Category: Galaxies Publications

Publications related to galaxies

Deep Learning for space-variant deconvolution in galaxy surveys

Deep Learning for space-variant deconvolution in galaxy surveys

Posted on by Jean-Luc Starck

 

Authors: Florent Sureau, Alexis Lechat, J-L. Starck
Journal: Astronomy and Astrophysics
Year: 2020
DOI: 10.1051/0004-6361/201937039
Download: ADS | arXiv

Abstract

The deconvolution of large survey images with millions of galaxies requires developing a new generation of methods that can take a space-variant point spread function into account. These methods have also to be accurate and fast. We investigate how deep learning might be used to perform this task. We employed a U-net deep neural network architecture to learn parameters that were adapted for galaxy image processing in a supervised setting and studied two deconvolution strategies. The first approach is a post-processing of a mere Tikhonov deconvolution with closed-form solution, and the second approach is an iterative deconvolution framework based on the alternating direction method of multipliers (ADMM). Our numerical results based on GREAT3 simulations with realistic galaxy images and point spread functions show that our two approaches outperform standard techniques that are based on convex optimization, whether assessed in galaxy image reconstruction or shape recovery. The approach based on a Tikhonov deconvolution leads to the most accurate results, except for ellipticity errors at high signal-to-noise ratio. The ADMM approach performs slightly better in this case. Considering that the Tikhonov approach is also more computation-time efficient in processing a large number of galaxies, we recommend this approach in this scenario.

In the spirit of reproducible research, the codes will be made freely available on the CosmoStat website (http://www.cosmostat.org). The testing datasets will also be provided to repeat the experiments performed in this paper.

Cosmic CARNage I: on the calibration of galaxy formation models

Cosmic CARNage I: on the calibration of galaxy formation models

Posted on by Samuel Farrens

 

Authors: A. Knebe, F. R. Pearce, V. Gonzalez-Perez et al.
Journal:  
Year: 12/2017
Download: ADS| Arxiv

Abstract

We present a comparison of nine galaxy formation models, eight semi-analytical and one halo occupation distribution model, run on the same underlying cold dark matter simulation (cosmological box of co-moving width 125h−1 Mpc, with a dark-matter particle mass of 1.24×109h−1 Msun) and the same merger trees. While their free parameters have been calibrated to the same observational data sets using two approaches, they nevertheless retain some 'memory' of any previous calibration that served as the starting point (especially for the manually-tuned models). For the first calibration, models reproduce the observed z = 0 galaxy stellar mass function (SMF) within 3-{\sigma}. The second calibration extended the observational data to include the z = 2 SMF alongside the z~0 star formation rate function, cold gas mass and the black hole-bulge mass relation. Encapsulating the observed evolution of the SMF from z = 2 to z = 0 is found to be very hard within the context of the physics currently included in the models. We finally use our calibrated models to study the evolution of the stellar-to-halo mass (SHM) ratio. For all models we find that the peak value of the SHM relation decreases with redshift. However, the trends seen for the evolution of the peak position as well as the mean scatter in the SHM relation are rather weak and strongly model dependent. Both the calibration data sets and model results are publicly available.

nIFTy Cosmology: the clustering consistency of galaxy formation models

nIFTy Cosmology: the clustering consistency of galaxy formation models

Posted on by Samuel Farrens

 

Authors: A. Pujol, R. A. Skibba, E. Gaztañaga et al.
Journal: MNRAS
Year: 02/2017
Download: ADS| Arxiv

Abstract

We present a clustering comparison of 12 galaxy formation models (including Semi-Analytic Models (SAMs) and Halo Occupation Distribution (HOD) models) all run on halo catalogues and merger trees extracted from a single {\Lambda}CDM N-body simulation. We compare the results of the measurements of the mean halo occupation numbers, the radial distribution of galaxies in haloes and the 2-Point Correlation Functions (2PCF). We also study the implications of the different treatments of orphan (galaxies not assigned to any dark matter subhalo) and non-orphan galaxies in these measurements. Our main result is that the galaxy formation models generally agree in their clustering predictions but they disagree significantly between HOD and SAMs for the orphan satellites. Although there is a very good agreement between the models on the 2PCF of central galaxies, the scatter between the models when orphan satellites are included can be larger than a factor of 2 for scales smaller than 1 Mpc/h. We also show that galaxy formation models that do not include orphan satellite galaxies have a significantly lower 2PCF on small scales, consistent with previous studies. Finally, we show that the 2PCF of orphan satellites is remarkably different between SAMs and HOD models. Orphan satellites in SAMs present a higher clustering than in HOD models because they tend to occupy more massive haloes. We conclude that orphan satellites have an important role on galaxy clustering and they are the main cause of the differences in the clustering between HOD models and SAMs.

What determines large scale galaxy clustering: halo mass or local density?

What determines large scale galaxy clustering: halo mass or local density?

Posted on by Samuel Farrens

 

Authors: A. Pujol, K. Hoffmann, N. Jiménez et al.
Journal: A&A
Year: 02/2017
Download: ADS| Arxiv

Abstract

Using a dark matter simulation we show how halo bias is determined by local density and not by halo mass. This is not totally surprising as, according to the peak-background split model, local matter density (bar δ) is the property that constrains bias at large scales. Massive haloes have a high clustering because they reside in high density regions. Small haloes can be found in a wide range of environments which differentially determine their clustering amplitudes. This contradicts the assumption made by standard halo occupation distribution (HOD) models that bias and occupation of haloes is determined solely by their mass. We show that the bias of central galaxies from semi-analytic models of galaxy formation as a function of luminosity and colour is therefore not correctly predicted by the standard HOD model. Using bar δ (of matter or galaxies) instead of halo mass, the HOD model correctly predicts galaxy bias. These results indicate the need to include information about local density and not only mass in order to correctly apply HOD analysis in these galaxy samples. This new model can be readily applied to observations and has the advantage that, in contrast with the dark matter halo mass, the galaxy density can be directly observed.

A new method to measure galaxy bias by combining the density and weak lensing fields

A new method to measure galaxy bias by combining the density and weak lensing fields

Posted on by Samuel Farrens

 

Authors: A. Pujol, C. Chang, E. Gaztañaga et al.
Journal: MNRAS
Year: 10/2016
Download: ADS| Arxiv

Abstract

We present a new method to measure redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on the work of Amara et al., who use the galaxy density field to construct a bias-weighted convergence field κg. The main difference between Amara et al.'s work and our new implementation is that here we present another way to measure galaxy bias, using tomography instead of bias parametrizations. The correlation between κg and the true lensing field κ allows us to measure galaxy bias using different zero-lag correlations, such as <κgκ>/<κκ> or <κgκg>/<κgκ>. Our method measures the linear bias factor on linear scales, under the assumption of no stochasticity between galaxies and matter. We use the Marenostrum Institut de Ciències de l'Espai (MICE) simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This article is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method and the regime in which it is consistent with the linear galaxy bias defined by projected two-point correlation functions (2PCF). We find that our method is consistent with a linear bias at the per cent level for scales larger than 30 arcmin, while non-linearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on σ8 as do the 2PCF measurements. We will apply this method to the Dark Energy Survey Science Verification data in a follow-up article.

Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

Posted on by Samuel Farrens

 

Authors: C. Chang, A. Pujol, E. Gaztañaga et al.
Journal: MNRAS
Year: 07/2016
Download: ADS| Arxiv

Abstract

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ˜116 deg2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1σ error bars in four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2-0.4), 0.97 ± 0.15 (z = 0.4-0.6), 1.38 ± 0.39 (z = 0.6-0.8), and 1.45 ± 0.56 (z = 0.8-1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

Clustering-based redshift estimation: application to VIPERS/CFHTLS

Clustering-based redshift estimation: application to VIPERS/CFHTLS

Posted on by Martin Kilbinger
Authors: V. Scottez, Y. Mellier, B. Granett, T. Moutard, M. Kilbinger et al.
Journal: MNRAS
Year: 2016
Download: ADS | arXiv

 

Abstract

We explore the accuracy of the clustering-based redshift estimation proposed by Ménard et al. when applied to VIMOS Public Extragalactic Redshift Survey (VIPERS) and Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) real data. This method enables us to reconstruct redshift distributions from measurement of the angular clustering of objects using a set of secure spectroscopic redshifts. We use state-of-the-art spectroscopic measurements with iAB < 22.5 from the VIPERS as reference population to infer the redshift distribution of galaxies from the CFHTLS T0007 release. VIPERS provides a nearly representative sample to a flux limit of iAB < 22.5 at a redshift of >0.5 which allows us to test the accuracy of the clustering-based redshift distributions. We show that this method enables us to reproduce the true mean colour-redshift relation when both populations have the same magnitude limit. We also show that this technique allows the inference of redshift distributions for a population fainter than the reference and we give an estimate of the colour-redshift mapping in this case. This last point is of great interest for future large-redshift surveys which require a complete faint spectroscopic sample.

Are the halo occupation predictions consistent with large-scale galaxy clustering?

Are the halo occupation predictions consistent with large-scale galaxy clustering?

Posted on by Samuel Farrens

 

Authors: A. Pujol and E. Gaztañaga
Journal: MNRAS 
Year: 08/2014
Download: ADS|Arxiv

Abstract

We study how well we can reconstruct the two-point clustering of galaxies on linear scales, as a function of mass and luminosity, using the halo occupation distribution (HOD) in several semi-analytical models (SAMs) of galaxy formation from the Millennium Simulation. We find that the HOD with Friends-of-Friends groups can reproduce galaxy clustering better than gravitationally bound haloes. This indicates that Friends-of-Friends groups are more directly related to the clustering of these regions than the bound particles of the overdensities. In general, we find that the reconstruction works at best to ≃5 per cent accuracy: it underestimates the bias for bright galaxies. This translates to an overestimation of 50 per cent in the halo mass when we use clustering to calibrate mass. We also found a degeneracy on the mass prediction from the clustering amplitude that affects all the masses. This effect is due to the clustering dependence on the host halo substructure, an indication of assembly bias. We show that the clustering of haloes of a given mass increases with the number of subhaloes, a result that only depends on the underlying matter distribution. As the number of galaxies increases with the number of subhaloes in SAMs, this results in a low bias for the HOD reconstruction. We expect this effect to apply to other models of galaxy formation, including the real Universe, as long as the number of galaxies increases with the number of subhaloes. We have also found that the reconstructions of galaxy bias from the HOD model fail for low-mass haloes with M ≲ 3-5 × 1011 h-1 M⊙. We find that this is because galaxy clustering is more strongly affected by assembly bias for these low masses.

Darth Fader: Using wavelets to obtain accurate redshifts of spectra at very low signal-to-noise

Darth Fader: Using wavelets to obtain accurate redshifts of spectra at very low signal-to-noise

Posted on by Samuel Farrens

 

Authors: D. P. Machado, A. Leonard, J.-L. Starck, F. B. Abdalla, S. Jouvel
Journal: A&A
Year: 2013
Download: ADS | arXiv

Abstract

We present the DARTH FADER algorithm, a new wavelet-based method for estimating redshifts of galaxy spectra in spectral surveys that is particularly adept in the very low SNR regime. We use a standard cross-correlation method to estimate the redshifts of galaxies, using a template set built using a PCA analysis on a set of simulated, noise-free spectra. Darth Fader employs wavelet filtering to both estimate the continuum & to extract prominent line features in each galaxy spectrum. A simple selection criterion based on the number of features present in the spectrum is then used to clean the catalogue: galaxies with fewer than six total features are removed as we are unlikely to obtain a reliable redshift estimate. Applying our wavelet-based cleaning algorithm to a simulated testing set, we successfully build a clean catalogue including extremely low signal-to-noise data (SNR=2.0), for which we are able to obtain a 5.1% catastrophic failure rate in the redshift estimates (compared with 34.5% prior to cleaning). We also show that for a catalogue with uniformly mixed SNRs between 1.0 & 20.0, with realistic pixel-dependent noise, it is possible to obtain redshifts with a catastrophic failure rate of 3.3% after cleaning (as compared to 22.7% before cleaning). Whilst we do not test this algorithm exhaustively on real data, we present a proof of concept of the applicability of this method to real data, showing that the wavelet filtering techniques perform well when applied to some typical spectra from the SDSS archive. The Darth Fader algorithm provides a robust method for extracting spectral features from very noisy spectra. The resulting clean catalogue gives an extremely low rate of catastrophic failures, even when the spectra have a very low SNR. For very large sky surveys, this technique may offer a significant boost in the number of faint galaxies with accurately determined redshifts.

Effect of model-dependent covariance matrix for studying Baryon Acoustic Oscillations

Effect of model-dependent covariance matrix for studying Baryon Acoustic Oscillations

Posted on by Jean-Luc Starck

 

Authors: A. Labatie, J.-L. Starck, M. Lachièze-Rey
Journal: ApJ
Year: 2012
Download: ADS | arXiv

Abstract

Large-scale structures in the Universe are a powerful tool to test cosmological models and constrain cosmological parameters. A particular feature of interest comes from Baryon Acoustic Oscillations (BAOs), which are sound waves traveling in the hot plasma of the early Universe that stopped at the recombination time. This feature can be observed as a localized bump in the correlation function at the scale of the sound horizon rs. As such, it provides a standard ruler and a lot of constraining power in the correlation function analysis of galaxy surveys. Moreover the detection of BAOs at the expected scale gives a strong support to cosmological models. Both of these studies (BAO detection and parameter constraints) rely on a statistical modeling of the measured correlation function ξ̂ . Usually ξ̂  is assumed to be gaussian, with a mean ξθ depending on the cosmological model and a covariance matrix C generally approximated as a constant (i.e. independent of the model). In this article we study whether a realistic model-dependent Cθ changes the results of cosmological parameter constraints compared to the approximation of a constant covariance matrix C. For this purpose, we use a new procedure to generate lognormal realizations of the Luminous Red Galaxies sample of the Sloan Digital Sky Survey Data Release 7 to obtain a model-dependent Cθ in a reasonable time. The approximation of Cθ as a constant creates small changes in the cosmological parameter constraints on our sample. We quantify this modeling error using a lot of simulations and find that it only has a marginal influence on cosmological parameter constraints for current and next-generation galaxy surveys. It can be approximately taken into account by extending the 1σ intervals by a factor ≈1.3.

Summary

We have designed a specific wavelet adapted to search for shells, and exploit the physics of the process by making use of two different mass tracers, introducing a specific statistic to detect the BAO features. We have applied our method to the detection of BAO in a galaxy sample drawn from the Sloan Digital Sky Survey (SDSS). We have used the "main" catalogue to trace the shells, and the luminous red galaxies (LRG) as tracers of the high density central regions. Using this new method, we detect, with a high significance, that the LRG in our sample are preferentially located close to the centers of shell-like structures in the density field, with characteristics similar to those expected from BAO (Arnalte-Mur, Labatie, Clerc, Martínez,  Starck et al, A&A, 2012). Then we have studied the classical method for detecting BAOs and the assumptions that the method requires. We have also found that the approximation of a constant covariance matrix in the classical BAO analysis method can affect non negligibly both the BAO detection and cosmological parameter constraints (Labatie, Starck, Lachieze-Rey, ApJ,2012a) (Labatie, Starck, Lachieze-Rey, ApJ,2012b).