Zobrazeno 1 - 10
of 1 485
pro vyhledávání: '"A. D'Aléo"'
Autor:
Volnova, Alina A., Aleo, Patrick D., Lavrukhina, Anastasia, Russeil, Etienne, Semenikhin, Timofey, Gangler, Emmanuel, Ishida, Emille E. O., Kornilov, Matwey V., Korolev, Vladimir, Malanchev, Konstantin, Pruzhinskaya, Maria V., Sreejith, Sreevarsha
Publikováno v:
In: Baixeries, J., Ignatov, D.I., Kuznetsov, S.O., Stupnikov, S. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2023. Communications in Computer and Information Science, vol 2086. Springer, Cham
SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and
Externí odkaz:
http://arxiv.org/abs/2410.18875
Autor:
Voloshina, A. S., Lavrukhina, A. D., Pruzhinskaya, M. V., Malanchev, K. L., Ishida, E. E. O., Krushinsky, V. V., Aleo, P. D., Gangler, E., Kornilov, M. V., Korolev, V. S., Russeil, E., Semenikhin, T. A., Sreejith, S., Volnova, A. A.
Publikováno v:
Monthly Notices of the Royal Astronomical Society, Volume 533, Issue 4, October 2024, Pages 4309-4323
Most of the stars in the Universe are M spectral class dwarfs, which are known to be the source of bright and frequent stellar flares. In this paper, we propose new approaches to discover M-dwarf flares in ground-based photometric surveys. We employ
Externí odkaz:
http://arxiv.org/abs/2404.07812
Autor:
Aleo, P. D., Engel, A. W., Narayan, G., Angus, C. R., Malanchev, K., Auchettl, K., Baldassare, V. F., Berres, A., de Boer, T. J. L., Boyd, B. M., Chambers, K. C., Davis, K. W., Esquivel, N., Farias, D., Foley, R. J., Gagliano, A., Gall, C., Gao, H., Gomez, S., Grayling, M., Jones, D. O., Lin, C. -C., Magnier, E. A., Mandel, K. S., Matheson, T., Raimundo, S. I., Shah, V. G., Soraisam, M. D., de Soto, K. M., Vicencio, S., Villar, V. A., Wainscoat, R. J.
We present LAISS (Lightcurve Anomaly Identification and Similarity Search), an automated pipeline to detect anomalous astrophysical transients in real-time data streams. We deploy our anomaly detection model on the nightly ZTF Alert Stream via the AN
Externí odkaz:
http://arxiv.org/abs/2404.01235
Autor:
Russeil, E., Malanchev, K. L., Aleo, P. D., Ishida, E. E. O., Pruzhinskaya, M. V., Gangler, E., Lavrukhina, A. D., Volnova, A. A., Voloshina, A., Semenikhin, T., Sreejith, S., Kornilov, M. V., Korolev, V. S.
We present Rainbow, a physically motivated framework which enables simultaneous multi-band light curve fitting. It allows the user to construct a 2-dimensional continuous surface across wavelength and time, even in situations where the number of obse
Externí odkaz:
http://arxiv.org/abs/2310.02916
The next generation of wide-field deep astronomical surveys will deliver unprecedented amounts of images through the 2020s and beyond. As both the sensitivity and depth of observations increase, more blended sources will be detected. This reality can
Externí odkaz:
http://arxiv.org/abs/2307.05826
Autor:
Gagliano, Alexander, Contardo, Gabriella, Foreman-Mackey, Daniel, Malz, Alex I., Aleo, Patrick D.
Substantial effort has been devoted to the characterization of transient phenomena from photometric information. Automated approaches to this problem have taken advantage of complete phase-coverage of an event, limiting their use for triggering rapid
Externí odkaz:
http://arxiv.org/abs/2305.08894
Autor:
Coulter, D. A., Jones, D. O., McGill, P., Foley, R. J., Aleo, P. D., Bustamante-Rosell, M. J., Chatterjee, D., Davis, K. W., Dickinson, C., Engel, A., Gagliano, A., Jacobson-Galán, W. V., Kilpatrick, C. D., Kutcka, J., Saux, X. K. Le, Pan, Y. -C., Quiñonez, P. J., Rojas-Bravo, C., Siebert, M. R., Taggart, K., Tinyanont, S., Wang, Q.
The modern study of astrophysical transients has been transformed by an exponentially growing volume of data. Within the last decade, the transient discovery rate has increased by a factor of ~20, with associated survey data, archival data, and metad
Externí odkaz:
http://arxiv.org/abs/2303.02154
Autor:
Aleo, P. D., Malanchev, K., Sharief, S., Jones, D. O., Narayan, G., Foley, R. J., Villar, V. A., Angus, C. R., Baldassare, V. F., Bustamante-Rosell, M. J., Chatterjee, D., Cold, C., Coulter, D. A., Davis, K. W., Dhawan, S., Drout, M. R., Engel, A., French, K. D., Gagliano, A., Gall, C., Hjorth, J., Huber, M. E., Jacobson-Galán, W. V., Kilpatrick, C. D., Langeroodi, D., Mandel, K. S., Margutti, R., Matasić, F., McGill, P., Pierel, J. D. R., Ramirez-Ruiz, E., Ransome, C. L., Rojas-Bravo, C., Siebert, M. R., Smith, K. W., de Soto, K. M., Stroh, M. C., Tinyanont, S., Taggart, K., Ward, S. M., Wojtak, R., Auchettl, K., Blanchard, P. K., de Boer, T. J. L., Boyd, B. M., Carroll, C. M., Chambers, K. C., DeMarchi, L., Dimitriadis, G., Dodd, S. A., Earl, N., Farias, D., Gao, H., Gomez, S., Grayling, M., Grillo, C., Hayes, E. E., Hung, T., Izzo, L., Khetan, N., Law-Smith, J. A. P., LeBaron, N., Lin, C. -C., Luo, Y., Magnier, E. A., Matthews, D., O'Grady, A. J. G., Pan, Y. -C., Politsch, C. A., Raimundo, S. I., Rest, A., Ridden-Harper, R., Sarangi, A., Smartt, S. J., Terreran, G., Thorp, S., Vazquez, J., Wainscoat, R. J., Wang, Q., Wasserman, A. R., Yadavalli, S. K., Yarza, R., Zenati, Y.
We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multi-color Pan-STARRS1 (PS1) griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host-galaxy associations, redshifts, spectroscopic
Externí odkaz:
http://arxiv.org/abs/2211.07128
Autor:
Malanchev, Konstantin, Kornilov, Matwey V., Pruzhinskaya, Maria V., Ishida, Emille E. O., Aleo, Patrick D., Korolev, Vladimir S., Lavrukhina, Anastasia, Russeil, Etienne, Sreejith, Sreevarsha, Volnova, Alina A., Voloshina, Anastasiya, Krone-Martins, Alberto
We describe the SNAD Viewer, a web portal for astronomers which presents a centralized view of individual objects from the Zwicky Transient Facility's (ZTF) data releases, including data gathered from multiple publicly available astronomical archives
Externí odkaz:
http://arxiv.org/abs/2211.07605
Autor:
Pruzhinskaya, Maria V., Ishida, Emille E. O., Novinskaya, Alexandra K., Russeil, Etienne, Volnova, Alina A., Malanchev, Konstantin L., Kornilov, Matwey V., Aleo, Patrick D., Korolev, Vladimir S., Krushinsky, Vadim V., Sreejith, Sreevarsha, Gangler, Emmanuel
Publikováno v:
A&A 672, A111 (2023)
We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from large-scale astronomical surveys. The main goal of this work is to explore the potential of adaptive learning techniques in ap
Externí odkaz:
http://arxiv.org/abs/2208.09053