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11 results on '"Lentner, Geoffrey"'

1. Inferencing Progenitor and Explosion Properties of Evolving Core-collapse Supernovae from Zwicky Transient Facility Light Curves

Author

Subrayan, Bhagya M., Milisavljevic, Danny, Moriya, Takashi J., Weil, Kathryn E., Lentner, Geoffrey, Linvill, Mark, Banovetz, John, Garretson, Braden, Reynolds, Jack, Sravan, Niharika, Chornock, Ryan, and Margutti, Rafaella

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract

We analyze a sample of 45 Type II supernovae from the Zwicky Transient Facility (ZTF) public survey using a grid of hydrodynamical models in order to assess whether theoretically-driven forecasts can intelligently guide follow up observations supporting all-sky survey alert streams. We estimate several progenitor properties and explosion physics parameters including zero-age-main-sequence (ZAMS) mass, mass-loss rate, kinetic energy, 56Ni mass synthesized, host extinction, and the time of explosion. Using complete light curves we obtain confident characterizations for 34 events in our sample, with the inferences of the remaining 11 events limited either by poorly constraining data or the boundaries of our model grid. We also simulate real-time characterization of alert stream data by comparing our model grid to various stages of incomplete light curves (t less than 25 days, t less than 50 days, all data), and find that some parameters are more reliable indicators of true values at early epochs than others. Specifically, ZAMS mass, time of explosion, steepness parameter beta, and host extinction are reasonably constrained with incomplete light curve data, whereas mass-loss rate, kinetic energy and 56Ni mass estimates generally require complete light curves spanning greater than 100 days. We conclude that real-time modeling of transients, supported by multi-band synthetic light curves tailored to survey passbands, can be used as a powerful tool to identify critical epochs of follow up observations. Our findings are relevant to identify, prioritize, and coordinate efficient follow up of transients discovered by Vera C. Rubin Observatory., Comment: 27 pages, 14 figures, Accepted to The Astrophysical Journal

Published
2022
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2. Real-Time Value-Driven Data Augmentation in the Era of LSST

Author

Sravan, Niharika, Milisavljevic, Dan, Reynolds, Jack M., Lentner, Geoffrey, and Linvill, Mark

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

The deluge of data from time-domain surveys is rendering traditional human-guided data collection and inference techniques impractical. We propose a novel approach for conducting data collection for science inference in the era of massive large-scale surveys that uses value-based metrics to autonomously strategize and co-ordinate follow-up in real-time. We demonstrate the underlying principles in the Recommender Engine For Intelligent Transient Tracking (REFITT) that ingests live alerts from surveys and value-added inputs from data brokers to predict the future behavior of transients and design optimal data augmentation strategies given a set of scientific objectives. The prototype presented in this paper is tested to work given simulated Rubin Observatory Legacy Survey of Space and Time (LSST) core-collapse supernova (CC SN) light-curves from the PLAsTiCC dataset. CC SNe were selected for the initial development phase as they are known to be difficult to classify, with the expectation that any learning techniques for them should be at least as effective for other transients. We demonstrate the behavior of REFITT on a random LSST night given ~32000 live CC SNe of interest. The system makes good predictions for the photometric behavior of the events and uses them to plan follow-up using a simple data-driven metric. We argue that machine-directed follow-up maximizes the scientific potential of surveys and follow-up resources by reducing downtime and bias in data collection., Comment: Published in The Astrophysical Journal

Published
2020
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3. Co-limitation towards lower latitudes shapes global forest diversity gradients

Author

Liang, Jingjing, Gamarra, Javier G. P., Picard, Nicolas, Zhou, Mo, Pijanowski, Bryan, Jacobs, Douglass F., Reich, Peter B., Crowther, Thomas W., Nabuurs, Gert-Jan, de-Miguel, Sergio, Fang, Jingyun, Woodall, Christopher W., Svenning, Jens-Christian, Jucker, Tommaso, Bastin, Jean-Francois, Wiser, Susan K., Slik, Ferry, Hérault, Bruno, Alberti, Giorgio, Keppel, Gunnar, Hengeveld, Geerten M., Ibisch, Pierre L., Silva, Carlos A., ter Steege, Hans, Peri, Pablo L., Coomes, David A., Searle, Eric B., von Gadow, Klaus, Jaroszewicz, Bogdan, Abbasi, Akane O., Abegg, Meinrad, Yao, Yves C. Adou, Aguirre-Gutiérrez, Jesús, Zambrano, Angelica M. Almeyda, Altman, Jan, Alvarez-Dávila, Esteban, Álvarez-González, Juan Gabriel, Alves, Luciana F., Amani, Bienvenu H. K., Amani, Christian A., Ammer, Christian, Ilondea, Bhely Angoboy, Antón-Fernández, Clara, Avitabile, Valerio, Aymard, Gerardo A., Azihou, Akomian F., Baard, Johan A., Baker, Timothy R., Balazy, Radomir, Bastian, Meredith L., Batumike, Rodrigue, Bauters, Marijn, Beeckman, Hans, Benu, Nithanel Mikael Hendrik, Bitariho, Robert, Boeckx, Pascal, Bogaert, Jan, Bongers, Frans, Bouriaud, Olivier, Brancalion, Pedro H. S., Brandl, Susanne, Brearley, Francis Q., Briseno-Reyes, Jaime, Broadbent, Eben N., Bruelheide, Helge, Bulte, Erwin, Catlin, Ann Christine, Cazzolla Gatti, Roberto, César, Ricardo G., Chen, Han Y. H., Chisholm, Chelsea, Cienciala, Emil, Colletta, Gabriel D., Corral-Rivas, José Javier, Cuchietti, Anibal, Cuni-Sanchez, Aida, Dar, Javid A., Dayanandan, Selvadurai, de Haulleville, Thales, Decuyper, Mathieu, Delabye, Sylvain, Derroire, Géraldine, DeVries, Ben, Diisi, John, Do, Tran Van, Dolezal, Jiri, Dourdain, Aurélie, Durrheim, Graham P., Obiang, Nestor Laurier Engone, Ewango, Corneille E. N., Eyre, Teresa J., Fayle, Tom M., Feunang, Lethicia Flavine N., Finér, Leena, Fischer, Markus, Fridman, Jonas, Frizzera, Lorenzo, de Gasper, André L., Gianelle, Damiano, Glick, Henry B., Gonzalez-Elizondo, Maria Socorro, Gorenstein, Lev, Habonayo, Richard, Hardy, Olivier J., Harris, David J., Hector, Andrew, Hemp, Andreas, Herold, Martin, Hillers, Annika, Hubau, Wannes, Ibanez, Thomas, Imai, Nobuo, Imani, Gerard, Jagodzinski, Andrzej M., Janecek, Stepan, Johannsen, Vivian Kvist, Joly, Carlos A., Jumbam, Blaise, Kabelong, Banoho L. P. R., Kahsay, Goytom Abraha, Karminov, Viktor, Kartawinata, Kuswata, Kassi, Justin N., Kearsley, Elizabeth, Kennard, Deborah K., Kepfer-Rojas, Sebastian, Khan, Mohammed Latif, Kigomo, John N., Kim, Hyun Seok, Klauberg, Carine, Klomberg, Yannick, Korjus, Henn, Kothandaraman, Subashree, Kraxner, Florian, Kumar, Amit, Kuswandi, Relawan, Lang, Mait, Lawes, Michael J., Leite, Rodrigo V., Lentner, Geoffrey, Lewis, Simon L., Libalah, Moses B., Lisingo, Janvier, López-Serrano, Pablito Marcelo, Lu, Huicui, Lukina, Natalia V., Lykke, Anne Mette, Maicher, Vincent, Maitner, Brian S., Marcon, Eric, Marshall, Andrew R., Martin, Emanuel H., Martynenko, Olga, Mbayu, Faustin M., Mbuvi, Musingo T. E., Meave, Jorge A., Merow, Cory, Miscicki, Stanislaw, Moreno, Vanessa S., Morera, Albert, Mukul, Sharif A., Müller, Jörg C., Murdjoko, Agustinus, Nava-Miranda, Maria Guadalupe, Ndive, Litonga Elias, Neldner, Victor J., Nevenic, Radovan V., Nforbelie, Louis N., Ngoh, Michael L., N’Guessan, Anny E., Ngugi, Michael R., Ngute, Alain S. K., Njila, Emile Narcisse N., Nyako, Melanie C., Ochuodho, Thomas O., Oleksyn, Jacek, Paquette, Alain, Parfenova, Elena I., Park, Minjee, Parren, Marc, Parthasarathy, Narayanaswamy, Pfautsch, Sebastian, Phillips, Oliver L., Piedade, Maria T. F., Piotto, Daniel, Pollastrini, Martina, Poorter, Lourens, Poulsen, John R., Poulsen, Axel Dalberg, Pretzsch, Hans, Rodeghiero, Mirco, Rolim, Samir G., Rovero, Francesco, Rutishauser, Ervan, Sagheb-Talebi, Khosro, Saikia, Purabi, Sainge, Moses Nsanyi, Salas-Eljatib, Christian, Salis, Antonello, Schall, Peter, Schepaschenko, Dmitry, Scherer-Lorenzen, Michael, Schmid, Bernhard, Schöngart, Jochen, Šebeň, Vladimír, Sellan, Giacomo, Selvi, Federico, Serra-Diaz, Josep M., Sheil, Douglas, Shvidenko, Anatoly Z., Sist, Plinio, Souza, Alexandre F., Stereńczak, Krzysztof J., Sullivan, Martin J. P., Sundarapandian, Somaiah, Svoboda, Miroslav, Swaine, Mike D., Targhetta, Natalia, Tchebakova, Nadja, Trethowan, Liam A., Tropek, Robert, Mukendi, John Tshibamba, Umunay, Peter Mbanda, Usoltsev, Vladimir A., Vaglio Laurin, Gaia, Valentini, Riccardo, Valladares, Fernando, van der Plas, Fons, Vega-Nieva, Daniel José, Verbeeck, Hans, Viana, Helder, Vibrans, Alexander C., Vieira, Simone A., Vleminckx, Jason, Waite, Catherine E., Wang, Hua-Feng, Wasingya, Eric Katembo, Wekesa, Chemuku, Westerlund, Bertil, Wittmann, Florian, Wortel, Verginia, Zawiła-Niedźwiecki, Tomasz, Zhang, Chunyu, Zhao, Xiuhai, Zhu, Jun, Zhu, Xiao, Zhu, Zhi-Xin, Zo-Bi, Irie C., and Hui, Cang

Published
2022
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4. Novel Proposals for FAIR, Automated, Recommendable, and Robust Workflows

Author

Abhinit, Ishan, Adams, Emily K., Alam, Khairul, Chase, Brian, Deelman, Ewa, Gorenstein, Lev, Hudson, Stephen, Islam, Tanzima, Larson, Jeffrey, Lentner, Geoffrey, Mandal, Anirban, Navarro, John-Luke, Nicolae, Bogdan, Pouchard, Line, Ross, Rob, Roy, Banani, Rynge, Mats, Serebrenik, Alexander, Vahi, Karan, Wild, Stefan, Xin, Yufeng, Ferreira da Silva, Rafael, Filgueira, Rosa, and University of St Andrews. School of Computer Science

Subjects
MCC, QA75, FAIR principles, Scientific workflows, Data integrity, QA75 Electronic computers. Computer science, Machine learning, High performance computing, 3rd-DAS, Ensembles, NIS, Computer Science(all)
Abstract

Funding: This work is partly funded by NSF award OAC-1839900. This material is based upon work supported by the U.S. Department of Energy, Office of Science, under contract number DE-AC02-06CH11357. libEnsemble was developed as part of the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. This research used resources of the OLCF at ORNL, which is supported by the Office of Science of the U.S. DOE under Contract No. DE-AC05-00OR22725. Lightning talks of the Workflows in Support of Large-Scale Science (WORKS) workshop are a venue where the workflow community (researchers, developers, and users) can discuss work in progress, emerging technologies and frameworks, and training and education materials. This paper summarizes the WORKS 2022 lightning talks, which cover five broad topics: data integrity of scientific workflows; a machine learning-based recommendation system; a Python toolkit for running dynamic ensembles of simulations; a cross-platform, high-performance computing utility for processing shell commands; and a meta(data) framework for reproducing hybrid workflows. Postprint

Published
2022

7. Python 201

Author

Lentner, Geoffrey, primary, Maji, Amiya, additional, and Gorenstein, Lev, additional

Published
2020
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11. The local Cygnus cold cloud and further constraints on a local hot bubble.

Author

Lentner, Geoffrey Robert

Subjects
Physics
Abstract

Recent studies of the local interstellar medium have identified regions of nearby cold neutral gas with unexpected low temperatures and high pressures well within the boundaries of the local cavity (Meyer et al., 2006). Now, a multi-wavelength study of the local Leo cold cloud (LLCC) has strengthened our understanding of this apparent conflict with the conventional view of this environment (Peek et al., 2011, Meyer et al., 2012). The soft X-ray background observed here cannot be completely accounted for by a local hot bubble model (Snowden et al., 2015). Interstellar absorption of Na I (D2 λ5889.591 and D1 λ5895.924) was found towards δ Cygni (Welty et al., 1994). The present study will cover an extensive preliminary search of a 40 deg2 field centered here. Using archival data from ELODIE, 41 of 284 targets have measurable interstellar absorption. Three of these occur along site lines to stars within the local cavity and represent the identification of a new nearby cloud. Further, the author has developed a suite of precision software tools packaged as an open source library for Python 3. This library builds on other popular modern packages for Python in astronomy and may help to accelerate the pace of investigation and discovery in spectroscopy.

Published
2015

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