scholarly journals Improved photometric redshifts with colour-constrained galaxy templates for future wide-area surveys

2020 ◽  
Vol 497 (2) ◽  
pp. 1935-1945
Author(s):  
Bomee Lee ◽  
Ranga-Ram Chary
Keyword(s):  
Galaxy Evolution ◽  
Training Sample ◽  
Spectral Energy ◽  
Colour Space ◽  
Photometric Redshifts ◽  
Mid Infrared ◽  
Photometric Redshift ◽  
Template Library ◽  
Galaxy Sample ◽  
Best Fitting

ABSTRACT Cosmology and galaxy evolution studies with LSST, Euclid, and Roman, will require accurate redshifts for the detected galaxies. In this study, we present improved photometric redshift estimates for galaxies using a template library that populates three-colour space and is constrained by HST/CANDELS photometry. For the training sample, we use a sample of galaxies having photometric redshifts that allows us to train on a large, unbiased galaxy sample having deep, unconfused photometry at optical-to-mid infrared wavelengths. Galaxies in the training sample are assigned to cubes in 3D colour space, V − H, I − J, and z − H. We then derive the best-fitting spectral energy distributions of the training sample at the fixed CANDELS median photometric redshifts to construct the new template library for each individual colour cube (i.e. colour-cube-based template library). We derive photometric redshifts (photo-z) of our target galaxies using our new colour-cube-based template library and with photometry in only a limited set of bands, as expected for the aforementioned surveys. As a result, our method yields σNMAD of 0.026 and an outlier fraction of 6 per cent using only photometry in the LSST and Euclid/Roman bands. This is an improvement of ∼10 per cent on σNMAD and a reduction in outlier fraction of ∼13 per cent compared to other techniques. In particular, we improve the photo-z precision by about 30 per cent at 2 < z < 3. We also assess photo-z improvements by including K or mid-infrared bands to the ugrizYJH photometry. Our colour-cube-based template library is a powerful tool to constrain photometric redshifts for future large surveys.

scholarly journals A lack of evolution in the very bright end of the galaxy luminosity function from z ≃ 8 to 10

2020 ◽  
Vol 493 (2) ◽  
pp. 2059-2084 ◽  
Author(s):  
R A A Bowler ◽  
M J Jarvis ◽  
J S Dunlop ◽  
R J McLure ◽  
D J McLeod ◽  
...  
Keyword(s):  
Galaxy Evolution ◽  
Luminosity Function ◽  
Near Infrared ◽  
Good Description ◽  
Number Density ◽  
Photometric Redshifts ◽  
Star Forming ◽  
Photometric Redshift ◽  
Wide Range ◽  
Best Fitting

ABSTRACT We utilize deep near-infrared survey data from the UltraVISTA fourth data release (DR4) and the VIDEO survey, in combination with overlapping optical and Spitzer data, to search for bright star-forming galaxies at z ≳ 7.5. Using a full photometric redshift fitting analysis applied to the ∼6 $\, {\rm deg}^2$ of imaging searched, we find 27 Lyman break galaxies (LBGs), including 20 new sources, with best-fitting photometric redshifts in the range 7.4 < z < 9.1. From this sample, we derive the rest-frame UV luminosity function at z = 8 and z = 9 out to extremely bright UV magnitudes (MUV ≃ −23) for the first time. We find an excess in the number density of bright galaxies in comparison to the typically assumed Schechter functional form derived from fainter samples. Combined with previous studies at lower redshift, our results show that there is little evolution in the number density of very bright (MUV ∼ −23) LBGs between z ≃ 5 and z ≃ 9. The tentative detection of an LBG with best-fitting photometric redshift of z = 10.9 ± 1.0 in our data is consistent with the derived evolution. We show that a double power-law fit with a brightening characteristic magnitude (ΔM*/Δz ≃ −0.5) and a steadily steepening bright-end slope (Δβ/Δz ≃ −0.5) provides a good description of the z > 5 data over a wide range in absolute UV magnitude (−23 < MUV < −17). We postulate that the observed evolution can be explained by a lack of mass quenching at very high redshifts in combination with increasing dust obscuration within the first ${\sim}1 \, {\rm Gyr}$ of galaxy evolution.

scholarly journals An ALMA survey of the brightest sub-millimetre sources in the SCUBA-2–COSMOS field

2020 ◽  
Vol 495 (3) ◽  
pp. 3409-3430 ◽  
Author(s):  
J M Simpson ◽  
Ian Smail ◽  
U Dudzevičiūtė ◽  
Y Matsuda ◽  
B-C Hsieh ◽  
...  
Keyword(s):  
Pilot Study ◽  
Flux Density ◽  
Luminosity Function ◽  
Spectral Energy Distribution ◽  
Line Emission ◽  
Spectral Energy ◽  
Complete Sample ◽  
Photometric Redshifts ◽  
Photometric Redshift ◽  
Number Counts

ABSTRACT We present an ALMA study of the ∼180 brightest sources in the SCUBA-2 850-μm map of the COSMOS field from the S2COSMOS survey, as a pilot study for AS2COSMOS – a full survey of the ∼1000 sources in this field. In this pilot study, we have obtained 870-μm continuum maps of an essentially complete sample of the brightest 182 sub-millimetre sources ($S_{850\, \mu \rm m}\gt $ 6.2 mJy) in COSMOS. Our ALMA maps detect 260 sub-millimetre galaxies (SMGs) spanning a range in flux density of $S_{870\, \mu \rm m}$ = 0.7–19.2 mJy. We detect more than one SMG counterpart in 34 ± 2 per cent of sub-millimetre sources, increasing to 53 ± 8 per cent for SCUBA-2 sources brighter than $S_{850\, \mu \rm m}\gt $ 12 mJy. We estimate that approximately one-third of these SMG–SMG pairs are physically associated (with a higher rate for the brighter secondary SMGs, $S_{870\, \mu \rm m}\gtrsim$ 3 mJy), and illustrate this with the serendipitous detection of bright [C ii] 157.74-μm line emission in two SMGs, AS2COS 0001.1 and 0001.2 at z = 4.63, associated with the highest significance single-dish source. Using our source catalogue, we construct the interferometric 870-μm number counts at $S_{870\, \mu \rm m}\gt $ 6.2 mJy. We use the extensive archival data of this field to construct the multiwavelength spectral energy distribution of each AS2COSMOS SMG, and subsequently model this emission with magphys to estimate their photometric redshifts. We find a median photometric redshift for the $S_{870\, \mu \rm m}\gt $ 6.2 mJy AS2COSMOS sample of z = 2.87 ± 0.08, and clear evidence for an increase in the median redshift with 870-μm flux density suggesting strong evolution in the bright end of the 870-μm luminosity function.

scholarly journals Photometric redshifts for the Pan-STARRS1 survey

2020 ◽  
Vol 642 ◽  
pp. A102 ◽  
Author(s):  
P. Tarrío ◽  
S. Zarattini
Keyword(s):  
Standard Deviation ◽  
Photometric Data ◽  
Local Linear Regression ◽  
Training Set ◽  
Colour Space ◽  
Photometric Redshifts ◽  
Additional Advantage ◽  
Robust Approach ◽  
Photometric Redshift ◽  
Data Release

We present a robust approach to estimating the redshift of galaxies using Pan-STARRS1 photometric data. Our approach is an application of the algorithm proposed for the SDSS Data Release 12. It uses a training set of 2 313 724 galaxies for which the spectroscopic redshift is obtained from SDSS, and magnitudes and colours are obtained from the Pan-STARRS1 Data Release 2 survey. The photometric redshift of a galaxy is then estimated by means of a local linear regression in a 5D magnitude and colour space. Our approach achieves an average bias of Δ̅z̅n̅o̅r̅m̅ = −1.92 × 10−4, a standard deviation of σ(Δznorm) = 0.0299, and an outlier rate of Po = 4.30% when cross-validating the training set. Even though the relation between each of the Pan-STARRS1 colours and the spectroscopic redshifts is noisier than for SDSS colours, the results obtained by our approach are very close to those yielded by SDSS data. The proposed approach has the additional advantage of allowing the estimation of photometric redshifts on a larger portion of the sky (∼3/4 vs ∼1/3). The training set and the code implementing this approach are publicly available at the project website.

scholarly journals Compact galaxies and the size–mass galaxy distribution from a colour-selected sample at 0.04 < z < 0.15 supplemented by ugrizYJHK photometric redshifts

2020 ◽  
Vol 500 (2) ◽  
pp. 1557-1574
Author(s):  
Ivan K Baldry ◽  
Tricia Sullivan ◽  
Raffaele Rani ◽  
Sebastian Turner
Keyword(s):  
Galaxy Evolution ◽  
High Redshift ◽  
Sample Selection ◽  
Distribution Functions ◽  
Sloan Digital Sky Survey ◽  
Photometric Redshifts ◽  
Galaxy Distribution ◽  
Sky Survey ◽  
Galaxy Sample ◽  
Compact Galaxies

ABSTRACT The size–mass galaxy distribution is a key diagnostic for galaxy evolution. Massive compact galaxies are potential surviving relics of a high-redshift phase of star formation. Some of these could be nearly unresolved in Sloan Digital Sky Survey (SDSS) imaging and thus not included in galaxy samples. To overcome this, a sample was selected from the combination of SDSS and UKIRT Infrared Deep Sky Survey (UKIDSS) photometry to r &lt; 17.8. This was done using colour–colour selection, and then by obtaining accurate photometric redshifts (photo-z) using scaled flux matching (SFM). Compared to spectroscopic redshifts (spec-z), SFM obtained a 1σ scatter of 0.0125 with only 0.3 per cent outliers (|Δln (1 + z)| &gt; 0.06). A sample of 163 186 galaxies was obtained with 0.04 &lt; z &lt; 0.15 over $2300\, {\rm deg}^2$ using a combination of spec-z and photo-z. Following Barro et al. log Σ1.5 = log M* − 1.5log r50, maj was used to define compactness. The spectroscopic completeness was 76 per cent for compact galaxies (log Σ1.5 &gt; 10.5) compared to 92 per cent for normal-sized galaxies. This difference is primarily attributed to SDSS ‘fibre collisions’ and not the completeness of the main galaxy sample selection. Using environmental overdensities, this confirms that compact quiescent galaxies are significantly more likely to be found in high-density environments compared to normal-sized galaxies. By comparison with a high-redshift sample from 3D-HST, log Σ1.5 distribution functions show significant evolution, with this being a compelling way to compare with simulations such as EAGLE. The number density of compact quiescent galaxies drops by a factor of about 30 from z ∼ 2 to log (n/Mpc−3) = − 5.3 ± 0.4 in the SDSS–UKIDSS sample. The uncertainty is dominated by the steep cut off in log Σ1.5, which is demonstrated conclusively using this complete sample.

scholarly journals Photometric redshifts for X-ray-selected active galactic nuclei in the eROSITA era

2019 ◽  
Vol 489 (1) ◽  
pp. 663-680 ◽  
Author(s):  
M Brescia ◽  
M Salvato ◽  
S Cavuoti ◽  
T T Ananna ◽  
G Riccio ◽  
...  
Keyword(s):  
Active Galactic Nuclei ◽  
Large Fraction ◽  
Spectral Energy Distribution ◽  
Galactic Nuclei ◽  
Training Sample ◽  
Spectral Energy ◽  
Ancillary Data ◽  
Photometric Redshifts ◽  
X Ray

ABSTRACT With the launch of eROSITA (extended Roentgen Survey with an Imaging Telescope Array), successfully occurred on 2019 July 13, we are facing the challenge of computing reliable photometric redshifts for 3 million of active galactic nuclei (AGNs) over the entire sky, having available only patchy and inhomogeneous ancillary data. While we have a good understanding of the photo-z quality obtainable for AGN using spectral energy distribution (SED)-fitting technique, we tested the capability of machine learning (ML), usually reliable in computing photo-z for QSO in wide and shallow areas with rich spectroscopic samples. Using MLPQNA as example of ML, we computed photo-z for the X-ray-selected sources in Stripe 82X, using the publicly available photometric and spectroscopic catalogues. Stripe 82X is at least as deep as eROSITA will be and wide enough to include also rare and bright AGNs. In addition, the availability of ancillary data mimics what can be available in the whole sky. We found that when optical, and near- and mid-infrared data are available, ML and SED fitting perform comparably well in terms of overall accuracy, realistic redshift probability density functions, and fraction of outliers, although they are not the same for the two methods. The results could further improve if the photometry available is accurate and including morphological information. Assuming that we can gather sufficient spectroscopy to build a representative training sample, with the current photometry coverage we can obtain reliable photo-z for a large fraction of sources in the Southern hemisphere well before the spectroscopic follow-up, thus timely enabling the eROSITA science return. The photo-z catalogue is released here.

scholarly journals Integrated photometric redshifts and SED fitting as tool for galaxy evolution studies

2012 ◽  
Vol 8 (S289) ◽  
pp. 292-295
Author(s):  
Ralf Kotulla
Keyword(s):  
Energy Distribution ◽  
Galaxy Evolution ◽  
High Redshift ◽  
Spectral Energy Distribution ◽  
Spectral Energy ◽  
Photometric Redshifts ◽  
First Results ◽  
The Common ◽  
High Redshift Universe ◽  
Fixed Input

AbstractPhotometric redshifts, i.e. redshifts derived by comparing an observed spectral-energy distribution (SED) to a range of empirical or theoretical SED templates, are commonly used in studies of the high-redshift Universe. Often, the next step is to use these redshifts as fixed input parameters for SED fitting to derive physical properties for each galaxy. However, this two-step approach ignores degeneracies between redshift and, e.g., stellar mass. Here I present first results using an improved approach that integrates both methods. I find that mass determinations are, on average, three times more uncertain than they seem from the common two-step approach. If not accounted for, these underestimated uncertainties can impact our ability of making meaningful comparisons between observations and simulations of galaxy evolution.

scholarly journals The Impact of Stochastic Attenuation on Photometric Redshift Estimates

2006 ◽  
Vol 2 (S235) ◽  
pp. 438-439
Author(s):  
Thorsten Tepper García ◽  
Uta Fritze-von Alvensleben
Keyword(s):  
Star Formation ◽  
Star Formation Rate ◽  
Formation Rate ◽  
Spectral Energy ◽  
Energy Distributions ◽  
Photometric Redshifts ◽  
Lyman Alpha ◽  
Photometric Redshift ◽  
The Impact ◽  
Johnson System

AbstractWe model the stochastic attenuation by HI absorbers in the intergalactic medium (IGM), such as Lyα Forest clouds, and absorbers associated with galaxies, such as Lyman Limit systems (LLS) and Damped Lyman Alpha absorbers (DLAs), and compute an ensemble of 4 · 103 attenuated Spectral Energy Distributions (SEDs) in the Johnson system for the spectrum of a galaxy with a constant star formation rate (CSFR). Using these, we asses the impact of the stochastic attenuation on the estimates of photometric redshifts for this type of galaxy by comparison with model SEDs that include only a mean attenuation.

scholarly journals Photometric redshifts from SDSS images using a convolutional neural network

2018 ◽  
Vol 621 ◽  
pp. A26 ◽  
Author(s):  
Johanna Pasquet ◽  
E. Bertin ◽  
M. Treyer ◽  
S. Arnouts ◽  
D. Fouchez
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Signal To Noise Ratio ◽  
Distribution Functions ◽  
Sloan Digital Sky Survey ◽  
Photometric Redshifts ◽  
Photometric Redshift ◽  
Probability Distribution Functions ◽  
Sky Survey ◽  
Galaxy Sample

We developed a deep convolutional neural network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies in the Main Galaxy Sample of the Sloan Digital Sky Survey at z <  0.4. Our method exploits all the information present in the images without any feature extraction. The input data consist of 64 × 64 pixel ugriz images centered on the spectroscopic targets, plus the galactic reddening value on the line-of-sight. For training sets of 100k objects or more (≥20% of the database), we reach a dispersion σMAD <  0.01, significantly lower than the current best one obtained from another machine learning technique on the same sample. The bias is lower than 10−4, independent of photometric redshift. The PDFs are shown to have very good predictive power. We also find that the CNN redshifts are unbiased with respect to galaxy inclination, and that σMAD decreases with the signal-to-noise ratio (S/N), achieving values below 0.007 for S/N >  100, as in the deep stacked region of Stripe 82. We argue that for most galaxies the precision is limited by the S/N of SDSS images rather than by the method. The success of this experiment at low redshift opens promising perspectives for upcoming surveys.

scholarly journals CPz: Classification-aided photometric-redshift estimation

2018 ◽  
Vol 619 ◽  
pp. A14 ◽  
Author(s):  
S. Fotopoulou ◽  
S. Paltani
Keyword(s):  
Galaxy Evolution ◽  
Near Infrared ◽  
Spectral Energy Distribution ◽  
Ultra Violet ◽  
Cost Effective ◽  
Continuum Emission ◽  
Spectral Energy ◽  
Distribution Fitting ◽  
Optical Photometry ◽  
Photometric Redshift

Broadband photometry offers a time and cost effective method to reconstruct the continuum emission of celestial objects. Thus, photometric redshift estimation has supported the scientific exploitation of extragalactic multiwavelength surveys for more than twenty years. Deep fields have been the backbone of galaxy evolution studies and have brought forward a collection of various approaches in determining photometric redshifts. In the era of precision cosmology, with the upcoming Euclid and LSST surveys, very tight constraints are put on the expected performance of photometric redshift estimation using broadband photometry, thus new methods have to be developed in order to reach the required performance. We present a novel automatic method of optimizing photometric redshift performance, the classification-aided photometric redshift estimation (CPz). The main feature of CPz is the unified treatment of all classes of objects detected in extragalactic surveys: galaxies of any type (passive, starforming and starbursts), active galactic nuclei (AGN), quasi-stellar objects (QSO), stars and also includes the identification of potential photometric redshift catastrophic outliers. The method operates in three stages. First, the photometric catalog is confronted with star, galaxy and QSO model templates by means of spectral energy distribution fitting. Second, three machine-learning classifiers are used to identify 1) the probability of each source to be a star, 2) the optimal photometric redshift model library set-up for each source and 3) the probability to be a photometric redshift catastrophic outlier. Lastly, the final sample is assembled by identifying the probability thresholds to be applied on the outcome of each of the three classifiers. Hence, with the final stage we can create a sample appropriate for a given science case, for example favoring purity over completeness. We apply our method to the near-infrared VISTA public surveys, matched with optical photometry from CFHTLS, KIDS and SDSS, mid-infrared WISE photometry and ultra-violet photometry from the Galaxy Evolution Explorer (GALEX). We show that CPz offers improved photometric redshift performance for both normal galaxies and AGN without the need for extra X-ray information.

scholarly journals SCUBA-2 observations of candidate starbursting protoclusters selected by Planck and Herschel-SPIRE

2019 ◽  
Vol 490 (3) ◽  
pp. 3840-3859 ◽  
Author(s):  
T Cheng ◽  
D L Clements ◽  
J Greenslade ◽  
J Cairns ◽  
P Andreani ◽  
...  
Keyword(s):  
Star Formation ◽  
High Redshift ◽  
Spectral Energy Distribution ◽  
Formation Rate ◽  
Spectral Energy ◽  
Cumulative Number ◽  
Redshift Distribution ◽  
Photometric Redshifts ◽  
Star Forming ◽  
Photometric Redshift

ABSTRACT We present SCUBA-2 850 $\mathrm{ \mu}$m observations of 13 candidate starbursting protoclusters selected using Planck and Herschel data. The cumulative number counts of the 850 $\mathrm{ \mu}$m sources in 9 of 13 of these candidate protoclusters show significant overdensities compared to the field, with the probability &lt;10−2 assuming the sources are randomly distributed in the sky. Using the 250, 350, 500, and 850 $\mathrm{ \mu}$m flux densities, we estimate the photometric redshifts of individual SCUBA-2 sources by fitting spectral energy distribution templates with an MCMC method. The photometric redshift distribution, peaking at 2 &lt; z &lt; 3, is consistent with that of known z &gt; 2 protoclusters and the peak of the cosmic star formation rate density (SFRD). We find that the 850 $\mathrm{ \mu}$m sources in our candidate protoclusters have infrared luminosities of $L_{\mathrm{IR}}\gtrsim 10^{12}\, \mathrm{L}_{\odot }$ and star formation rates of SFR  = (500–1500) M⊙ yr−1. By comparing with results in the literature considering only Herschel photometry, we conclude that our 13 candidate protoclusters can be categorized into four groups: six of them being high-redshift starbursting protoclusters, one being a lower redshift cluster or protocluster, three being protoclusters that contain lensed dusty star-forming galaxies or are rich in 850 $\mathrm{ \mu}$m sources, and three regions without significant Herschel or SCUBA-2 source overdensities. The total SFRs of the candidate protoclusters are found to be comparable or higher than those of known protoclusters, suggesting our sample contains some of the most extreme protocluster population. We infer that cross-matching Planck and Herschel data is a robust method for selecting candidate protoclusters with overdensities of 850 $\mathrm{ \mu}$m sources.

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