The VISTA Variables in the V\'ia L\'actea eXtended (VVVX) ESO public survey: Completion of the observations and legacy

Autor: Saito, R. K., Hempel, M., Alonso-García, J., Lucas, P. W., Minniti, D., Alonso, S., Baravalle, L., Borissova, J., Caceres, C., Chené, A. N., Cross, N. J. G., Duplancic, F., Garro, E. R., Gómez, M., Ivanov, V. D., Kurtev, R., Luna, A., Majaess, D., Navarro, M. G., Pullen, J. B., Rejkuba, M., Sanders, J. L., Smith, L. C., Albino, P. H. C., Alonso, M. V., Amôres, E. B., Angeloni, R., Arias, J. I., Arnaboldi, M., Barbuy, B., Bayo, A., Beamin, J. C., Bedin, L. R., Bellini, A., Benjamin, R. A., Bica, E., Bonatto, C. J., Botan, E., Braga, V. F., Brown, D. A., Cabral, J. B., Camargo, D., Garatti, A. Caratti o, Carballo-Bello, J. A., Catelan, M., Chavero, C., Chijani, M. A., Clariá, J. J., Coldwell, G. V., Peña, C. Contreras, Ramos, R. Contreras, Corral-Santana, J. M., Cortés, C. C., Cortés-Contreras, M., Cruz, P., Daza-Perilla, I. V., Debattista, V. P., Dias, B., Donoso, L., D'Souza, R., Emerson, J. P., Federle, S., Fermiano, V., Fernandez, J., Fernández-Trincado, J. G., Ferreira, T., Lopes, C. E. Ferreira, Firpo, V., Flores-Quintana, C., Fraga, L., Froebrich, D., Galdeano, D., Gavignaud, I., Geisler, D., Gerhard, O. E., Gieren, W., Gonzalez, O. A., Gramajo, L. V., Gran, F., Granitto, P. M., Griggio, M., Guo, Z., Gurovich, S., Hilker, M., Jones, H. R. A., Kammers, R., Kuhn, M. A., Kumar, M. S . N., Kundu, R., Lares, M., Libralato, M., Lima, E., Maccarone, T. J., Cortés, P. Marchant, Martin, E. L., Masetti, N., Matsunaga, N., Mauro, F., McDonald, I., Mejías, A., Mesa, V., Milla-Castro, F. P., Minniti, J. H., Bidin, C. Moni, Montenegro, K., Morris, C., Motta, V., Navarete, F., Molina, C. Navarro, Nikzat, F., Castellón, J. L. Nilo, Obasi, C., Ortigoza-Urdaneta, M., Palma, T., Parisi, C., Ramírez, K. Pena, Pereyra, L., Perez, N., Petralia, I., Pichel, A., Pignata, G., Alegría, S. Ramírez, Rojas, A. F., Rojas, D., Roman-Lopes, A., Rovero, A. C., Saroon, S., Schmidt, E. O., Schröder, A. C., Schultheis, M., Sgró, M. A., Solano, E., Soto, M., Stecklum, B., Steeghs, D., Tamura, M., Tissera, P., Valcarce, A. A. R., Valotto, C. A., Vasquez, S., Villalon, C., Villanova, S., Cádiz, F. Vivanco, Bacigalupo, R. Zelada, Zijlstra, A., Zoccali, M.

Publikováno v: A&A 689, A148 (2024)

The ESO public survey VISTA Variables in the V\'ia L\'actea (VVV) surveyed the inner Galactic bulge and the adjacent southern Galactic disk from $2009-2015$. Upon its conclusion, the complementary VVV eXtended (VVVX) survey has expanded both the temp

Externí odkaz: http://arxiv.org/abs/2406.16646

Delivering laser performance conditions to enable fusion ignition, and beyond at the National Ignition Facility

Autor: Di Nicola, JM., Suratwala, T., Pelz, L., Heebner, J., Aden, R., Alessi, D., Amula, S., Barnes, A., Bhasker, A., Bond, T., Bude, J., Buckley, B., Browning, D., Cabral, J., CalonicoSoto, A., Carr, W., Chang, L., Chou, J., Cohen, S., Cope, T., Cross, D., Deveno, R., DeVore, P., Deland, A., Nicola, P. Di, Dumbacher, T., Erbert, G., Erickson, M., Erlandson, A., Filip, C., Fratanduono, D., Gottesman, N., Gowda, A., Handler, A., Hernandez, V.J., Herriot, S., Horner, J., House, R., Kalantar, D., Kegelmeyer, L., Kinsella, C., Lanier, T., Larson, D., Galloudec, B. Le, Lusk, J., MacGowan, B., McLaren, S., Manes, K., McCandless, K., Mennerat, G., Miller, C., Monticelli, M., Muir, R., Negres, R., Nelson, J., Nostrand, M., Ordoñez, M., Orth, C., Padilla, E., Pao, A., Penner, J., Petersen, T., Prantil, M., Raman, R., Rana, S., Raymond, B., Ruiz, N., Sacks, R., Schrauth, S., Shaw, M., Sommer, S., Siegel, L., Spaeth, M., Stolz, C., Tam, M.F., Tate, T., Trummer, S., VanBlarcom, D., Varadan, K., Vella, A., Wargo, A., Wang, L., Waxer, L., Wegner, P., Welday, B., Whitman, P., Widmayer, C., Williams, W., Wong, L., Wong, N., Van Wonterghem, B., Yang, S., Brunton, G.

Publikováno v: In High Energy Density Physics September 2024 52

Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV

Autor: Cabral, J. B., Lares, M., Gurovich, S., Minniti, D., Granitto, P. M.

Publikováno v: A&A 652, A151 (2021)

As most of the modern astronomical sky surveys produce data faster than humans can analyze it, Machine Learning (ML) has become a central tool in Astronomy. Modern ML methods can be characterized as highly resistant to some experimental errors. Howev

Externí odkaz: http://arxiv.org/abs/2105.01714

Fundamental optimization of steam Rankine cycle power plants

Autor: Porto-Hernandez, L.A., Vargas, J.V.C., Munoz, M.N., Galeano-Cabral, J., Ordonez, J.C., Balmant, W., Mariano, A.B.

Publikováno v: In Energy Conversion and Management 1 August 2023 289

From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning

Autor: Cabral, J. B., Sánchez, B., Ramos, F., Gurovich, S., Granitto, P., Vanderplas, J.

Machine learning algorithms are highly useful for the classification of time series data in astronomy in this era of peta-scale public survey data releases. These methods can facilitate the discovery of new unknown events in most astrophysical areas,

Externí odkaz: http://arxiv.org/abs/1809.02154