Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Malz, Alex I."'
Autor:
Crenshaw, John Franklin, Kalmbach, J. Bryce, Gagliano, Alexander, Yan, Ziang, Connolly, Andrew J., Malz, Alex I., Schmidt, Samuel J., Collaboration, The LSST Dark Energy Science
Evaluating the accuracy and calibration of the redshift posteriors produced by photometric redshift (photo-z) estimators is vital for enabling precision cosmology and extragalactic astrophysics with modern wide-field photometric surveys. Evaluating p
Externí odkaz:
http://arxiv.org/abs/2405.04740
Autor:
Lee, Jaemyoung Jason, Sako, Masao, Kessler, Richard, Malz, Alex I., Collaboration, The LSST Dark Energy Science
Differential Chromatic Refraction (DCR) is caused by the wavelength dependence of our atmosphere's refractive index, which shifts the apparent positions of stars and galaxies and distorts their shapes depending on their spectral energy distributions
Externí odkaz:
http://arxiv.org/abs/2405.04522
Autor:
de Soto, Kaylee M., Villar, Ashley, Berger, Edo, Gomez, Sebastian, Hosseinzadeh, Griffin, Branton, Doug, Campos, Sandro, DeLucchi, Melissa, Kubica, Jeremy, Lynn, Olivia, Malanchev, Konstantin, Malz, Alex I.
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.
Externí odkaz:
http://arxiv.org/abs/2403.07975
Autor:
Moskowitz, Irene, Gawiser, Eric, Crenshaw, John Franklin, Andrews, Brett H., Malz, Alex I., Schmidt, Samuel, Collaboration, The LSST Dark Energy Science
Publikováno v:
ApJL 967 L6 (2024)
Large imaging surveys will rely on photometric redshifts (photo-z's), which are typically estimated through machine learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for LSST
Externí odkaz:
http://arxiv.org/abs/2402.15551
Autor:
Malz, Alex I., Dai, Mi, Ponder, Kara A., Ishida, Emille E. O., Gonzalez-Gaitain, Santiago, Durgesh, Rupesh, Krone-Martins, Alberto, de Souza, Rafael S., Kennamer, Noble, Sreejith, Sreevarsha, Galbany, Lluis, Collaboration, The LSST Dark Energy Science, Initiative, The Cosmostatistics
Context: When selecting a classifier to use for a supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, i.e. contamination within the photometrically classified SN Ia sample, rather
Externí odkaz:
http://arxiv.org/abs/2305.14421
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:
Breivik, Katelyn, Connolly, Andrew J., Ford, K. E. Saavik, Jurić, Mario, Mandelbaum, Rachel, Miller, Adam A., Norman, Dara, Olsen, Knut, O'Mullane, William, Price-Whelan, Adrian, Sacco, Timothy, Sokoloski, J. L., Villar, Ashley, Acquaviva, Viviana, Ahumada, Tomas, AlSayyad, Yusra, Alves, Catarina S., Andreoni, Igor, Anguita, Timo, Best, Henry J., Bianco, Federica B., Bonito, Rosaria, Bradshaw, Andrew, Burke, Colin J., de Campos, Andresa Rodrigues, Cantiello, Matteo, Caplar, Neven, Chandler, Colin Orion, Chan, James, da Costa, Luiz Nicolaci, Danieli, Shany, Davenport, James R. A., Fabbian, Giulio, Fagin, Joshua, Gagliano, Alexander, Gall, Christa, Camargo, Nicolás Garavito, Gawiser, Eric, Gezari, Suvi, Gomboc, Andreja, Gonzalez-Morales, Alma X., Graham, Matthew J., Gschwend, Julia, Guy, Leanne P., Holman, Matthew J., Hsieh, Henry H., Hundertmark, Markus, Ilić, Dragana, Ishida, Emille E. O., Jurkić, Tomislav, Kannawadi, Arun, Kosakowski, Alekzander, Kovačević, Andjelka B., Kubica, Jeremy, Lanusse, François, Lazar, Ilin, Levine, W. Garrett, Li, Xiaolong, Lu, Jing, Luna, Gerardo Juan Manuel, Mahabal, Ashish A., Malz, Alex I., Mao, Yao-Yuan, Medan, Ilija, Moeyens, Joachim, Nikolić, Mladen, Nikutta, Robert, O'Dowd, Matt, Olsen, Charlotte, Pearson, Sarah, Pedraza, Ilhuiyolitzin Villicana, Popinchalk, Mark, Popović, Luka C., Pritchard, Tyler A., Quint, Bruno C., Radović, Viktor, Ragosta, Fabio, Riccio, Gabriele, Riley, Alexander H., Rożek, Agata, Sánchez-Sáez, Paula, Sarro, Luis M., Saunders, Clare, Savić, Đorđe V., Schmidt, Samuel, Scott, Adam, Shirley, Raphael, Smotherman, Hayden R., Stetzler, Steven, Storey-Fisher, Kate, Street, Rachel A., Trilling, David E., Tsapras, Yiannis, Ustamujic, Sabina, van Velzen, Sjoert, Vázquez-Mata, José Antonio, Venuti, Laura, Wyatt, Samuel, Yu, Weixiang, Zabludoff, Ann
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depe
Externí odkaz:
http://arxiv.org/abs/2208.02781
Autor:
Lokken, Martine, Gagliano, Alexander, Narayan, Gautham, Hložek, Renée, Kessler, Richard, Crenshaw, John Franklin, Salo, Laura, Alves, Catarina S., Chatterjee, Deep, Vincenzi, Maria, Malz, Alex I., Collaboration, The LSST Dark Energy Science
As we observe a rapidly growing number of astrophysical transients, we learn more about the diverse host galaxy environments in which they occur. Host galaxy information can be used to purify samples of cosmological Type Ia supernovae, uncover the pr
Externí odkaz:
http://arxiv.org/abs/2206.02815
The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate a
Externí odkaz:
http://arxiv.org/abs/2202.12775
Autor:
Dey, Biprateep, Newman, Jeffrey A., Andrews, Brett H., Izbicki, Rafael, Lee, Ann B., Zhao, David, Rau, Markus Michael, Malz, Alex I.
Many astrophysical analyses depend on estimates of redshifts (a proxy for distance) determined from photometric (i.e., imaging) data alone. Inaccurate estimates of photometric redshift uncertainties can result in large systematic errors. However, pro
Externí odkaz:
http://arxiv.org/abs/2110.15209