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11 results on '"Istvan Szapudi"'

1. Introducing the Texas Euclid Survey for Lyα (TESLA) Survey: Initial Study Correlating Galaxy Properties to Lyα Emission

Author

Óscar A. Chávez Ortiz, Steven L. Finkelstein, Dustin Davis, Gene Leung, Erin Mentuch Cooper, Micaela Bagley, Rebecca Larson, Caitlin M. Casey, Adam P. McCarron, Karl Gebhardt, Yuchen Guo, Chenxu Liu, Isaac Laseter, Jason Rhodes, Ralf Bender, Max Fabricius, Ariel G. Sánchez, Claudia Scarlata, Peter Capak, Lukas Zalesky, David Sanders, Istvan Szapudi, Eric Baxter, Conor McPartland, John R. Weaver, Sune Toft, Bahram Mobasher, Nao Suzuki, and Nima Chartab

Subjects
Galaxies, Surveys, Reionization, Lyman-alpha galaxies, Astrophysics, QB460-466
Abstract

We present the Texas Euclid Survey for Ly α (TESLA), a spectroscopic survey in the 10 deg ^2 of the Euclid North Ecliptic Pole (NEP) field. Using TESLA, we study how the physical properties of Ly α emitters (LAEs) correlate with Ly α emission to understand the escape of Ly α emission from galaxies at redshifts of 2–3.5. We present an analysis of 43 LAEs performed in the NEP field using early data from the TESLA survey. We use Subaru Hyper Suprime-Cam imaging in the grizy bands, Spitzer/IRAC channels 1 and 2 from the Hawaii 20 deg ^2 (H20) survey, and spectra acquired by the Visible Integral-Field Replicable Unit Spectrograph (VIRUS) on the Hobby–Eberly Telescope. We perform spectral energy distribution (SED) fitting to compute the galaxy properties of 43 LAEs, and study correlations between stellar mass, star formation rate (SFR), and dust to the Ly α rest-frame equivalent width ( W _Ly _α ). We uncover marginal (1 σ significance) correlations between stellar mass and W _Ly _α , and SFR and W _Ly _α , with a Spearman correlation coefficient of −0. ${34}_{-.14}^{+.17}$ and −0. ${37}_{-.14}^{+.16}$ , respectively. We show that the W _Ly _α distribution of the 43 LAEs is consistent with being drawn from an exponential distribution with an e-folding scale of W _0 = 150 Å. Once complete the TESLA survey will enable the study of ≳50,000 LAEs to explore more correlations between galaxy properties and W _Ly _α . The large sample size will allow the construction of a predictive model for W _Ly _α as a function of SED-derived galaxy properties, which could be used to improve Ly α -based constraints on reionization.

Published
2023
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5. Galaxy Clustering in Early Sloan Digital Sky Survey Redshift Data

Author

Mark SubbaRao, Douglas Tucker, Idit Zehavi, Avery Meiksin, Albert Stebbins, Julianne Dalcanton, Jon Loveday, Francisco Javier Castander, Peter Kunszt, David Schlegel, Scott Dodelson, Istvan Csabai, Alexander Szalay, Gillian Knapp, Houjun Mo, and Istvan Szapudi

Subjects
Physics, Absolute magnitude, 010308 nuclear & particles physics, Velocity dispersion, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, Redshift survey, 01 natural sciences, Galaxy, Redshift, Luminosity, Correlation function (statistical mechanics), Space and Planetary Science, 0103 physical sciences, Surface brightness, 010303 astronomy & astrophysics
Abstract

We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5,700 km/s < cz < 39,000 km/s, distributed in several long but narrow (2.5-5 degree) segments, covering 690 square degrees. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 Mpc/h. The two-dimensional correlation function \xi(r_p,\pi) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, \xi(r)=(r/6.1+/-0.2 Mpc/h)^{-1.75+/-0.03}, for 0.1 Mpc/h < r < 16 Mpc/h. The galaxy pairwise velocity dispersion is \sigma_{12} ~ 600+/-100 km/s for projected separations 0.15 Mpc/h < r_p < 5 Mpc/h. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r < 10 Mpc/h: subsamples with absolute magnitude ranges centered on M_*-1.5, M_*, and M_*+1.5 have real-space correlation functions that are parallel power laws of slope ~ -1.8 with correlation lengths of approximately 7.4 Mpc/h, 6.3 Mpc/h, and 4.7 Mpc/h, respectively.

Published
2002
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6. Higher Order Moments of the Angular Distribution of Galaxies from Early Sloan Digital Sky Survey Data

Author

Istvan Szapudi, Joshua A. Frieman, Roman Scoccimarro, Alexander S. Szalay, Andrew J. Connolly, Scott Dodelson, Daniel J. Eisenstein, James E. Gunn, David Johnston, Stephen Kent, Jon Loveday, Avery Meiksin, Robert C. Nichol, Ryan Scranton, Albert Stebbins, Michael S. Vogeley, James Annis, Neta A. Bahcall, J. Brinkman, Istvan Csabai, Mamoru Doi, Masataka Fukugita, Željko Ivezić, Rita S. J. Kim, Gillian R. Knapp, Don Q. Lamb, Brian C. Lee, Robert H. Lupton, Timothy A. McKay, Jeff Munn, John Peoples, Jeff Pier, Constance Rockosi, David Schlegel, Christopher Stoughton, Douglas L. Tucker, Brian Yanny, and Donald G. York

Subjects
Physics, Stars, Angular distribution, Space and Planetary Science, Astrophysics::Instrumentation and Methods for Astrophysics, Astrophysics::Solar and Stellar Astrophysics, Higher order moments, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, Cluster analysis, Astrophysics::Galaxy Astrophysics, Galaxy
Abstract

– 3 –areas of bad seeing, contamination from bright stars, ghosts, and high galacticextinction masked out. This survey region, which forms part of the SDSS EarlyData Release, is the same as that for which two-point angular clustering statisticshave recently been computed. The third and fourth moments of the cell counts,s

Published
2002
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7. The Fifth Data Release of the Sloan Digital Sky Survey

Author

Jennifer K. Adelman‐McCarthy, Marcel A. Agueros, Sahar S. Allam, Kurt S. J. Anderson, Scott F. Anderson, James Annis, Neta A. Bahcall, Coryn A. L. Bailer‐Jones, Ivan K. Baldry, J. C. Barentine, Timothy C. Beers, V. Belokurov, Andreas Berlind, Mariangela Bernardi, Michael R. Blanton, John J. Bochanski, William N. Boroski, D. M. Bramich, Howard J. Brewington, Jarle Brinchmann, J. Brinkmann, Robert J. Brunner, Tamas Budavari, Larry N. Carey, Samuel Carliles, Michael A. Carr, Francisco J. Castander, A. J. Connolly, R. J. Cool, Carlos E. Cunha, Istvan Csabai, Julianne J. Dalcanton, Mamoru Doi, Daniel J. Eisenstein, Michael L. Evans, N. W. Evans, Xiaohui Fan, Douglas P. Finkbeiner, Scott D. Friedman, Joshua A. Frieman, Masataka Fukugita, Bruce Gillespie, G. Gilmore, Karl Glazebrook, Jim Gray, Eva K. Grebel, James E. Gunn, Ernst de Haas, Patrick B. Hall, Michael Harvanek, Suzanne L. Hawley, Jeffrey Hayes, Timothy M. Heckman, John S. Hendry, Gregory S. Hennessy, Robert B. Hindsley, Christopher M. Hirata, Craig J. Hogan, David W. Hogg, Jon A. Holtzman, Shin‐ichi Ichikawa, Takashi Ichikawa, Željko Ivezić, Sebastian Jester, David E. Johnston, Anders M. Jorgensen, Mario Jurić, Guinevere Kauffmann, Stephen M. Kent, S. J. Kleinman, G. R. Knapp, Alexei Yu. Kniazev, Richard G. Kron, Jurek Krzesinski, Nikolay Kuropatkin, Donald Q. Lamb, Hubert Lampeitl, Brian C. Lee, R. French Leger, Marcos Lima, Huan Lin, Daniel C. Long, Jon Loveday, Robert H. Lupton, Rachel Mandelbaum, Bruce Margon, David Martinez‐Delgado, Takahiko Matsubara, Peregrine M. McGehee, Timothy A. McKay, Avery Meiksin, Jeffrey A. Munn, Reiko Nakajima, Thomas Nash, Eric H. Neilsen, Jr., Heidi Jo Newberg, Robert C. Nichol, Maria Nieto‐Santisteban, Atsuko Nitta, Hiroaki Oyaizu, Sadanori Okamura, Jeremiah P. Ostriker, Nikhil Padmanabhan, Changbom Park, John Peoples, Jr., Jeffrey R. Pier, Adrian C. Pope, Dimitri Pourbaix, Thomas R. Quinn, M. Jordan Raddick, Paola Re Fiorentin, Gordon T. Richards, Michael W. Richmond, Hans‐Walter Rix, Constance M. Rockosi, David J. Schlegel, Donald P. Schneider, Ryan Scranton, Uroš Seljak, Erin Sheldon, Kazu Shimasaku, Nicole M. Silvestri, J. Allyn Smith, Vernesa Smolčić, Stephanie A. Snedden, Albert Stebbins, Chris Stoughton, Michael A. Strauss, Mark SubbaRao, Yasushi Suto, Alexander S. Szalay, Istvan Szapudi, Paula Szkody, Max Tegmark, Aniruddha R. Thakar, Christy A. Tremonti, Douglas L. Tucker, Alan Uomoto, Daniel E. Vanden Berk, Jan Vandenberg, S. Vidrih, Michael S. Vogeley, Wolfgang Voges, Nicole P. Vogt, David H. Weinberg, Andrew A. West, Simon D. M. White, Brian Wilhite, Brian Yanny, D. R. Yocum, Donald G. York, Idit Zehavi, Stefano Zibetti, and Daniel B. Zucker

Subjects
Physics, Imaging systems in astronomy, Stars--Observations, Astronomy, media_common.quotation_subject, Astrophysics (astro-ph), Astrophysics::Instrumentation and Methods for Astrophysics, FOS: Physical sciences, Astronomy and Astrophysics, Quasar, Segue, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Redshift, Galaxy, Stars, Space and Planetary Science, Sky, Survey quality, Data release, Astrophysics::Galaxy Astrophysics, media_common
Abstract

This paper describes the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). DR5 includes all survey quality data taken through June 2005 and represents the completion of the SDSS-I project (whose successor, SDSS-II will continue through mid-2008). It includes five-band photometric data for 217 million objects selected over 8000 square degrees, and 1,048,960 spectra of galaxies, quasars, and stars selected from 5713 square degrees of that imaging data. These numbers represent a roughly 20% increment over those of the Fourth Data Release; all the data from previous data releases are included in the present release. In addition to "standard" SDSS observations, DR5 includes repeat scans of the southern equatorial stripe, imaging scans across M31 and the core of the Perseus cluster of galaxies, and the first spectroscopic data from SEGUE, a survey to explore the kinematics and chemical evolution of the Galaxy. The catalog database incorporates several new features, including photometric redshifts of galaxies, tables of matched objects in overlap regions of the imaging survey, and tools that allow precise computations of survey geometry for statistical investigations., Comment: ApJ Supp, in press, October 2007. This paper describes DR5. The SDSS Sixth Data Release (DR6) is now public, available from http://www.sdss.org

Published
2007

8. The Fourth Data Release of the Sloan Digital Sky Survey

Author

Jennifer K. Adelman‐McCarthy, Marcel A. Agueros, Sahar S. Allam, Kurt S. J. Anderson, Scott F. Anderson, James Annis, Neta A. Bahcall, Ivan K. Baldry, J. C. Barentine, Andreas Berlind, Mariangela Bernardi, Michael R. Blanton, William N. Boroski, Howard J. Brewington, Jarle Brinchmann, J. Brinkmann, Robert J. Brunner, Tamas Budavari, Larry N. Carey, Michael A. Carr, Francisco J. Castander, A. J. Connolly, Istvan Csabai, Paul C. Czarapata, Julianne J. Dalcanton, Mamoru Doi, Feng Dong, Daniel J. Eisenstein, Michael L. Evans, Xiaohui Fan, Douglas P. Finkbeiner, Scott D. Friedman, Joshua A. Frieman, Masataka Fukugita, Bruce Gillespie, Karl Glazebrook, Jim Gray, Eva K. Grebel, James E. Gunn, Vijay K. Gurbani, Ernst de Haas, Patrick B. Hall, Frederick H. Harris, Michael Harvanek, Suzanne L. Hawley, Jeffrey Hayes, John S. Hendry, Gregory S. Hennessy, Robert B. Hindsley, Christopher M. Hirata, Craig J. Hogan, David W. Hogg, Donald J. Holmgren, Jon A. Holtzman, Shin‐ichi Ichikawa, Željko Ivezić, Sebastian Jester, David E. Johnston, Anders M. Jorgensen, Mario Jurić, Stephen M. Kent, S. J. Kleinman, G. R. Knapp, Alexei Yu. Kniazev, Richard G. Kron, Jurek Krzesinski, Nikolay Kuropatkin, Donald Q. Lamb, Hubert Lampeitl, Brian C. Lee, R. French Leger, Huan Lin, Daniel C. Long, Jon Loveday, Robert H. Lupton, Bruce Margon, David Martinez‐Delgado, Rachel Mandelbaum, Takahiko Matsubara, Peregrine M. McGehee, Timothy A. McKay, Avery Meiksin, Jeffrey A. Munn, Reiko Nakajima, Thomas Nash, Eric H. Neilsen, Jr., Heidi Jo Newberg, Peter R. Newman, Robert C. Nichol, Tom Nicinski, Maria Nieto‐Santisteban, Atsuko Nitta, William O’Mullane, Sadanori Okamura, Russell Owen, Nikhil Padmanabhan, George Pauls, John Peoples, Jr., Jeffrey R. Pier, Adrian C. Pope, Dimitri Pourbaix, Thomas R. Quinn, Gordon T. Richards, Michael W. Richmond, Constance M. Rockosi, David J. Schlegel, Donald P. Schneider, Joshua Schroeder, Ryan Scranton, Uroš Seljak, Erin Sheldon, Kazu Shimasaku, J. Allyn Smith, Vernesa Smolčić, Stephanie A. Snedden, Chris Stoughton, Michael A. Strauss, Mark SubbaRao, Alexander S. Szalay, Istvan Szapudi, Paula Szkody, Max Tegmark, Aniruddha R. Thakar, Douglas L. Tucker, Alan Uomoto, Daniel E. Vanden Berk, Jan Vandenberg, Michael S. Vogeley, Wolfgang Voges, Nicole P. Vogt, Lucianne M. Walkowicz, David H. Weinberg, Andrew A. West, Simon D. M. White, Yongzhong Xu, Brian Yanny, D. R. Yocum, Donald G. York, Idit Zehavi, Stefano Zibetti, and Daniel B. Zucker

Subjects
media_common.quotation_subject, Milky Way, Astronomy, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Imaging data, surveys, Thick disk, Astrophysics::Galaxy Astrophysics, media_common, Physics, Imaging systems in astronomy, Stars--Observations, Astrophysics (astro-ph), Astrophysics::Instrumentation and Methods for Astrophysics, Astronomy and Astrophysics, Quasar, NATURAL SCIENCES. Physics, Galaxy, PRIRODNE ZNANOSTI. Fizika, atlases, Stars, Space and Planetary Science, Sky, Data release, catalogs
Abstract

This paper describes the fourth data release of the Sloan Digital Sky Survey (SDSS), including all survey-quality data taken through June 2004. The data release includes five-band photometric data for 180 million objects selected over 6670 deg^2, and 673,280 spectra of galaxies, quasars, and stars selected from 4783 deg^2 of that imaging data using the standard SDSS target selection algorithms. These numbers represent a roughly 25% increment over those of the Third Data Release. The Fourth Data Release also includes an additional 131,840 spectra of objects selected using a variety of alternative algorithms, to address scientific issues ranging from the kinematics of stars in the Milky Way thick disk to populations of faint galaxies and quasars., Comment: 26 pages, 2 figures

Published
2006
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9. Projected Three-Point Correlation Functions and Galaxy Bias

Author

Zheng Zheng and Istvan Szapudi

Subjects
Physics, Astrophysics (astro-ph), FOS: Physical sciences, Astronomy and Astrophysics, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Correlation function (astronomy), Galaxy, Redshift, symbols.namesake, Nonlinear system, Fourier transform, Dimension (vector space), Space and Planetary Science, symbols, Multipole expansion, Bispectrum
Abstract

The three-point correlation function (3PCF) can now be measured in large galaxy redshift surveys, but in three dimensions its interpretation is complicated by the presence of redshift-space distortions. I investigate the projected 3PCF, where these distortions are eliminated by integrating over the redshift dimension, as is commonly done for the two-point correlation function. The calculation of the projected 3PCF from the real-space, three-dimensional bispectrum is greatly simplified by expanding both quantities in Fourier components, analogous to Szapudi's (2004) expansion of the three-dimensional quantities in multipole components. In the weakly nonlinear regime, the bispectrum can be well represented by the first few Fourier components. There is a well-known relation between the reduced 3PCFs of matter and galaxies in the weakly nonlinear regime, which can be used to infer galaxy bias factors if the real-space three-dimensional galaxy correlation functions (two-point and three-point) can be measured. I show that the same relation holds for the reduced {\it projected} 3PCFs if these are properly defined. These results should aid determinations of galaxy bias from large redshift surveys by eliminating the complication of redshift-space distortions., Comment: 13 pages, 1 figure. To appear in ApJ (Oct. 20th, 2004). References added. Minor revisons to match the version in press

Published
2004
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10. The Sloan Digital Sky Survey: Technical Summary

Author

Donald G. York, J. Adelman, John E. Anderson, Jr., Scott F. Anderson, James Annis, Neta A. Bahcall, J. A. Bakken, Robert Barkhouser, Steven Bastian, Eileen Berman, William N. Boroski, Steve Bracker, Charlie Briegel, John W. Briggs, J. Brinkmann, Robert Brunner, Scott Burles, Larry Carey, Michael A. Carr, Francisco J. Castander, Bing Chen, Patrick L. Colestock, A. J. Connolly, J. H. Crocker, István Csabai, Paul C. Czarapata, John Eric Davis, Mamoru Doi, Tom Dombeck, Daniel Eisenstein, Nancy Ellman, Brian R. Elms, Michael L. Evans, Xiaohui Fan, Glenn R. Federwitz, Larry Fiscelli, Scott Friedman, Joshua A. Frieman, Masataka Fukugita, Bruce Gillespie, James E. Gunn, Vijay K. Gurbani, Ernst de Haas, Merle Haldeman, Frederick H. Harris, J. Hayes, Timothy M. Heckman, G. S. Hennessy, Robert B. Hindsley, Scott Holm, Donald J. Holmgren, Chi-hao Huang, Charles Hull, Don Husby, Shin-Ichi Ichikawa, Takashi Ichikawa, Željko Ivezić, Stephen Kent, Rita S. J. Kim, E. Kinney, Mark Klaene, A. N. Kleinman, S. Kleinman, G. R. Knapp, John Korienek, Richard G. Kron, Peter Z. Kunszt, D. Q. Lamb, B. Lee, R. French Leger, Siriluk Limmongkol, Carl Lindenmeyer, Daniel C. Long, Craig Loomis, Jon Loveday, Rich Lucinio, Robert H. Lupton, Bryan MacKinnon, Edward J. Mannery, P. M. Mantsch, Bruce Margon, Peregrine McGehee, Timothy A. McKay, Avery Meiksin, Aronne Merelli, David G. Monet, Jeffrey A. Munn, Vijay K. Narayanan, Thomas Nash, Eric Neilsen, Rich Neswold, Heidi Jo Newberg, R. C. Nichol, Tom Nicinski, Mario Nonino, Norio Okada, Sadanori Okamura, Jeremiah P. Ostriker, Russell Owen, A. George Pauls, John Peoples, R. L. Peterson, Donald Petravick, Jeffrey R. Pier, Adrian Pope, Ruth Pordes, Angela Prosapio, Ron Rechenmacher, Thomas R. Quinn, Gordon T. Richards, Michael W. Richmond, Claudio H. Rivetta, Constance M. Rockosi, Kurt Ruthmansdorfer, Dale Sandford, David J. Schlegel, Donald P. Schneider, Maki Sekiguchi, Gary Sergey, Kazuhiro Shimasaku, Walter A. Siegmund, Stephen Smee, J. Allyn Smith, S. Snedden, R. Stone, Chris Stoughton, Michael A. Strauss, Christopher Stubbs, Mark SubbaRao, Alexander S. Szalay, Istvan Szapudi, Gyula P. Szokoly, Anirudda R. Thakar, Christy Tremonti, Douglas L. Tucker, Alan Uomoto, Dan Vanden Berk, Michael S. Vogeley, Patrick Waddell, Shu-i Wang, Masaru Watanabe, David H. Weinberg, Brian Yanny, and Naoki Yasuda

Subjects
2dF Galaxy Redshift Survey, Physics, media_common.quotation_subject, Astrophysics::High Energy Astrophysical Phenomena, Astrophysics (astro-ph), Astrophysics::Instrumentation and Methods for Astrophysics, FOS: Physical sciences, Astronomy and Astrophysics, Quasar, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Redshift survey, LAMOST, Extended Groth Strip, Space and Planetary Science, Sky, Monoceros Ring, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Galaxy Astrophysics, Photometric redshift, media_common
Abstract

The Sloan Digital Sky Survey (SDSS) will provide the data to support detailed investigations of the distribution of luminous and non- luminous matter in the Universe: a photometrically and astrometrically calibrated digital imaging survey of pi steradians above about Galactic latitude 30 degrees in five broad optical bands to a depth of g' about 23 magnitudes, and a spectroscopic survey of the approximately one million brightest galaxies and 10^5 brightest quasars found in the photometric object catalog produced by the imaging survey. This paper summarizes the observational parameters and data products of the SDSS, and serves as an introduction to extensive technical on-line documentation., 9 pages, 7 figures, AAS Latex. To appear in AJ, Sept 2000

Published
2000

11. A Machine-learning Approach to Predict Missing Flux Densities in Multiband Galaxy Surveys

Author

Nima Chartab, Bahram Mobasher, Asantha R. Cooray, Shoubaneh Hemmati, Zahra Sattari, Henry C. Ferguson, David B. Sanders, John R. Weaver, Daniel K. Stern, Henry J. McCracken, Daniel C. Masters, Sune Toft, Peter L. Capak, Iary Davidzon, Mark E. Dickinson, Jason Rhodes, Andrea Moneti, Olivier Ilbert, Lukas Zalesky, Conor J. R. McPartland, István Szapudi, Anton M. Koekemoer, Harry I. Teplitz, and Mauro Giavalisco

Subjects
Astronomy data analysis, Astronomy data visualization, Galaxy evolution, Astrophysics, QB460-466
Abstract

We present a new method based on information theory to find the optimal number of bands required to measure the physical properties of galaxies with desired accuracy. As a proof of concept, using the recently updated COSMOS catalog (COSMOS2020), we identify the most relevant wave bands for measuring the physical properties of galaxies in a Hawaii Two-0- (H20) and UVISTA-like survey for a sample of i < 25 AB mag galaxies. We find that with the available i -band fluxes, r , u , IRAC/ ch 2, and z bands provide most of the information regarding the redshift with importance decreasing from r band to z band. We also find that for the same sample, IRAC/ ch 2, Y , r , and u bands are the most relevant bands in stellar-mass measurements with decreasing order of importance. Investigating the intercorrelation between the bands, we train a model to predict UVISTA observations in near-IR from H20-like observations. We find that magnitudes in the YJH bands can be simulated/predicted with an accuracy of 1 σ mag scatter ≲0.2 for galaxies brighter than 24 AB mag in near-IR bands. One should note that these conclusions depend on the selection criteria of the sample. For any new sample of galaxies with a different selection, these results should be remeasured. Our results suggest that in the presence of a limited number of bands, a machine-learning model trained over the population of observed galaxies with extensive spectral coverage outperforms template fitting. Such a machine-learning model maximally comprises the information acquired over available extensive surveys and breaks degeneracies in the parameter space of template fitting inevitable in the presence of a few bands.

Published
2023
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