Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method
Abstract
Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating -band flux information to refine redshift estimates (i.e. using fluxes as opposed to only ); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.
Keywords
Cite
@article{arxiv.2408.00922,
title = {Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method},
author = {A. Campos and B. Yin and S. Dodelson and A. Amon and A. Alarcon and C. Sánchez and G. M. Bernstein and G. Giannini and J. Myles and S. Samuroff and O. Alves and F. Andrade-Oliveira and K. Bechtol and M. R. Becker and J. Blazek and H. Camacho and A. Carnero Rosell and M. Carrasco Kind and R. Cawthon and C. Chang and R. Chen and A. Choi and J. Cordero and C. Davis and J. DeRose and H. T. Diehl and C. Doux and A. Drlica-Wagner and K. Eckert and T. F. Eifler and J. Elvin-Poole and S. Everett and X. Fang and A. Ferté and O. Friedrich and M. Gatti and D. Gruen and R. A. Gruendl and I. Harrison and W. G. Hartley and K. Herner and H. Huang and E. M. Huff and M. Jarvis and E. Krause and N. Kuropatkin and P. -F. Leget and N. MacCrann and J. McCullough and A. Navarro-Alsina and S. Pandey and J. Prat and M. Raveri and R. P. Rollins and A. Roodman and R. Rosenfeld and A. J. Ross and E. S. Rykoff and J. Sanchez and L. F. Secco and I. Sevilla-Noarbe and E. Sheldon and T. Shin and M. A. Troxel and I. Tutusaus and T. N. Varga and R. H. Wechsler and B. Yanny and Y. Zhang and J. Zuntz and M. Aguena and J. Annis and D. Bacon and S. Bocquet and D. Brooks and D. L. Burke and J. Carretero and F. J. Castander and M. Costanzi and L. N. da Costa and J. De Vicente and P. Doel and I. Ferrero and B. Flaugher and J. Frieman and J. García-Bellido and E. Gaztanaga and G. Gutierrez and S. R. Hinton and D. L. Hollowood and K. Honscheid and D. J. James and K. Kuehn and M. Lima and H. Lin and J. L. Marshall and J. Mena-Fernández and F. Menanteau and R. Miquel and R. L. C. Ogando and M. Paterno and M. E. S. Pereira and A. Pieres and A. A. Plazas Malagón and A. Porredon and E. Sanchez and D. Sanchez Cid and M. Smith and E. Suchyta and M. E. C. Swanson and G. Tarle and C. To and V. Vikram and N. Weaverdyck},
journal= {arXiv preprint arXiv:2408.00922},
year = {2024}
}