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

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 impact of photometric redshift errors on lensing statistics in ray-tracing simulations

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stz1016 ◽

2019 ◽

Vol 486 (2) ◽

pp. 2730-2753 ◽

Cited By ~ 1

Author(s):

Matthew W Abruzzo ◽

Zoltán Haiman

Keyword(s):

Power Spectrum ◽

Ray Tracing ◽

Cold Dark Matter ◽

Cosmological Parameters ◽

Photometric Redshift ◽

Galaxy Distribution ◽

The Galaxy ◽

The Impact ◽

Parameter Constraints ◽

Lower Limits

Abstract Weak lensing surveys are reaching sensitivities at which uncertainties in the galaxy redshift distributions n(z) from photo-z errors degrade cosmological constraints. We use ray-tracing simulations and a simple treatment of photo-z errors to assess cosmological parameter biases from uncertainties in n(z) in an LSST-like survey. We use lensing peak counts and the power spectrum to infer cosmological parameters, and find that the latter is somewhat more resilient to photo-z errors. We place conservative lower limits on the survey size at which different types of photo-z errors significantly degrade (${\sim }50{{\ \rm per\ cent}}$) ΛCDM (cold dark matter, wCDM) parameter constraints. A residual constant photo-z bias of |δz| < 0.003(1 + z), the current LSST requirement, does not significantly degrade surveys smaller than ≈1300 (≈490) deg2 using peaks and ≈6500 (≈4900) deg2 using the power spectrum. Surveys smaller than ≈920 (≈450) deg2 and ≈4600 (≈4000) deg2 avoid 25 per cent degradation. Adopting a recent prediction for LSST’s full photo-z probability distribution function (PDF), we find that simply approximating n(z) with the photo-z galaxy distribution computed from this PDF significantly degrades surveys as small as ≈60 (≈65) deg2 using peaks or the power spectrum. If the centroid bias in each tomographic bin is removed from the photo-z galaxy distribution, using peaks or the power spectrum still significantly degrades surveys larger than ≈200 (≈255) or ≈248 (≈315) deg2; 25 per cent degradations occur at survey sizes of ≈140 (≈180) deg2 or ≈165 (≈210) deg2. These results imply that the expected broad photo-z PDF significantly biases parameters, which must be further mitigated using more sophisticated photo-z treatments.

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Impact of relativistic effects on the primordial non-Gaussianity signature in the large-scale clustering of quasars

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa2998 ◽

2020 ◽

Vol 499 (2) ◽

pp. 2598-2607

Author(s):

Mike (Shengbo) Wang ◽

Florian Beutler ◽

David Bacon

Keyword(s):

Dark Energy ◽

Power Spectrum ◽

Luminosity Function ◽

Large Scale ◽

Relativistic Effects ◽

Redshift Range ◽

Cosmological Background ◽

Relativistic Corrections ◽

The Galaxy ◽

The Impact

ABSTRACT Relativistic effects in clustering observations have been shown to introduce scale-dependent corrections to the galaxy overdensity field on large scales, which may hamper the detection of primordial non-Gaussianity fNL through the scale-dependent halo bias. The amplitude of relativistic corrections depends not only on the cosmological background expansion, but also on the redshift evolution and sensitivity to the luminosity threshold of the tracer population being examined, as parametrized by the evolution bias be and magnification bias s. In this work, we propagate luminosity function measurements from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) to be and s for the quasar (QSO) sample, and thereby derive constraints on relativistic corrections to its power spectrum multipoles. Although one could mitigate the impact on the fNL signature by adjusting the redshift range or the luminosity threshold of the tracer sample being considered, we suggest that, for future surveys probing large cosmic volumes, relativistic corrections should be forward modelled from the tracer luminosity function including its uncertainties. This will be important to quasar clustering measurements on scales $k \sim 10^{-3}\, h\, {\rm Mpc}^{-1}$ in upcoming surveys such as the Dark Energy Spectroscopic Instrument (DESI), where relativistic corrections can overwhelm the expected fNL signature at low redshifts z ≲ 1 and become comparable to fNL ≃ 1 in the power spectrum quadrupole at redshifts z ≳ 2.5.

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Photometric Redshifts with the LSST. II. The Impact of Near-infrared and Near-ultraviolet Photometry

The Astronomical Journal ◽

10.3847/1538-3881/ab8a43 ◽

2020 ◽

Vol 159 (6) ◽

pp. 258

Author(s):

Melissa L. Graham ◽

Andrew J. Connolly ◽

Winnie Wang ◽

Samuel J. Schmidt ◽

Christopher B. Morrison ◽

...

Keyword(s):

Near Infrared ◽

Photometric Redshifts ◽

Near Ultraviolet ◽

The Impact

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Simulating JWST deep extragalactic imaging surveys and physical parameter recovery

Astronomy and Astrophysics ◽

10.1051/0004-6361/202037450 ◽

2020 ◽

Vol 640 ◽

pp. A67

Author(s):

O. B. Kauffmann ◽

O. Le Fèvre ◽

O. Ilbert ◽

J. Chevallard ◽

C. C. Williams ◽

...

Keyword(s):

Star Formation ◽

Near Infrared ◽

High Redshift ◽

Spectral Energy Distribution ◽

Formation Rate ◽

Spectral Energy ◽

Photometric Redshifts ◽

The Galaxy ◽

Stellar Masses ◽

The Impact

We present a new prospective analysis of deep multi-band imaging with the James Webb Space Telescope (JWST). In this work, we investigate the recovery of high-redshift 5 < z < 12 galaxies through extensive image simulations of accepted JWST programs, including the Early Release Science in the EGS field and the Guaranteed Time Observations in the HUDF. We introduced complete samples of ∼300 000 galaxies with stellar masses of log(M*/M⊙) > 6 and redshifts of 0 < z < 15, as well as galactic stars, into realistic mock NIRCam, MIRI, and HST images to properly describe the impact of source blending. We extracted the photometry of the detected sources, as in real images, and estimated the physical properties of galaxies through spectral energy distribution fitting. We find that the photometric redshifts are primarily limited by the availability of blue-band and near-infrared medium-band imaging. The stellar masses and star formation rates are recovered within 0.25 and 0.3 dex, respectively, for galaxies with accurate photometric redshifts. Brown dwarfs contaminating the z > 5 galaxy samples can be reduced to < 0.01 arcmin−2 with a limited impact on galaxy completeness. We investigate multiple high-redshift galaxy selection techniques and find that the best compromise between completeness and purity at 5 < z < 10 using the full redshift posterior probability distributions. In the EGS field, the galaxy completeness remains higher than 50% at magnitudes mUV < 27.5 and at all redshifts, and the purity is maintained above 80 and 60% at z ≤ 7 and 10, respectively. The faint-end slope of the galaxy UV luminosity function is recovered with a precision of 0.1–0.25, and the cosmic star formation rate density within 0.1 dex. We argue in favor of additional observing programs covering larger areas to better constrain the bright end.

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Mixed dark matter: matter power spectrum and halo mass function

Journal of Cosmology and Astroparticle Physics ◽

10.1088/1475-7516/2021/12/044 ◽

2021 ◽

Vol 2021 (12) ◽

pp. 044

Author(s):

G. Parimbelli ◽

G. Scelfo ◽

S.K. Giri ◽

A. Schneider ◽

M. Archidiacono ◽

...

Keyword(s):

Dark Matter ◽

Power Spectrum ◽

Large Scale ◽

Cosmological Parameters ◽

Mass Function ◽

Large Set ◽

Cluster Number ◽

Matter Power Spectrum ◽

Wide Range ◽

The Impact

Abstract We investigate and quantify the impact of mixed (cold and warm) dark matter models on large-scale structure observables. In this scenario, dark matter comes in two phases, a cold one (CDM) and a warm one (WDM): the presence of the latter causes a suppression in the matter power spectrum which is allowed by current constraints and may be detected in present-day and upcoming surveys. We run a large set of N-body simulations in order to build an efficient and accurate emulator to predict the aforementioned suppression with percent precision over a wide range of values for the WDM mass, Mwdm, and its fraction with respect to the totality of dark matter, fwdm. The suppression in the matter power spectrum is found to be independent of changes in the cosmological parameters at the 2% level for k≲ 10 h/Mpc and z≤ 3.5. In the same ranges, by applying a baryonification procedure on both ΛCDM and CWDM simulations to account for the effect of feedback, we find a similar level of agreement between the two scenarios. We examine the impact that such suppression has on weak lensing and angular galaxy clustering power spectra. Finally, we discuss the impact of mixed dark matter on the shape of the halo mass function and which analytical prescription yields the best agreement with simulations. We provide the reader with an application to galaxy cluster number counts.

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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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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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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–Galaxy lensing in HSC: Validation tests and the impact of heterogeneous spectroscopic training sets

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stz2968 ◽

2019 ◽

Vol 490 (4) ◽

pp. 5658-5677 ◽

Cited By ~ 6

Author(s):

Joshua S Speagle ◽

Alexie Leauthaud ◽

Song Huang ◽

Christopher P Bradshaw ◽

Felipe Ardila ◽

...

Keyword(s):

Large Scale ◽

Training Sample ◽

Weak Lensing ◽

Redshift Distribution ◽

High Quality ◽

Photometric Redshifts ◽

The Galaxy ◽

Validation Tests ◽

The Impact ◽

Training Sets

ABSTRACT Although photometric redshifts (photo-z’s) are crucial ingredients for current and upcoming large-scale surveys, the high-quality spectroscopic redshifts currently available to train, validate, and test them are substantially non-representative in both magnitude and colour. We investigate the nature and structure of this bias by tracking how objects from a heterogeneous training sample contribute to photo-z predictions as a function of magnitude and colour, and illustrate that the underlying redshift distribution at fixed colour can evolve strongly as a function of magnitude. We then test the robustness of the galaxy–galaxy lensing signal in 120 deg2 of HSC–SSP DR1 data to spectroscopic completeness and photo-z biases, and find that their impacts are sub-dominant to current statistical uncertainties. Our methodology provides a framework to investigate how spectroscopic incompleteness can impact photo-z-based weak lensing predictions in future surveys such as LSST and WFIRST.

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