Estimating redshifts from broadband photometry is often limited by how accurately we can map the colors of galaxies to an underlying spectral template. Current techniques utilize spectrophotometric samples of galaxies or spectra derived from spectral synthesis models. Both of these approaches have their limitations, either the sample sizes are small and often not representative of the diversity of galaxy colors or the model colors can be biased (often as a function of wavelength) which introduces systematics in the derived redshifts. In this paper we learn the underlying spectral energy distributions from an ensemble of $\sim$100K galaxies with measured redshifts and colors. We show that we are able to reconstruct emission and absorption lines at a significantly higher resolution than the broadband filters used to measure the photometry for a sample of 20 spectral templates. We find that our training algorithm reduces the fraction of outliers in the derived photometric redshifts by up to 28%, bias up to 91%, and scatter up to 25%, when compared to estimates using a standard set of spectral templates. We discuss the current limitations of this approach and its applicability for recovering the underlying properties of galaxies. Our derived templates and the code used to produce these results are publicly available in a dedicated Github repository: https://github.com/dirac-institute/photoz_template_learning.
A normalizing flow approach for the inference of star cluster properties from unresolved broadband photometry I: Comparison to spectral energy distribution fitting
Universität Heidelberg(海德堡大学);Université Côte d’Azur(蔚蓝海岸大学);Universidad Nacional Autónoma de México(墨西哥国立自治大学);INAF – Arcetri Astrophysical Observatory(意大利国家天体物理研究所阿切特里天文台);University of Wyoming(怀俄明大学);Australian National University(澳大利亚国立大学);The Johns Hopkins University(约翰斯·霍普金斯大学)
The Southern Photometric Local Universe Survey (S-PLUS) is an ongoing survey of $\sim$9300 deg$^2$ in the southern sky in a 12-band photometric system. This paper presents the second data release (DR2) of S-PLUS, consisting of 514 tiles covering an area of 950 deg$^2$. The data has been fully calibrated using a new photometric calibration technique suitable for the new generation of wide-field multi-filter surveys. This technique consists of a $χ^2$ minimisation to fit synthetic stellar templates to already calibrated data from other surveys, eliminating the need for standard stars and reducin…
Current and future imaging surveys require photometric redshifts (photo-zs) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge but is needed to advance our understanding of cosmology. In this paper we explore how the synergies between narrow-band photometric data and large imaging surveys can be exploited to improve broadband photometric redshifts. We used a multi-task learning (MTL) network to improve broadband photo-z estimates by simultaneously predicting the broadband photo-z and the narrow-band photometry from the broadband photometry. The narrow-…
Large time-domain surveys provide a unique opportunity to detect and explore variability of millions of sources on timescales from days to years. Broadband photometric variability can be used as the key selection criteria for weak type-I active galactic nuclei (AGN), when other "direct" confirmation criteria like X-ray or radio emission are unavailable. However, to detect variability of rather weak AGN powered by intermediate-mass black holes, typical sensitivity provided by existing light curve databases is insufficient. Here we present an algorithm for post-processing of light curves for sou…
The IR emission of dust heated by stars provides critical information for galaxy evolution studies. Unfortunately, observations are often limited to the MIR, making templates a necessity. Previously published templates were based on small samples of luminous galaxies, not necessarily representative of normal star-forming galaxies. We construct new dust templates, including instrument-specific relations and software tools that facilitate the estimation of the TIR luminosity and SFR based on one or several fluxes up to z=4. For the first time the templates include a dependence on both TIR lumino…
Photometric Redshifts in JWST Deep Fields: A Pixel-Based Alternative with DeepDISC
University of Illinois at Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校);Harvard & Smithsonian(哈佛与史密森尼学会);National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign(美国国家超级计算应用中心,伊利诺伊大学厄巴纳-香槟分校);Center for Artificial Intelligence Innovation, University of Illinois at Urbana-Champaign(人工智能创新中心,伊利诺伊大学厄巴纳-香槟分校);Kavli Institute of Particle Astrophysics and Cosmology(卡弗里粒子天体物理与宇宙学研究所);Stanford University(斯坦福大学);SLAC National Accelerator Laboratory(SLAC国家加速器实验室)
Probabilistic Spectral Reconstruction of Trans-Neptunian Objects from Sparse Photometry: A Framework for Taxonomy, Survey Optimization, and Outlier Detection
University of Michigan(密歇根大学);Michigan Institute for Data and AI in Society, University of Michigan(密歇根大学数据与人工智能社会研究所);University of Auckland(奥克兰大学);Lunar and Planetary Laboratory, The University of Arizona(亚利桑那大学月球与行星实验室);Case Western Reserve University(凯斯西储大学)