Photometric redshifts for the Kilo-Degree Survey

We present a machine-learning photometric redshift (ML photo-z) analysis of the Kilo-Degree Survey Data Release 3 (KiDS DR3), using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes provide photo-zs of quality comparable to, if not better than, those from the Bayesian Photometric Redshift (BPZ) code, at least up to zphot ≲ 0.9 and r ≲ 23.5. At the bright end of r ≲ 20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared (IR) bands are added. While the fiducial four-band ugri setup gives a photo-z bias 〈δz/(1 + z)〉 = −2 × 10−4 and scatter σδz/(1+z) < 0.022 at mean 〈z〉 = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by ~7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 μm, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives 〈δz/(1 + z)〉 < 4 × 10−5 and σδz/(1+z) < 0.019. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimised for low-redshift studies such as galaxy-galaxy lensing, is limited to r ≲ 20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation.

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The XXL Survey

Astronomy and Astrophysics ◽

10.1051/0004-6361/201832989 ◽

2018 ◽

Vol 620 ◽

pp. A13 ◽

Cited By ~ 10

Author(s):

M. Ricci ◽

C. Benoist ◽

S. Maurogordato ◽

C. Adami ◽

L. Chiappetti ◽

...

Keyword(s):

Near Infrared ◽

Mass Range ◽

Selection Function ◽

Photometric Redshifts ◽

Statistical Tool ◽

Cluster Galaxy ◽

Photometric Redshift ◽

Luminosity Functions ◽

The Galaxy ◽

The Individual

Context. The luminosity function (LF) is a powerful statistical tool used to describe galaxies and learn about their evolution. In particular, the LFs of galaxies inside clusters allow us to better understand how galaxies evolve in these dense environments. Knowledge of the LFs of galaxies in clusters is also crucial for clusters studies in the optical and near-infrared (NIR) as they encode, along with their density profiles, most of their observational properties. However, no consensus has been reached yet about the evolution of the cluster galaxy LF with halo mass and redshift. Aims. The main goal of this study is to investigate the LF of a sample of 142 X-ray selected clusters, with spectroscopic redshift confirmation and a well defined selection function, spanning a wide redshift and mass range, and to test the LF dependence on cluster global properties, in a homogeneous and unbiased way. Methods. Our study is based on the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) photometric galaxy catalogue, associated with photometric redshifts. We constructed LFs inside a scaled radius using a selection in photometric redshift around the cluster spectroscopic redshift in order to reduce projection effects. The width of the photometric redshift selection was carefully determined to avoid biasing the LF and depended on both the cluster redshift and the galaxy magnitudes. The purity was then enhanced by applying a precise background subtraction. We constructed composite luminosity functions (CLFs) by stacking the individual LFs and studied their evolution with redshift and richness, analysing separately the brightest cluster galaxy (BCG) and non-BCG members. We fitted the dependences of the CLFs and BCG distributions parameters with redshift and richness conjointly in order to distinguish between these two effects. Results. We find that the usual photometric redshift selection methods can bias the LF estimate if the redshift and magnitude dependence of the photometric redshift quality is not taken into account. Our main findings concerning the evolution of the galaxy luminosity distribution with redshift and richness are that, in the inner region of clusters and in the redshift-mass range we probe (about 0 < z < 1 and 1013 M⊙ < M500 < 5 × 1014 M⊙), the bright part of the LF (BCG excluded) does not depend much on mass or redshift except for its amplitude, whereas the BCG luminosity increases both with redshift and richness.

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Efficient SIMDization and Data Management of the Lattice QCD Computation on the Cell Broadband Engine

Scientific Programming ◽

10.1155/2009/634756 ◽

2009 ◽

Vol 17 (1-2) ◽

pp. 153-172 ◽

Cited By ~ 2

Author(s):

Khaled Z. Ibrahim ◽

François Bodin

Keyword(s):

Lattice Qcd ◽

General Purpose ◽

Double Precision ◽

Limited Bandwidth ◽

Cell Broadband Engine ◽

Order Of Magnitude ◽

Simd Execution ◽

Local Store ◽

Time Continuum ◽

Better Than

Lattice Quantum Chromodynamic (QCD) models subatomic interactions based on a four-dimensional discretized space–time continuum. The Lattice QCD computation is one of the grand challenges in physics especially when modeling a lattice with small spacing. In this work, we study the implementation of the main kernel routine of Lattice QCD that dominates the execution time on the Cell Broadband Engine. We tackle the problem of efficient SIMD execution and the problem of limited bandwidth for data transfers with the off-chip memory. For efficient SIMD execution, we present runtime data fusion technique that groups data processed similarly at runtime. We also introduce analysis needed to reduce the pressure on the scarce memory bandwidth that limits the performance of this computation. We studied two implementations for the main kernel routine that exhibit different patterns of accessing the memory and thus allowing different sets of optimizations. We show the attributes that make one implementation more favorable in terms of performance. For lattice size that is significantly larger than the local store, our implementation achieves 31.2 GFlops for single precision computations and 16.6 GFlops for double precision computations on the PowerXCell 8i, an order of magnitude better than the performance achieved on most general-purpose processors.

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PhotoWeb redshift: boosting photometric redshift accuracy with large spectroscopic surveys

Astronomy and Astrophysics ◽

10.1051/0004-6361/201937382 ◽

2020 ◽

Vol 636 ◽

pp. A90 ◽

Cited By ~ 1

Author(s):

M. Shuntov ◽

J. Pasquet ◽

S. Arnouts ◽

O. Ilbert ◽

M. Treyer ◽

...

Keyword(s):

Large Scale ◽

Distribution Functions ◽

Distance Measurements ◽

Photometric Redshifts ◽

Star Forming ◽

Photometric Redshift ◽

Probability Distribution Functions ◽

Galaxy Sample ◽

New Generation ◽

Better Than

Improving distance measurements in large imaging surveys is a major challenge to better reveal the distribution of galaxies on a large scale and to link galaxy properties with their environments. As recently shown, photometric redshifts can be efficiently combined with the cosmic web extracted from overlapping spectroscopic surveys to improve their accuracy. In this paper we apply a similar method using a new generation of photometric redshifts based on a convolution neural network (CNN). The CNN is trained on the SDSS images with the main galaxy sample (SDSS-MGS, r ≤ 17.8) and the GAMA spectroscopic redshifts up to r ∼ 19.8. The mapping of the cosmic web is obtained with 680 000 spectroscopic redshifts from the MGS and BOSS surveys. The redshift probability distribution functions (PDF), which are well calibrated (unbiased and narrow, ≤120 Mpc), intercept a few cosmic web structures along the line of sight. Combining these PDFs with the density field distribution provides new photometric redshifts, zweb, whose accuracy is improved by a factor of two (i.e., σ ∼ 0.004(1 + z)) for galaxies with r ≤ 17.8. For half of them, the distance accuracy is better than 10 cMpc. The narrower the original PDF, the larger the boost in accuracy. No gain is observed for original PDFs wider than 0.03. The final zweb PDFs also appear well calibrated. The method performs slightly better for passive galaxies than star-forming ones, and for galaxies in massive groups since these populations better trace the underlying large-scale structure. Reducing the spectroscopic sampling by a factor of 8 still improves the photometric redshift accuracy by 25%. Finally, extending the method to galaxies fainter than the MGS limit still improves the redshift estimates for 70% of the galaxies, with a gain in accuracy of 20% at low z where the resolution of the cosmic web is the highest. As two competing factors contribute to the performance of the method, the photometric redshift accuracy and the resolution of the cosmic web, the benefit of combining cosmological imaging surveys with spectroscopic surveys at higher redshift remains to be evaluated.

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The COSMOS2015 galaxy stellar mass function

Astronomy and Astrophysics ◽

10.1051/0004-6361/201730419 ◽

2017 ◽

Vol 605 ◽

pp. A70 ◽

Cited By ~ 125

Author(s):

I. Davidzon ◽

O. Ilbert ◽

C. Laigle ◽

J. Coupon ◽

H. J. McCracken ◽

...

Keyword(s):

Mass Density ◽

Mass Function ◽

Stellar Mass ◽

Photometric Redshifts ◽

Near Ir ◽

Low Mass ◽

Mass Assembly ◽

First Time ◽

Best Fit ◽

Ir Bands

We measure the stellar mass function (SMF) and stellar mass density of galaxies in the COSMOS field up to z ~ 6. We select them in the near-IR bands of the COSMOS2015 catalogue, which includes ultra-deep photometry from UltraVISTA-DR2, SPLASH, and Subaru/Hyper Suprime-Cam. At z> 2.5 we use new precise photometric redshifts with error σz = 0.03(1 + z) and an outlier fraction of 12%, estimated by means of the unique spectroscopic sample of COSMOS (~100 000 spectroscopic measurements in total, more than one thousand having robust zspec> 2.5). The increased exposure time in the DR2, along with our panchromatic detection strategy, allow us to improve the completeness at high z with respect to previous UltraVISTA catalogues (e.g. our sample is >75% complete at 1010 ℳ⊙ and z = 5). We also identify passive galaxies through a robust colour–colour selection, extending their SMF estimate up to z = 4. Our work provides a comprehensive view of galaxy-stellar-mass assembly between z = 0.1 and 6, for the first time using consistent estimates across the entire redshift range. We fit these measurements with a Schechter function, correcting for Eddington bias. We compare the SMF fit with the halo mass function predicted from ΛCDM simulations, finding that at z> 3 both functions decline with a similar slope in thehigh-mass end. This feature could be explained assuming that mechanisms quenching star formation in massive haloes become less effective at high redshifts; however further work needs to be done to confirm this scenario. Concerning the SMF low-mass end, it shows a progressive steepening as it moves towards higher redshifts, with α decreasing from -1.47+0.02-0.02 at z ≃ 0.1 to -2.11+0.30-0.13 at z ≃ 5. This slope depends on the characterisation of the observational uncertainties, which is crucial to properly remove the Eddington bias. We show that there is currently no consensus on the method to quantify such errors: different error models result in different best-fit Schechter parameters.

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Pre-processing of galaxies in cosmic filaments around AMASCFI clusters in the CFHTLS

Astronomy and Astrophysics ◽

10.1051/0004-6361/201935394 ◽

2019 ◽

Vol 632 ◽

pp. A49 ◽

Cited By ~ 15

Author(s):

F. Sarron ◽

C. Adami ◽

F. Durret ◽

C. Laigle

Keyword(s):

Galaxy Clusters ◽

Spectral Energy ◽

Photometric Redshifts ◽

Star Forming ◽

Galaxy Groups ◽

Photometric Redshift ◽

Preferred Direction ◽

The Galaxy ◽

Strategic Program ◽

Galaxy Populations

Context. Galaxy clusters and groups are thought to accrete material along the preferred direction of cosmic filaments. These structures have proven difficult to detect because their contrast is low, however, and only a few studies have focused on cluster infall regions. Aims. We detect cosmic filaments around galaxy clusters using photometric redshifts in the range 0.15 < z < 0.7. We characterise galaxy populations in these structures to study the influence of pre-processing by cosmic filaments and galaxy groups on star formation quenching. Methods. We detected cosmic filaments in the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) T0007 data, focusing on regions around clusters of the AMASCFI CFHTLS cluster sample. The filaments were reconstructed with the discrete persistent structure extractor (DISPERSE) algorithm in photometric redshift slices. We show that this reconstruction is reliable for a CFHTLS-like survey at 0.15 < z < 0.7 using a mock galaxy catalogue. We split our galaxy catalogue into two populations (passive and star forming) using the LePhare spectral energy density fitting algorithm and worked with two redshift bins (0.15 < z ≤ 0.4 and 0.4 < z < 0.7). Results. We showed that the AMASCFI cluster connectivity (i.e. the number of filaments that is connected to a cluster) increases with cluster mass M200. Filament galaxies outside R200 are found to be closer to clusters at low redshift, regardless of the galaxy type. Passive galaxies in filaments are closer to clusters than star-forming galaxies in the low redshift bin alone. The passive fraction of galaxies decreases with increasing clustercentric distance up to d ∼ 5 cMpc. Galaxy groups and clusters that are not located at nodes of our reconstruction are mainly found inside cosmic filaments. Conclusions. These results give clues for pre-processing in cosmic filaments that could be due to smaller galaxy groups. This trend could be further explored by applying this method to larger photometric surveys such as the Hyper Suprime-Cam Subaru Strategic Program (HSC-SPP) or Euclid.

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PKS 2250–351: A giant radio galaxy in Abell 3936

Publications of the Astronomical Society of Australia ◽

10.1017/pasa.2019.49 ◽

2020 ◽

Vol 37 ◽

Cited By ~ 2

Author(s):

N. Seymour ◽

M. Huynh ◽

S. S. Shabala ◽

J. Rogers ◽

L. J. M. Davies ◽

...

Keyword(s):

Radio Galaxy ◽

Elliptical Galaxy ◽

Host Galaxy ◽

The Galaxy ◽

Order Of Magnitude ◽

Mass Assembly ◽

Murchison Widefield Array ◽

Ir Emission ◽

Jet Power ◽

Compact Array

Abstract We present a detailed analysis of the radio galaxy PKS $2250{-}351$ , a giant of 1.2 Mpc projected size, its host galaxy, and its environment. We use radio data from the Murchison Widefield Array, the upgraded Giant Metre-wavelength Radio Telescope, the Australian Square Kilometre Array Pathfinder, and the Australia Telescope Compact Array to model the jet power and age. Optical and IR data come from the Galaxy And Mass Assembly (GAMA) survey and provide information on the host galaxy and environment. GAMA spectroscopy confirms that PKS $2250{-}351$ lies at $z=0.2115$ in the irregular, and likely unrelaxed, cluster Abell 3936. We find its host is a massive, ‘red and dead’ elliptical galaxy with negligible star formation but with a highly obscured active galactic nucleus dominating the mid-IR emission. Assuming it lies on the local M– $\sigma$ relation, it has an Eddington accretion rate of $\lambda_{\rm EDD}\sim 0.014$ . We find that the lobe-derived jet power (a time-averaged measure) is an order of magnitude greater than the hotspot-derived jet power (an instantaneous measure). We propose that over the lifetime of the observed radio emission ( ${\sim} 300\,$ Myr), the accretion has switched from an inefficient advection-dominated mode to a thin disc efficient mode, consistent with the decrease in jet power. We also suggest that the asymmetric radio morphology is due to its environment, with the host of PKS $2250{-}351$ lying to the west of the densest concentration of galaxies in Abell 3936.

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ALHAMBRA survey: morphological classification

Proceedings of the International Astronomical Union ◽

10.1017/s1743921314011508 ◽

2012 ◽

Vol 10 (H16) ◽

pp. 378-378

Author(s):

M. Pović ◽

M. Huertas-Company ◽

I. Márquez ◽

J. Masegosa ◽

J. A. López Aguerri ◽

...

Keyword(s):

Near Infrared ◽

High Redshift ◽

Morphological Properties ◽

Support Vector ◽

Late Type ◽

Morphological Classification ◽

Photometric Redshifts ◽

Photometric Redshift ◽

The Galaxy ◽

Medium Band

AbstractThe Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) survey is a photometric survey designed to study systematically cosmic evolution and cosmic variance (Moles et al.2008). It employs 20 continuous medium-band filters (3500 - 9700 Å), plus JHK near-infrared (NIR) bands, which enable measurements of photometric redshifts with good accuracy. ALHAMBRA covers > 4 deg2 in eight discontinuous regions (~ 0.5 deg2 per region), of theseseven fields overlap with other extragalactic, multiwavelength surveys (DEEP2, SDSS, COSMOS, HDF-N, Groth, ELAIS-N1). We detect > 600.000 sources, reaching the depth of R(AB) ~ 25.0, and photometric accuracy of 2-4% (Husillos et al., in prep.). Photometric redshifts are measured using the Bayesian Photometric Redshift (BPZ) code (Benítez et al.2000), reaching one of the best accuracies up to date of δz/z ≤ 1.2% (Molino et al., in prep.).To deal with the morphological classification of galaxies in the ALHAMBRA survey (Pović et al., in prep.), we used the galaxy Support Vector Machine code (galSVM; Huertas-Company 2008, 2009), one of the new non-parametric methods for morphological classification, specially useful when dealing with low resolution and high-redshift data. To test the accuracy of our morphological classification we used a sample of 3000 local, visually classified galaxies (Nair & Abraham 2010), moving them to conditions typical of our ALHAMBRA data (taking into account the background, redshift and magnitude distributions, etc.), and measuring their morphology using galSVM. Finally, we measured the morphology of ALHAMBRA galaxies, obtaining for each source seven morphological parameters (two concentration indexes, asymmetry, Gini, M20 moment of light, smoothness, and elongation), probability if the source belongs to early- or late-type, and its error. Comparing ALHAMBRA morph COSMOS/ACS morphology (obtained with the same method) we expect to have qualitative separation in two main morphological types for ~ 20.000 sources in 8 ALHAMBRA fields. For early-type galaxies we expect to recover ~ 70% and 30-40% up to magnitudes 20.0 and 21.5, respectively, having the contamination of late-types of < 7%. For late-type galaxies, we expect to recover ~ 70%, 60 - 70%, and ~ 30% of sources up to magnitudes 22.0, 22.5, and 23.0, respectively, having the contamination of early-types of ≤ 10%. These data will be used to study the evolution of active and non-active galaxies respect to morphology and morphological properties of galaxies in groups and clusters.

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Impact of photometric redshifts on the galaxy power spectrum and BAO scale in the LSST survey

Astronomy and Astrophysics ◽

10.1051/0004-6361/201833732 ◽

2019 ◽

Vol 623 ◽

pp. A76 ◽

Cited By ~ 1

Author(s):

Reza Ansari ◽

Adeline Choyer ◽

Farhang Habibi ◽

Christophe Magneville ◽

Marc Moniez ◽

...

Keyword(s):

Power Spectrum ◽

Large Scale ◽

Near Infrared ◽

Linear Part ◽

Cosmological Parameters ◽

Photometric Redshifts ◽

Photometric Redshift ◽

Near Ultraviolet ◽

The Galaxy ◽

The Impact

Context. The Large Synoptic Survey Telescope (LSST) survey will image billions of galaxies every few nights for ten years, and as such, should be a major contributor to precision cosmology in the 2020s. High precision photometric data will be available in six bands, from near-infrared to near-ultraviolet. The computation of precise, unbiased, photometric redshifts up to at least z = 2 is one of the main LSST challenges and its performance will have major impact on all extragalactic LSST sciences. Aims. We evaluate the efficiency of our photometric redshift reconstruction on mock galaxy catalogues up to z = 2.45 and estimate the impact of realistic photometric redshift (photo-z) reconstruction on the large-scale structures (LSS) power spectrum and the baryonic acoustic oscillation (BAO) scale determination for a LSST-like photometric survey. We study the effectiveness of the BAO scale as a cosmological probe in the LSST survey. Methods. We have performed a detailed modelling of the photo-z distribution as a function of galaxy type, redshift and absolute magnitude using our photo-z reconstruction code with a quality selection cut based on a boosted decision tree (BDT). We have simulated a catalogue of galaxies in the redshift range [0.2−2.45] using the Planck 2015 ΛCDM cosmological parameters over 10 000 square-degrees, in the six bands, assuming LSST photometric precision for a ten-year survey. The mock galaxy catalogues were produced with several redshift error models. The LSS power spectrum was then computed in several redshift ranges and for each error model. Finally we extracted the BAO scale and its uncertainty using only the linear part of the LSS spectrum. Results. We have computed the fractional error on the recovered power spectrum which is dominated by the shot noise at high redshift (z ≳ 1), for scales k ≳ 0.1, due to the photo-z damping. The BAO scale can be recovered with a percent or better accuracy level from z = 0.5 to z = 1.5 using realistic photo-z reconstruction. Conclusions. Reaching the LSST requirements for photo-z reconstruction is crucial to exploit the LSST potential in cosmology, in particular to measure the LSS power spectrum and its evolution with redshift. Although the BAO scale is not the most powerful cosmological probe in LSST, it can be used to check the consistency of the LSS measurement. Moreover we show that the impact of photo-z smearing on the recovered isotropic BAO scale in LSST should stay limited up to z ≈ 1.5, so as long as the galaxy number density balances the photo-z smoothing.

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The PAU Survey: Photometric redshifts using transfer learning from simulations

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa2265 ◽

2020 ◽

Vol 497 (4) ◽

pp. 4565-4579

Author(s):

M Eriksen ◽

A Alarcon ◽

L Cabayol ◽

J Carretero ◽

R Casas ◽

...

Keyword(s):

Transfer Learning ◽

Broad Band ◽

Training Data ◽

Machine Learning Techniques ◽

Test Case ◽

Photometric Redshifts ◽

Mixture Density ◽

Photometric Redshift ◽

The Galaxy ◽

The Impact

ABSTRACT In this paper, we introduce the deepz deep learning photometric redshift (photo-z) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. deepz reduces the σ68 scatter statistic by 50 per cent at iAB = 22.5 compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-z scatter by 10 per cent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.

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Galaxy evolution in different environments along redshift within the local universe z < 0.8

Journal of Physics Conference Series ◽

10.1088/1742-6596/2145/1/012002 ◽

2021 ◽

Vol 2145 (1) ◽

pp. 012002

Author(s):

Ponlawat Yoifoi ◽

Wichean Kriwattanawong

Keyword(s):

Star Formation ◽

Galaxy Evolution ◽

Spectroscopic Data ◽

Sloan Digital Sky Survey ◽

Number Density ◽

Local Universe ◽

Photometric Redshift ◽

Star Formation Activity ◽

Sky Survey ◽

The Galaxy

Abstract This study presents the evolution of the galaxies in different matter density along redshift within the local universe. A sample of 702,352 galaxies was collected from the Sloan Digital Sky Survey (SDSS). Under the limitation of the spectroscopic data, the appropriate photometric redshift was used to represent the spectroscopic redshift in the range of 0.0 ≤ z ≤ 0.8. Number density of galaxies, galaxy’s colors, and star formation activities are considered to describe the evolution of galaxies. In summary, the number density is not clearly different although the Dec and RA of the sky areas are disparate, but it steeply declines along the redshift direction. Considering the number density together with galaxies’ Hα emission line from spectroscopic data, we find that both equivalent of hydrogen alpha and Hα flux tend to decrease along the redshift, similar to the decreasing trend of the number density. Furthermore, the galaxy color trend is found to be redder as a function of the redshift for the magnitude range of -19 ≤ M g ≤ -17. It implies that the overview of the star formation activity of the fainter galaxies at the lower redshift tend to show higher than the ones at higher redshift.

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