Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST)

Author:

Schmidt S J1ORCID,Malz A I234,Soo J Y H56,Almosallam I A78,Brescia M9ORCID,Cavuoti S910,Cohen-Tanugi J11,Connolly A J12,DeRose J1314151617,Freeman P E18,Graham M L12ORCID,Iyer K G1920,Jarvis M J2122ORCID,Kalmbach J B12,Kovacs E23,Lee A B18,Longo G10,Morrison C B12,Newman J A24,Nourbakhsh E1,Nuss E11,Pospisil T18,Tranin H11,Wechsler R H251626,Zhou R1524ORCID,Izbicki R2728

Affiliation:

1. Department of Physics, University of California, One Shields Ave., Davis, CA, 95616, USA

2. German Centre of Cosmological Lensing, Ruhr-Universitaet Bochum, Universitaetsstraße 150, 44801 Bochum, Germany

3. Center for Cosmology and Particle Physics, New York University, 726 Broadway, New York, 10003, USA

4. Department of Physics, New York University, 726 Broadway, New York, 10003, USA

5. School of Physics, University of Science Malaysia, 11800 USM, Pulau Pinang, Malaysia

6. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK

7. King Abdulaziz City for Science and Technology, Riyadh 11442, Saudi Arabia

8. Information Engineering, Parks Road, Oxford, OX1 3PJ, UK

9. INAF-Astronomical Observatory of Capodimonte, Salita Moiariello 16, 80131 Napoli, Italy

10. Department of Physics E. Pancini, University Federico II, via Cinthia 6, I-80126, Napoli, Italy

11. Laboratoire Univers et Particules de Montpellier, Université de Montpellier, CNRS, Montpellier, France

12. DIRAC Institute and Department of Astronomy, University of Washington, Box 351580, U.W., Seattle WA 98195, USA

13. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA

14. Berkeley Center for Cosmological Physics, Department of Physics, University of California, Berkeley CA 94720

15. Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA

16. Kavli Institute for Particle Astrophysics and Cosmology and Department of Physics, Stanford University, Stanford, CA 94305, USA

17. Department of Particle Physics and Astrophysics, SLAC National Accelerator Laboratory, Stanford, CA 94305, USA

18. Department of Statistics & Data Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA

19. Dunlap Institute for Astronomy & Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4, Canada

20. Department of Physics and Astronomy, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019 USA

21. Astrophysics, Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford, OX1 3RH, UK

22. Department of Physics and Astronomy, University of the Western Cape, Bellville 7535, South Africa

23. Argonne National Laboratory, Lemont, IL 60439, USA

24. Department of Physics and Astronomy and the Pittsburgh Particle Physics, Astrophysics and Cosmology Center (PITT PACC), University of Pittsburgh, Pittsburgh, PA 15260, USA

25. Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA

26. SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA

27. Department of Statistics, Federal University of Sao Carlos, Sao Carlos, Brazil

28. External collaborator

Abstract

Abstract Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing twelve photo-z algorithms applied to mock data produced forLarge Synoptic Survey Telescope The Rubin Observatory Legacy Survey of Space and Time (lsst) Dark Energy Science Collaboration (desc). By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. We report systematic biases and overall over/under-breadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate (CDE) loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performance metrics.

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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