Photometric redshifts with machine learning, lights and shadows on a complex data science use case.
作者： Stefano Cavuoti , Massimo Brescia , Valeria Amaro , Giuseppe Riccio , Giuseppe Longo
DOI: 10.3389/FSPAS.2021.658229
关键词:
摘要: The current role of data-driven science is constantly increasing its importance within Astrophysics, due to the huge amount multi-wavelength data collected every day, characterized by complex and high-volume information requiring efficient as much possible automated exploration tools. Furthermore, accomplish main legacy objectives future or incoming large deep survey projects, such JWST, LSST Euclid, a crucial played an accurate estimation photometric redshifts, whose knowledge would permit detection analysis extended peculiar sources disentangling low-z from high-z contribute solve modern cosmological discrepancies. recent redshift challenges, organized several like pushed exploitation multi-dimensional observed ad hoc simulated improve optimize redshifts prediction statistical characterization based on both SED template fitting machine learning methodologies. But they also provided new impetus in investigation hybrid techniques, aimed at conjugating positive peculiarities different methodologies, thus optimizing accuracy maximizing range coverage, particularly important regime, where spectroscopic ground truth poorly available. In context we summarize what learned proposed more than decade research.
arxiv.org
sci-hub.st 参考文章(143)
Teuvo Kohonen, Self-organized formation of topologically correct feature maps Biological Cybernetics. ,vol. 43, pp. 509- 521 ,(1988) , 10.1007/BF00337288
Ben Hoyle, Markus Michael Rau, Kerstin Paech, Christopher Bonnett, Stella Seitz, Jochen Weller, Anomaly detection for machine learning redshifts applied to SDSS galaxies Monthly Notices of the Royal Astronomical Society. ,vol. 452, pp. 4183- 4194 ,(2015) , 10.1093/MNRAS/STV1551
Ron Kohavi, George H. John, The Wrapper Approach Springer, Boston, MA. pp. 33- 50 ,(1998) , 10.1007/978-1-4615-5725-8_3
A. Merloni, P. Predehl, N. Meidinger, M. Freyberg, T.H. Reiprich, K. Dennerl, T. Boller, A. Rau, H. Böhringer, M. Sasaki, M. Brusa, A. Georgakakis, J. Robrade, F. Haberl, H. Brunner, W. E. Becker, M. Salvato, J. Wilms, S. Allen, A. Santangelo, P. Friedrich, K. Nandra, A. Schwope, J. Mohr, G. Hasinger, eROSITA science book: mapping the structure of the energetic universe arXiv: High Energy Astrophysical Phenomena. ,(2012)
Christopher Bonnett, MA Troxel, William Hartley, Adam Amara, Boris Leistedt, Matthew R Becker, Gary M Bernstein, Sarah Louise Bridle, Claudio Bruderer, MT Busha, Matías Carrasco Kind, MJ Childress, FJ Castander, Chihway Chang, Martin Crocce, Tamara M Davis, TF Eifler, J Frieman, C Gangkofner, Enrique Gaztanaga, Karl Glazebrook, Daniel Gruen, Tomasz Kacprzak, A King, Juliana Kwan, Ofer Lahav, G Lewis, Chris Lidman, H Lin, Niall MacCrann, Ramon Miquel, CR O’Neill, A Palmese, Hiranya V Peiris, Alexandre Refregier, Eduardo Rozo, ES Rykoff, Iftach Sadeh, C Sánchez, Erin Sheldon, Syed Uddin, Risa H Wechsler, J Zuntz, Timothy Abbott, Filipe B Abdalla, S Allam, Robert Armstrong, M Banerji, Anne Hollister Bauer, Aurélien Benoit-Lévy, Emmanuel Bertin, D Brooks, Elizabeth Buckley-Geer, David Lyle Burke, Diego Capozzi, Aurelio Carnero Rosell, J Carretero, Carlos Eduardo Cunha, Christopher B D’Andrea, LN Da Costa, Darren L DePoy, S Desai, H Thomas Diehl, Jörg P Dietrich, Peter Doel, Angelo Fausti Neto, Enrique Fernandez, Brenna Flaugher, P Fosalba, David W Gerdes, Robert A Gruendl, K Honscheid, Bhuvnesh Jain, David J James, Michael Jarvis, AG Kim, Kyler Kuehn, N Kuropatkin, TS Li, M Lima, Marcio Antonio Geimba Maia, M March, Jennifer L Marshall, Paul Martini, P Melchior, Christopher J Miller, E Neilsen, Robert C Nichol, B Nord, R Ogando, AA Plazas, Kevin Reil, Anita K Romer, Aaron Roodman, Masao Sako, E Sanchez, B Santiago, Robert Christopher Smith, Marcelle Soares-Santos, Flávia Sobreira, Eric Suchyta, Molly EC Swanson, Gregory Tarle, J Thaler, D Thomas, Vinu Vikram, AR Walker, (Dark Energy Survey Collaboration), None, Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing Physical Review D. ,vol. 94, pp. 042005- ,(2016) , 10.1103/PHYSREVD.94.042005
J Green, P Schechter, C Baltay, R Bean, D Bennett, R Brown, C Conselice, M Donahue, X Fan, BS Gaudi, C Hirata, J Kalirai, T Lauer, B Nichol, N Padmanabhan, S Perlmutter, B Rauscher, J Rhodes, T Roellig, D Stern, T Sumi, A Tanner, Y Wang, D Weinberg, E Wright, N Gehrels, R Sambruna, W Traub, J Anderson, K Cook, P Garnavich, L Hillenbrand, Z Ivezic, E Kerins, J Lunine, P McDonald, M Penny, M Phillips, G Rieke, A Riess, R van der Marel, RK Barry, E Cheng, D Content, R Cutri, R Goullioud, K Grady, G Helou, C Jackson, J Kruk, M Melton, C Peddie, N Rioux, M Seiffert, Wide-Field InfraRed Survey Telescope WFIRST Final Report arXiv: Instrumentation and Methods for Astrophysics. ,(2012)
Ibrahim A. Almosallam, Sam N. Lindsay, Matt J. Jarvis, Stephen J. Roberts, A Sparse Gaussian Process Framework for Photometric Redshift Estimation Monthly Notices of the Royal Astronomical Society. ,vol. 455, pp. 2387- 2401 ,(2016) , 10.1093/MNRAS/STV2425
M. Viola, M. Cacciato, M. Brouwer, K. Kuijken, H. Hoekstra, P. Norberg, A. S. G. Robotham, E. van Uitert, M. Alpaslan, I. K. Baldry, A. Choi, J. T. A. de Jong, S. P. Driver, T. Erben, A. Grado, Alister W. Graham, C. Heymans, H. Hildebrandt, A. M. Hopkins, N. Irisarri, B. Joachimi, J. Loveday, L. Miller, R. Nakajima, P. Schneider, C. Sifón, G. Verdoes Kleijn, Dark matter halo properties of GAMA galaxy groups from 100 square degrees of KiDS weak lensing data Monthly Notices of the Royal Astronomical Society. ,vol. 452, pp. 3529- 3550 ,(2015) , 10.1093/MNRAS/STV1447
V. Rashkov, O. Lahav, M. Banerji, F. B. Abdalla, A comparison of six photometric redshift methods applied to 1.5 million luminous red galaxies Monthly Notices of the Royal Astronomical Society. ,vol. 417, pp. 1891- 1903 ,(2011) , 10.1111/J.1365-2966.2011.19375.X
M. Paolillo, S. Cavuoti, M. Brescia, C. Tortora, G. Longo, N. R. Napolitano, M. Radovich, F. La Barbera, M. Capaccioli, J. T. A. de Jong, F. Getman, A. Grado, Machine-learning-based photometric redshifts for galaxies of the ESO Kilo-Degree Survey data release 2 Monthly Notices of the Royal Astronomical Society. ,vol. 452, pp. 3100- 3105 ,(2015) , 10.1093/MNRAS/STV1496