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O. Ilbert

Publications and source records attributed to O. Ilbert.

At least 55 records · Page 3Linked to original sources
arXiv2022

The Main Sequence of star-forming galaxies across cosmic times

By compiling a comprehensive census of literature studies, we investigate the evolution of the Main Sequence (MS) of star-forming galaxies (SFGs) in the widest range of redshift ($0 < z < 6$) and stellar mass ($10^{8.5}-10^{11.5}$ $M_{\odot}$) ever probed. We convert all observations to a common calibration and find a remarkable consensus on the variation of the MS shape and normalization across cosmic time. The relation exhibits a curvature towards the high stellar masses at all redshifts. The best functional form is governed by two parameters: the evolution of the normalization and the turnover mass ($M_0(t)$), which both evolve as a power law of the Universe age. The turn-over mass determines the MS shape. It marginally evolves with time, making the MS slightly steeper towards $z\sim4-6$. At stellar masses below $M_0(t)$, SFGs have a constant specific SFR (sSFR), while above $M_0(t)$ the sSFR is suppressed. We find that the MS is dominated by central galaxies. This allows to turn $M_0(t)$ into the corresponding host halo mass. This evolves as the halo mass threshold between cold and hot accretion regimes, as predicted by the theory of accretion, where the central galaxy is fed or starved of cold gas supply, respectively. We, thus, argue that the progressive MS bending as a function of the Universe age is caused by the lower availability of cold gas in halos entering the hot accretion phase, in addition to black hole feedback. We also find qualitatively the same trend in the largest sample of star-forming galaxies provided by the IllustrisTNG simulation. Nevertheless, we still note large quantitative discrepancies with respect to observations, in particular at the high mass end. These can not be easily ascribed to biases or systematics in the observed SFRs and the derived MS.

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arXiv2022

Euclid preparation. XXI. Intermediate-redshift contaminants in the search for $z>6$ galaxies within the Euclid Deep Survey

(Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Euclid bands and availability of ancillary data could make the identification of z>6 galaxies challenging. In this work, we assess the degree of contamination by intermediate-redshift galaxies (z=1-5.8) expected for z>6 galaxies within the Euclid Deep Survey. This study is based on ~176,000 real galaxies at z=1-8 in a ~0.7 deg2 area selected from the UltraVISTA ultra-deep survey, and ~96,000 mock galaxies with 25.3$\leq$H<27.0, which altogether cover the range of magnitudes to be probed in the Euclid Deep Survey. We simulate Euclid and ancillary photometry from the fiducial, 28-band photometry, and fit spectral energy distributions (SEDs) to various combinations of these simulated data. Our study demonstrates that identifying z>6 with Euclid data alone will be very effective, with a z>6 recovery of 91(88)% for bright (faint) galaxies. For the UltraVISTA-like bright sample, the percentage of z=1-5.8 contaminants amongst apparent z>6 galaxies as observed with Euclid alone is 18%, which is reduced to 4(13)% by including ultra-deep Rubin (Spitzer) photometry. Conversely, for the faint mock sample, the contamination fraction with Euclid alone is considerably higher at 39%, and minimized to 7% when including ultra-deep Rubin data. For UltraVISTA-like bright galaxies, we find that Euclid (I-Y)>2.8 and (Y-J)<1.4 colour criteria can separate contaminants from true z>6 galaxies, although these are applicable to only 54% of the contaminants, as many have unconstrained (I-Y) colours. In the most optimistic scenario, these cuts reduce the contamination fraction to 1% whilst preserving 81% of the fiducial z>6 sample. For the faint mock sample, colour cuts are infeasible.

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arXiv2022

COSMOS2020: UV selected galaxies at $z\geq7.5$

This paper presents a new search for $z\geq7.5$ galaxies using the COSMOS2020 photometric catalogues. Finding galaxies at the reionization epoch through deep imaging surveys remains observationally challenging. The larger area covered by ground-based surveys like COSMOS enables the discovery of the brightest galaxies at these high redshifts. Covering $1.4$deg$^2$, our COSMOS catalogues were constructed from the latest UltraVISTA data release (DR4) combined with the final Spitzer/IRAC COSMOS images and the Hyper-Suprime-Cam Subaru Strategic Program DR2 release. We identify $17$ new $7.5<z<10$ candidate sources, and confirm $15$ previously published candidates. Using deblended photometry extracted by fitting surface brightness models on multi-band images, we select four candidates which would be rejected using fixed aperture photometry. We test the robustness of all our candidates by comparing six different photometric redshift estimates. Finally, we compute the galaxy UV luminosity function in three redshift bins centred at $z=8,9,10$. We find no clear evolution of the number density of the brightest galaxies $M_\text{UV}<-21.5$, in agreement with previous works. Rapid changes in the quenching efficiency or attenuation by dust could explain such lack of evolution between $z\sim 8$ and $z\sim 9. A spectroscopic confirmation of the redshifts, already planned with JWST and the Keck telescopes, will be essential to confirm our results.

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arXiv2022

COSMOS2020: The cosmic evolution of the stellar-to-halo mass relation for central and satellite galaxies up to z~5

We use the COSMOS2020 catalogue to measure the stellar-to-halo mass relation (SHMR) divided by central and satellite galaxies from $z=0.2$ to $z = 5.5$. Starting from accurate photometric redshifts we measure the near-infrared selected two-point angular correlation and stellar mass functions in ten redshift bins and fit them with an HOD-based model. At each redshift, we measure the ratio of stellar mass to halo mass, $M_*/M_h$, which shows the characteristic strong dependence of halo mass with a peak at $M_h^{\rm peak} \sim 10^{12}\, M_{\odot}$. Our results are in accordance with the scenario in which the peak of star-formation efficiency moves towards more massive halos at higher redshifts. We also measure the fraction of satellites as a function of stellar mass and redshift. For all stellar mass thresholds the satellite fraction decreases at higher redshifts. At a given redshift there is a higher fraction of low-mass satellites. The satellite contribution to the total stellar mass budget in halos becomes more important than centrals at halo masses of about $M_h > 10^{13} \, M_{\odot}$ and always stays below by peak, indicating that quenching mechanisms are present in massive halos that keep the star-formation efficiency low. Finally, we compare our results with three hydrodynamical simulations Horizon-AGN, Illustris-TNG-100 and EAGLE. We find that the most significant discrepancy is at the high mass end, where the simulations generally show that satellites have a higher contribution to the total stellar mass budget than the observations. This, together with the finding that the fraction of satellites is higher in the simulations, indicates that the feedback mechanisms acting in group-and cluster-scale halos appear to be less efficient in quenching the mass assembly of satellites, and/or that quenching occurs much later in the simulations.

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arXiv2022

COSMOS2020: Manifold Learning to Estimate Physical Parameters in Large Galaxy Surveys

We present a novel method to estimate galaxy physical properties from spectral energy distributions (SEDs), alternate to template fitting techniques and based on self-organizing maps (SOM) to learn the high-dimensional manifold of a photometric galaxy catalog. The method has been previously tested with hydrodynamical simulations in Davidzon et al. (2019) while here is applied to real data for the first time. It is crucial for its implementation to build the SOM with a high quality, panchromatic data set, which we elect to be the "COSMOS2020" galaxy catalog. After the training and calibration steps with COSMOS2020, other galaxies can be processed through SOM to obtain an estimate of their stellar mass and star formation rate (SFR). Both quantities result to be in good agreement with independent measurements derived from more extended photometric baseline, and also their combination (i.e., the SFR vs. stellar mass diagram) shows a main sequence of star forming galaxies consistent with previous studies. We discuss the advantages of this method compared to traditional SED fitting, highlighting the impact of having, instead of the usual synthetic templates, a collection of empirical SEDs built by the SOM in a "data-driven" way. Such an approach also allows, even for extremely large data sets, an efficient visual inspection to identify photometric errors or peculiar galaxy types. Considering in addition the computational speed of this new estimator, we argue that it will play a valuable role in the analysis of oncoming large-area surveys like Euclid or the Legacy Survey of Space and Time at the Vera Cooper Rubin Telescope.

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arXiv2022

The VIMOS Ultra Deep Survey: The reversal of the star-formation rate $-$ density relation at $2 < z < 5$

Utilizing spectroscopic observations taken for the VIMOS Ultra-Deep Survey (VUDS), new observations from Keck/DEIMOS, and publicly available observations of large samples of star-forming galaxies, we report here on the relationship between the star formation rate (SFR) and the local environment ($δ_{gal}$) of galaxies in the early universe ($2<z<5$). Unlike what is observed at lower redshifts ($z<2$), we observe a definite, nearly monotonic increase in the average SFR with increasing galaxy overdensity over more than an order of magnitude in $δ_{gal}$. The robustness of this trend is quantified by accounting for both uncertainties in our measurements and galaxy populations that are either underrepresented or not present in our sample and find that the trend remains significant under all circumstances. This trend appears to be primarily driven by the fractional increase of galaxies in high density environments that are more massive in their stellar content and are forming stars at a higher rate than their less massive counterparts. We find that, even after stellar mass effects are accounted for, there remains a weak but significant SFR-$δ_{gal}$ trend in our sample implying that additional environmentally-related processes are helping to drive this trend. We also find clear evidence that the average SFR of galaxies in the densest environments increases with increasing redshift. These results lend themselves to a picture in which massive gas-rich galaxies coalesce into proto-cluster environments at $z\sim3$, interact with other galaxies or with a forming large-scale medium, subsequently using or losing most of their gas in the process, and begin to seed the nascent red sequence that is present in clusters at slightly lower redshifts.

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arXiv2022

Photometric Redshift Estimation with Convolutional Neural Networks and Galaxy Images: A Case Study of Resolving Biases in Data-Driven Methods

Deep Learning models have been increasingly exploited in astrophysical studies, yet such data-driven algorithms are prone to producing biased outputs detrimental for subsequent analyses. In this work, we investigate two major forms of biases, i.e., class-dependent residuals and mode collapse, in a case study of estimating photometric redshifts as a classification problem using Convolutional Neural Networks (CNNs) and galaxy images with spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multi-channel outputs, balancing the training data and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshifts or photometric redshifts, and the biases with respect to these two definitions are incompatible and should be treated in a split way. We suggest that resolving biases in the spectroscopic space is a prerequisite for resolving biases in the photometric space. Experiments show that our methods possess a better capability in controlling biases compared to benchmark methods, and exhibit robustness under varying implementing and training conditions provided with high-quality data. Our methods have promises for future cosmological surveys that require a good constraint of biases, and may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance trade-off and the demand on sufficient statistics suggest the need for developing better methodologies and optimizing data usage strategies.

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arXiv2021

Euclid preparation: XVIII. Cosmic Dawn Survey. Spitzer observations of the Euclid deep fields and calibration fields

We present a new infrared survey covering the three Euclid deep fields and four other Euclid calibration fields using Spitzer's Infrared Array Camera (IRAC). We have combined these new observations with all relevant IRAC archival data of these fields in order to produce the deepest possible mosaics of these regions. In total, these observations represent nearly 11% of the total Spitzer mission time. The resulting mosaics cover a total of approximately 71.5deg$^2$ in the 3.6 and 4.5um bands, and approximately 21.8deg$^2$ in the 5.8 and 8um bands. They reach at least 24 AB magnitude (measured to sigma, in a 2.5 arcsec aperture) in the 3.6um band and up to ~ 5 mag deeper in the deepest regions. The astrometry is tied to the Gaia astrometric reference system, and the typical astrometric uncertainty for sources with 16<[3.6]<19 is <0.15 arcsec. The photometric calibration is in excellent agreement with previous WISE measurements. We have extracted source number counts from the 3.6um band mosaics and they are in excellent agreement with previous measurements. Given that the Spitzer Space Telescope has now been decommissioned these mosaics are likely to be the definitive reduction of these IRAC data. This survey therefore represents an essential first step in assembling multi-wavelength data on the Euclid deep fields which are set to become some of the premier fields for extragalactic astronomy in the 2020s.

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arXiv2021

COSMOS2020: A panchromatic view of the Universe to $z\sim10$ from two complementary catalogs

The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data has been collected in the COSMOS field. This paper describes the collection, processing, and analysis of this new imaging data to produce a new reference photometric redshift catalog. Source detection and multi-wavelength photometry is performed for 1.7 million sources across the $2\,\mathrm{deg}^{2}$ of the COSMOS field, $\sim$966,000 of which are measured with all available broad-band data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The $i<21$ sources have sub-percent photometric redshift accuracy and even the faintest sources at $25<i<27$ reach a precision of $5\,\%$. Finally, these results are discussed in the context of previous, current, and future surveys in the COSMOS field. Compared to COSMOS2015, reaches the same photometric redshift precision at almost one magnitude deeper. Both photometric catalogs and their photometric redshift solutions and physical parameters will be made available through the usual astronomical archive systems (ESO Phase 3, IPAC IRSA, and CDS).

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arXiv2021

Euclid preparation: XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography

The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on the accurate knowledge of the galaxy mean redshift $\langle z \rangle$. We investigate the possibility of measuring $\langle z \rangle$ with an accuracy better than $0.002\,(1+z)$, in ten tomographic bins spanning the redshift interval $0.2 99.8\%$. The zPDF approach could also be successful if we debias the zPDF using a spectroscopic training sample. This approach requires deep imaging data, but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the debiasing method and confirm our finding by applying it to real-world weak-lensing data sets (COSMOS and KiDS+VIKING-450).

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arXiv2020

Euclid preparation: X. The Euclid photometric-redshift challenge

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-$z$s at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2--2.6 redshift range that the Euclid mission will probe. We design a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data are divided into two samples: one calibration sample for which photometry and redshifts are provided to the participants; and the validation sample, containing only the photometry, to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates sources they consider unfit for use in cosmological analyses. The performance of each method is assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, sources for which the photo-z deviates by more than 0.15(1+z) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. [abridged]

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arXiv2020

Euclid preparation: VIII. The Complete Calibration of the Colour-Redshift Relation survey: VLT/KMOS observations and data release

The Complete Calibration of the Colour-Redshift Relation survey (C3R2) is a spectroscopic effort involving ESO and Keck facilities designed to empirically calibrate the galaxy colour-redshift relation - P(z|C) to the Euclid depth (i_AB=24.5) and is intimately linked to upcoming Stage IV dark energy missions based on weak lensing cosmology. The aim is to build a spectroscopic calibration sample that is as representative as possible of the galaxies of the Euclid weak lensing sample. In order to minimise the number of spectroscopic observations to fill the gaps in current knowledge of the P(z|C), self-organising map (SOM) representations of the galaxy colour space have been constructed. Here we present the first results of an ESO@ VLT Large Programme approved in the context of C3R2, which makes use of the two VLT optical and near-infrared multi-object spectrographs, FORS2 and KMOS. This paper focuses on high-quality spectroscopic redshifts of high-z galaxies observed with the KMOS spectrograph in the H- and K-bands. A total of 424 highly-reliable z are measured in the 1.3<=z<=2.5 range, with total success rates of 60.7% in the H-band and 32.8% in the K-band. The newly determined z fill 55% of high and 35% of lower priority empty SOM grid cells. We measured Halpha fluxes in a 1."2 radius aperture from the spectra of the spectroscopically confirmed galaxies and converted them into star formation rates. In addition, we performed an SED fitting analysis on the same sample in order to derive stellar masses, E(B-V), total magnitudes, and SFRs. We combine the results obtained from the spectra with those derived via SED fitting, and we show that the spectroscopic failures come from either weakly star-forming galaxies (at z<1.7, i.e. in the H-band) or low S/N spectra (in the K-band) of z>2 galaxies.

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arXiv2020

Simulating JWST deep extragalactic imaging surveys and physical parameter recovery

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 $5 6$ and redshifts $0 5$ 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 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 $50\%$ for $m_\text{UV}<27.5$ sources at all redshifts, and the purity is maintained above $80$ and $60\%$ at $z\leq7$ 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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arXiv2020

PhotoWeb redshift: boosting photometric redshift accuracy with large spectroscopic surveys

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. Photometric redshifts can be efficiently combined with the cosmic web (CW) extracted from overlapping spectroscopic surveys to improve their accuracy. 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, $r \leq 17.8$) and the GAMA spectroscopic redshifts up tor $\sim 19.8$. The mapping of the CW 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, $\leq 120$ Mpc), intercept a few CW structure along the line of sight. Combining these PDFs with the density field distribution provides new photometric redshifts, $z_{web}$, whose accuracy is improved by a factor of two (i.e.,$σ \sim 0.004(1+z)$) for galaxies with $r \leq 17.8$. 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 $z_{web}$ 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%. 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 CW is the highest.

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arXiv2020

A hyper luminous starburst at z=4.72 magnified by a lensing galaxy pair at z=1.48

[Abridged] We discovered in the Herschel Reference Survey an extremely bright IR source with $S_{500}$~120mJy (Red Virgo 4 - RV4). Based on IRAM/EMIR and IRAM/NOEMA detections of the CO(5-4), CO(4-3), and [CI] lines, RV4 is located at z=4.724, yielding a total observed L$_{IR}$ of 1.1+/-0.6x0$^{14}$L$_{\odot}$. At the position of the Herschel emission, three blobs are detected with the VLA at 10cm. The CO(5-4) line detection of each blob confirms that they are at the same redshift with the same line width, indicating that they are multiple images of the same source. In Spitzer and deep optical observations, two sources, High-z Lens 1 (HL1) West and HL1 East, are detected at the center of the three VLA/NOEMA blobs. These two sources are placed at z=1.48 with XSHOOTER spectra, suggesting that they could be merging and gravitationally lensing the emission of RV4. HL1 is the second most distant lens known to date in strong lensing systems. The Einstein radius of the lensing system is 2.2"+/-0.2 (20kpc). The high redshift of HL1 and the large Einstein radius are highly unusual for a strong lensing system. We present the ISM properties of the background source RV4. Different estimates of the gas depletion time yield low values suggesting that RV4 is a SB galaxy. Among all high-z SMGs, this source exhibits one of the lowest L$_{[CI]}$ to L$_{IR}$ ratios, 3.2+/-0.9x10$^{-6}$, suggesting an extremely short gas tdepl of only 14+/-5Myr. It also shows a relatively high L$_{[CI]}$ to L$_{CO(4-3)}$ ratio (0.7+/-0.2) and low L$_{CO(5-4)}$ to L$_{IR}$ ratio (only ~50% of the value expected for normal galaxies) hinting a low density of gas. Finally, we discuss that the short tdepl of RV4 can be explained by either a very high SFE, which is difficult to reconcile with major mergers simulations of high-z galaxies, or a rapid decrease of SF, which would bias the estimate of tdepl toward low value.

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arXiv2019

The main sequence of star forming galaxies II. A non evolving slope at the high mass end

By using the deepest available mid and far infrared surveys in the CANDELS, GOODS and COSMOS fields we study the evolution of the Main Sequence (MS) of star forming galaxies (SFGs) from z~0 to` ~2.5 at stellar masses larger than 10^{10} M_{\odot}. The MS slope and scatter are consistent with a re-scaled version of the local relation and distribution, shifted at higher values of SFR according to ~(1+z)^{3.2}. The relation exhibits a bending at the high mass end and a slightly increasing scatter as a function of the stellar mass. We show that the previously reported evolution of the MS slope, in the considered mass and redshift range, is due to a selection effect. The distribution of galaxies in the MS region at fixed stellar mass is well represented by a single log-normal distribution at all redshifts and masses, with starburst galaxies (SBs) occupying the tail at high SFR.

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arXiv2019

The VIMOS Public Extragalactic Redshift Survey (VIPERS) -- Environment-size relation of massive passive galaxies at 0.5 < z < 0.8

We use the statistics of the VIPERS survey to investigate the relation between the surface mean stellar mass density Sigma=Mstar/(2*pi*Re^2) of massive passive galaxies (MPGs, Mstar>10^11 Msun) and their environment in the redshift range 0.5 2*10^11 Msun, we find an excess of MPGs with low Sigma and a deficit of high-Sigma MPGs in the densest regions wrt other environments. We interpret this result as due to the migration of some high-Sigma MPGs (<1% of the total population of MPGs) into low-Sigma MPGs, probably through mergers or cannibalism of small satellites. In summary, our results imply that the accretion of satellite galaxies has a marginal role in the mass-assembly history of most MPGs. We have previously found that the number density of VIPERS massive star-forming galaxies (MSFGs) declines rapidily from z=0.8 to z=0.5, which mirrors the rapid increase in the number density of MPGs. This indicates that the MSFGs at z>0.8 migrate to the MPG population. Here, we investigate the Sigma-delta relation of MSFGs at z>0.8 and find that it is consistent within 1 sigma with that of low-Sigma MPGs at z<0.8. Thus, the results of this and our previous paper show that MSFGs at z>0.8 are consistent in terms of number and environment with being the progenitors of low-Sigma MPGs at z<0.8.

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