Simultaneous Estimation of Photometric Redshifts and SED Parameters: Improved Techniques and a Realistic Error Budget
arXiv:1502.07757 · doi:10.1088/0004-637X/804/1/8
Abstract
We seek to improve the accuracy of joint galaxy photometric redshift estimation and spectral energy distribution (SED) fitting. By simulating different sources of uncorrected systematic errors, we demonstrate that if the uncertainties on the photometric redshifts are estimated correctly, so are those on the other SED fitting parameters, such as stellar mass, stellar age, and dust reddening. Furthermore, we find that if the redshift uncertainties are over(under)-estimated, the uncertainties in SED parameters tend to be over(under)-estimated by similar amounts. These results hold even in the presence of severe systematics and provide, for the first time, a mechanism to validate the uncertainties on these parameters via comparison with spectroscopic redshifts. We propose a new technique (annealing) to re-calibrate the joint uncertainties in the photo-z and SED fitting parameters without compromising the performance of the SED fitting + photo-z estimation. This procedure provides a consistent estimation of the multidimensional probability distribution function in SED fitting + z parameter space, including all correlations. While the performance of joint SED fitting and photo-z estimation might be hindered by template incompleteness, we demonstrate that the latter is "flagged" by a large fraction of outliers in redshift, and that significant improvements can be achieved by using flexible stellar populations synthesis models and more realistic star formation histories. In all cases, we find that the median stellar age is better recovered than the time elapsed from the onset of star formation [abridged].
arXiv comment11 pages, 5 figures, 3 tables. Accepted for publication in the Astrophysical Journal
References in corpus (19)
- The Dust Content and Opacity of Actively Star-Forming Galaxies
- CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey
- EAZY: A Fast, Public Photometric Redshift Code
- A Simple Model for the Absorption of Starlight by Dust in Galaxies
- COSMOS Photometric Redshifts with 30-bands for 2-deg2
- An ultra-deep near-infrared spectrum of a compact quiescent galaxy at z=2.2
- Modeling the Panchromatic Spectral Energy Distributions of Galaxies
- CANDELS Multi-wavelength Catalogs: Source Detection and Photometry in the GOODS-South Field
- A Critical Assessment of Photometric Redshift Methods: A CANDELS Investigation
- Fitting the integrated Spectral Energy Distributions of Galaxies
- CFHTLenS: Improving the quality of photometric redshifts with precision photometry
- TPZ : Photometric redshift PDFs and ancillary information by using prediction trees and random forests
- On the Stellar Populations and Evolution of Star-Forming Galaxies at 6.3 < z < 8.6
- Estimating photometric redshifts with artificial neural networks
- SED fitting with Markov Chain Monte Carlo: Methodology and Application to z=3.1 Lyman Alpha Emitting Galaxies
- Biases and Uncertainties in Physical Parameter Estimates of Lyman Break Galaxies from Broad-band Photometry
- Improved Photometric Redshifts via Enhanced Estimates of System Response, Galaxy Templates, and Magnitude Priors
- The enrichment history of the intracluster medium: a Bayesian approach
- Real or Interloper? The Redshift Likelihoods of z>8 Galaxies in the HUDF12
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- The Main Sequence of star-forming galaxies across cosmic times
- An Older, More Quiescent Universe from Panchromatic SED Fitting of the 3D-HST Survey
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- Reconstruction of Galaxy Star Formation Histories through SED Fitting: The Dense Basis Approach
- Early Low-Mass Galaxies and Star-Cluster Candidates at z~6-9 Identified by the Gravitational Lensing Technique and Deep Optical/Near-Infrared Imaging
- Learning the Relationship between Galaxies Spectra and their Star Formation Histories using Convolutional Neural Networks and Cosmological Simulations
- The MUSE Hubble Ultra Deep Field Survey: III. Testing photometric redshifts to 30th magnitude
- {\sc mirkwood:} Fast and Accurate SED Modeling Using Machine Learning
- Value Added Catalog of physical properties of more than 1.3 million galaxies from the DESI Survey
- Hierarchical Bayesian inference of photometric redshifts with stellar population synthesis models
- A re-assessment of strong line metallicity conversions in the machine learning era
- Surrogate modelling the Baryonic Universe II: on forward modelling the colours of individual and populations of galaxies
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- Toward a stellar population catalog in the Kilo Degree Survey: the impact of stellar recipes on stellar masses and star formation rates
- Detecting episodes of star formation using Bayesian model selection
- Machine Learning vs. Spectral Energy Distribution Fitting: A Comparative Analysis of Accuracy in Stellar Mass Estimation
- Beyond mirkwood: Enhancing SED Modeling with Conformal Predictions
- The Photometric Analysis of the Environment Around Two Dusty Star-Forming Galaxies at