3) from the Gaia Mission includes radial velocity measurements of over 33 million targets. Among many scientific applications, the overlap of this stellar sample with targeted exoplanet transit survey stars presents an opportunity to ...
Quadry Chance, Daniel Foreman-Mackey, Sarah Ballard, Andrew R. Casey, Trevor J. David, Adrian M. Price-Whelan   +5 more
doaj   +1 more source

Unsupervised classification of eclipsing binary light curves through k-medoids clustering. [PDF]

J Appl Stat, 2020
Modak S, Chattopadhyay T, Chattopadhyay AK.   +2 more
europepmc   +1 more source

Computational AstroStatistics: Fast Algorithms and Efficient Statistics for Density Estimation in Large Astronomical Datasets

, 2000
We present initial results on the use of Mixture Models for density estimation in large astronomical databases. We provide herein both the theoretical and experimental background for using a mixture model of Gaussians based on the Expectation Maximization (EM) Algorithm.
Nichol, R. C., Connolly, A. J., Moore, A. W., Schneider, J., Genovese, C., Wasserman, L.   +5 more
openaire   +2 more sources

HyperDecouple_Net: A Decoupling Algorithm for Crosstalk in 2D Spectral Images

This paper addresses the imaging crosstalk problem in 2D spectra from the LAMOST Phase II upgrade, caused by increased fiber density. We propose HyperDecouple_Net, a hypernetwork-based decoupling algorithm designed to overcome key limitations of existing
Qiong Chen, Zewei Chen
core   +1 more source

Self-Supervised Spectral Representation Learning for LAMOST

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has collected tens of millions of spectra, providing an unprecedented resource for large-scale spectroscopic studies.
Lei Yuan, Zhenping Yi, Anhua Zhou, Wenjun Zhang, Yuchen Liang, Yihan Song   +5 more
core   +1 more source