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Antonio D. Montero-Dorta

Publications and source records attributed to Antonio D. Montero-Dorta.

At least 37 records · Page 2Linked to original sources

Secondary halo bias through cosmic time II: Reconstructing halo properties using clustering information

When constructing galaxy mock catalogs based on suits of dark matter halo catalogs generated with approximated, calibrated or machine-learning approaches, the assignment of intrinsic properties for such tracers is a step of paramount relevance, given that these can shape the abundance of mock galaxy cluster and the spatial distribution of mock galaxies. We explore the possibility to assign properties of dark matter halos within the context of calibrated/learning approaches, explicitly using clustering information. The goal is to retrieve the correct signal of primary and secondary large-effective bias as a function of properties reconstructed solely based on phase-space properties of the halo distribution and dark matter density field. The algorithm reconstructs a set halo properties (such as virial mass, maximum circular velocity, concentration and spin) constraint to reproduce both primary and secondary (or assembly) bias. The key ingredients of the algorithm are the implementation of individually-assigned large-scale effective bias, a multi-scale approach to account for halo exclusion and a hierarchical assignment of halo properties. The method facilitates the assignment of halo properties aiming at replicating the large-scale effective bias, both primary and secondary. This improves over over previous methods found in the literature, especially at the high mass population. We have designed an strategy to reconstruct the main properties of dark matter halos obtained by calibrated/learning algorithms, in a way that the expected one and two-point statistics (on large scales) replicates the signal from detailed N-body simulations. We encourage the application of this strategy (or the implementation of our algorithm) for the generation of mock catalogs of dark matter halos based on approximated methods.

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Secondary halo bias through cosmic time I: Scaling relations and the connection with the cosmic web

We measure the signal of secondary halo bias as a function of a variety of intrinsic and environmental halo properties, and characterize its statistical significance as a function of cosmological redshift. Using fixed and paired $N$-body simulations of dark-matter halos -- the UNIT simulation -- with masses above $10^{11}M_{\odot}h^{-1}$ identified over a wide range of cosmological redshifts (0<z<5), we explore the behavior of the scaling relations among different halo properties. We include novel environmental properties based on the halo distribution as well as the underlying dark-matter field. We implement an object-by-object estimator of large-scale effective bias and test its validity against standard approaches. With a bias assigned to each tracer, we perform a statistical analysis aiming at characterizing the distribution of bias and the signal of secondary halo bias. We show how the halo scaling relations linking direct probes of the halo potential well do not depend on the environment. On the contrary, links between halo mass and the so called set of secondary halo properties are sensitive to the cosmological environment. We show that the signal of secondary bias derives statistically from secondary correlations beyond the standard link to halo mass. We also show that the secondary bias arise through non-local and/or environmental properties related either to the halo distribution or to the properties of the underlying dark-matter field. Properties such as the tidal field and the local Mach number generates the signals of secondary bias with the highest significance. We propose applications of the assignment of individual bias for the generation of mock catalogs containing the signal of secondary bias, as well as a series of cosmological analyses aiming at mining large galaxy data sets.

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The dependence of assembly bias on the cosmic web

For low-mass haloes, the physical origins of halo assembly bias have been linked to the slowdown of accretion due to tidal forces, which are expected to be more dominant in some cosmic-web environments as compared to others. In this work, we use publicly available data from the application of the Discrete Persistent Structures Extractor (DisPerSE) to the IllustrisTNG magnetohydrodynamical simulation to investigate the dependence of the related galaxy assembly bias effect on the cosmic web. We first show that, at fixed halo mass, the galaxy population displays significant low-mass secondary bias when split by distance to DisPerSE critical points representing nodes ($d_{\rm node}$), filaments ($d_{\rm skel}$), and saddles ($d_{\rm sadd}$), with objects closer to these features being more tightly clustered. The secondary bias produced by some of these parameters exceeds the assembly bias signal considerably at some mass ranges, particularly for $d_{\rm sadd}$. We also demonstrate that the assembly bias signal is reduced significantly when clustering is conditioned to galaxies being close or far from these critical points. The maximum attenuation is measured for galaxies close to saddle points, where less than 35$\%$ of the signal remains. Conversely, objects near voids preserve a fairly pristine effect (almost 85$\%$ of the signal). Our analysis confirms the important role played by the tidal field in shaping assembly bias, but they are also consistent with the signal being the result of different physical mechanisms. Our work introduces some new aspects of secondary bias where the predictions from hydrodynamical simulations can be directly tested with observational data.

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High-fidelity reproduction of central galaxy joint distributions with Neural Networks

The relationship between galaxies and haloes is central to the description of galaxy formation, and a fundamental step towards extracting precise cosmological information from galaxy maps. However, this connection involves several complex processes that are interconnected. Machine Learning methods are flexible tools that can learn complex correlations between a large number of features, but are traditionally designed as deterministic estimators. In this work, we use the IllustrisTNG300-1 simulation and apply neural networks in a binning classification scheme to predict probability distributions of central galaxy properties, namely stellar mass, colour, specific star formation rate, and radius, using as input features the halo mass, concentration, spin, age, and the overdensity on a scale of 3 $h^{-1}$ Mpc. The model captures the intrinsic scatter in the relation between halo and galaxy properties, and can thus be used to quantify the uncertainties related to the stochasticity of the galaxy properties with respect to the halo properties. In particular, with our proposed method, one can define and accurately reproduce the properties of the different galaxy populations in great detail. We demonstrate the power of this tool by directly comparing traditional single-point estimators and the predicted joint probability distributions, and also by computing the power spectrum of a large number of tracers defined on the basis of the predicted colour-stellar mass diagram. We show that the neural networks reproduce clustering statistics of the individual galaxy populations with excellent precision and accuracy.

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Tracking the evolution of satellite galaxies: mass stripping and dark-matter deficient galaxies

Satellite galaxies undergo a variety of physical processes when they are accreted by groups and clusters, often resulting in the loss of baryonic and dark matter (DM) mass. In this work, we evaluate the predictions from the IllustrisTNG hydrodynamical simulation regarding the evolution of the matter content of satellites, focusing on a population that are accreted at $z>1$ and retain their identity as satellites down to $z=0$. At fixed host halo mass, the amount of DM and stellar mass stripped depends mostly on the pericentric distance, $d_{\rm peri}$, here normalised by host halo virial radius. The closest encounters result in significant loss of DM, with subhaloes retaining between 20 and a few per cent of their $z=1$ mass. At fixed $d_{\rm peri}$, DM mass stripping seems more severe in lower mass haloes. Conversely, the average satellite in higher mass haloes has its stellar mass growth halted earlier, having lost a higher fraction of stellar mass by $z=0$. We also show that mass stripping has a strong impact on the quenched fractions. The IllustrisTNG boxes are qualitatively consistent in these predictions, with quantitative differences mostly originating from the distinct subhalo mass ranges covered by the boxes. Finally, we have identified DM-deficient systems in all TNG boxes. These objects are preferentially found in massive clusters ($M_{\rm host } \gtrsim 10^{13}$ M$_\odot$), had very close encounters with their central galaxies ($d_{\rm peri}\simeq0.05\, R_{\rm vir}$), and were accreted at high redshift ($z_{\rm infall} \gtrsim 1.4$), reinforcing the notion that tidal stripping is responsible for their remarkable lack of DM.

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Mimicking the halo-galaxy connection using machine learning

Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of objects is also taken under consideration, it becomes very relevant for cosmological measurements. In this paper, we use machine learning techniques to analyse these intricate relations in the IllustrisTNG300 magnetohydrodynamical simulation, predicting baryonic properties from halo properties. We employ four different algorithms: extremely randomized trees, K-nearest neighbours, light gradient boosting machine, and neural networks, along with a unique and powerful combination of the results from all four approaches. Overall, the different algorithms produce consistent results in terms of predicting galaxy properties from a set of input halo properties that include halo mass, concentration, spin, and halo overdensity. For stellar mass, the Pearson correlation coefficient is 0.98, dropping down to 0.7-0.8 for specific star formation rate (sSFR), colour, and size. In addition, we apply, for the first time in this context, an existing data augmentation method, synthetic minority over-sampling technique for regression with Gaussian noise (SMOGN), designed to alleviate the problem of imbalanced data sets, showing that it improves the overall shape of the predicted distributions and the scatter in the halo-galaxy relations. We also demonstrate that our predictions are good enough to reproduce the power spectra of multiple galaxy populations, defined in terms of stellar mass, sSFR, colour, and size with high accuracy. Our results align with previous reports suggesting that certain galaxy properties cannot be reproduced using halo features alone.

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On the environmental influence of groups and clusters of galaxies beyond the virial radius: Galactic conformity at few Mpc scales

The environment within dark matter haloes can quench the star formation of galaxies. However, environmental effects beyond the virial radius of haloes ($\gtrsim$ 1 Mpc) are less evident. An example is the debated correlation between colour or star formation in central galaxies and neighbour galaxies in adjacent haloes at large separations of several Mpc, referred to as two-halo galactic conformity. We use two galaxy catalogues generated from different versions of the semi-analytic model SAG applied to the MDPL2 cosmological simulation and the IllustrisTNG300 cosmological hydrodynamical simulation to study the two-halo conformity by measuring the quenched fraction of neighbouring galaxies as a function of the real-space distance from central galaxies. We find that low-mass central galaxies in the vicinity of massive systems ($M_{\rm 200c}$ $\geq$ 10$^{13}$ $h^{-1}~\rm M_{\odot}$) out to 5 $h^{-1}$ Mpc are preferentially quenched compared to other central galaxies at fixed stellar mass $M_{\star}$ or fixed host halo mass $M_{\rm 200c}$ at $z$ ~ 0. In all the galaxies catalogues is consistent that the low-mass ($M_{\star} < 10^{10}$ $h^{-1}~\rm M_{\odot}$ or $M_{\rm 200c} < 10^{11.8}$ $h^{-1}~\rm M_{\odot}$) central galaxies in the vicinity of clusters and, especially, groups of galaxies mostly produce the two-halo galactic conformity. On average, the quenched low-mass central galaxies are much closer to massive haloes than star-forming central galaxies of the same mass (by a factor of ~5). Our results agree with other works regarding the environmental influence of massive haloes that can extend beyond the virial radius and affect nearby low-mass central galaxies.

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Measuring the growth of structure by matching dark matter haloes to galaxies with VIPERS and SDSS

We test the history of structure formation from redshift 1 to today by matching galaxies from VIPERS and SDSS with dark matter haloes in the MultiDark SMDPL N-body simulation. We first show that the standard subhalo abundance matching (SHAM) recipe implemented with MultiDark characterizes the clustering of galaxies well both at redshift 0 for SDSS and at redshift 1 for VIPERS. This is an important validation of the SHAM model at high redshift. We then remap the simulation timesteps to test alternative growth histories and infer the growth index $γ=0.6\pm0.3$. This analysis demonstrates the power of using N-body simulations to forward model galaxy surveys for cosmological inference.

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SHAM through the lens of a hydrodynamical simulation

We use the IllustrisTNG100 hydrodynamical simulation to study the dependence of the galaxy two-point correlation function on a broad range of secondary subhalo and galactic properties. We construct galaxy mock catalogues adopting a standard sub-halo abundance matching scheme coupled with a secondary assignment between galaxy colour or specific star formation rate and the following subhalo properties: starvation redshift z$_{\rm starve}$, concentration at infall, overdensity $δ_R^{\rm env}$, tidal anisotropy $α_R$, and tidal overdensity $δ_R$. The last two quantities allow us to fully characterise the tidal field of our subhaloes, acting as mediators between their internal and large-scale properties. The resulting mock catalogues overall return good agreement with the IllustrisTNG100 measurements. The accuracy of each model strongly depends on the correlation between the secondary galaxy and subhalo properties employed. Among all the subhalo proxies tested, we find that z$_{\rm starve}$ and $c_{\rm infall}$ are the ones that best trace the large-scale structure, producing robust clustering predictions for different samples of red/blue and quenched/star-forming galaxies.

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The large-scale distribution of ionized metals in IllustrisTNG

We study the intrinsic large-scale distribution and evolution of seven ionized metals in the IllustrisTNG magneto-hydrodynamical cosmological simulation. We focus on the fractions of C\,\textsc{ii}, C\,\textsc{iv}, Mg\,\textsc{ii}, N\,\textsc{v}, Ne\,\textsc{viii}, O\,\textsc{vi}, and Si\,\textsc{iv} in different cosmic web structures (filaments, haloes, and voids) and gas phases (warm-hot intergalactic medium WHIM, hot, diffuse, and condensed gas) from $z=6$ to $z=0$. Our analysis provides a new perspective to the study of the distribution and evolution of baryons across cosmic time while offering new hints in the context of the well-known missing baryons problem. The cosmic web components are here identified using the local comoving dark matter density, which provides a simple but effective way of mapping baryons on large scales. Our results show that C\,\textsc{ii} and Mg\,\textsc{ii} are mostly located in condensed gas inside haloes in high-density and low-temperature star-forming regions ($ρ_{\rm gas}/\barρ_{\rm bar}\gtrsim10^3$, and ${\rm T}\lesssim10^{5}$~K). C\,\textsc{iv} and Si\,\textsc{iv} present similar evolution of their mass fractions in haloes and filaments across cosmic time. In particular, their mass budgets in haloes in condensed phase ($ρ_{\rm gas}/\barρ_{\rm bar}\gtrsim10^3$, and ${\rm T}\lesssim10^{5}$~K) are driven by gas cooling and star formation with a peak at $z\sim2$. Finally, our results confirm that O\,\textsc{vi}, Ne\,\textsc{viii}, and N\,\textsc{v} are good tracers of warm/hot and low-density gas at low redshift ($ρ_{\rm gas}/\barρ_{\rm bar}\lesssim10^3$, and ${\rm T}\gtrsim10^{5}$~K), regions that are likely to contain most of the missing baryons in the local Universe.

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The galaxy size - halo mass scaling relations and clustering properties of central and satellite galaxies

In this work, we combine size and stellar mass measurements from the Sloan Digital Sky Server (SDSS) with the group finder algorithm of Rodriguez \& Merchán in order to determine the stellar and halo mass -- size relations of central and satellite galaxies separately. We show that, while central and satellite galaxies display similar stellar mass -- size relations, their halo mass -- size relations differ significantly. As expected, more massive haloes tend to host larger central galaxies. However, the size of satellite galaxies depends only slightly on halo virial mass. We show that these results are compatible with a remarkably simple model in which the size of central and satellite galaxies scales as the cubic root of their host halo mass, with the normalization for satellites being $\sim$ 30 \% smaller than that for central galaxies, which can be attributed to tidal stripping. We further check that our measurements are in excellent agreement with predictions from the IllustrisTNG hydrodynamical simulation. In the second part of this paper, we analyse how the clustering properties of central and satellite galaxies depend on their size. We demonstrate that, independently of the stellar mass threshold adopted, smaller galaxies are more tightly clustered than larger galaxies when either the entire sample or only satellites are considered. The opposite trend is observed on large scales when the size split is performed for the central galaxies alone. Our results place significant constraints for halo-galaxy connection models that link galaxy size with the properties of their hosting haloes.

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On the influence of halo mass accretion history on galaxy properties and assembly bias

Halo assembly bias is the secondary dependence of the clustering of dark-matter haloes on their assembly histories at fixed halo mass. This established dependence is expected to manifest itself on the clustering of the galaxy population, a potential effect commonly known as galaxy assembly bias. Using the IllustrisTNG300 magnetohydrodynamical simulation, we analyse the dependence of the properties and clustering of galaxies on the shape of the specific mass accretion history of their hosting haloes (sMAH). We first show that several halo and galaxy properties strongly correlate with the slope of the sMAH ($β$) at fixed halo mass. Namely, haloes with increasingly steeper $β$ increment their halo masses faster at early times, and their hosted galaxies present larger stellar-to-halo mass ratios, lose their gas faster, reach the peak of their star formation histories at higher redshift, and become quenched earlier. We also demonstrate that $β$ is more directly connected to these key galaxy formation properties than other broadly employed halo proxies, such as formation time. Finally, we measure the secondary dependence of galaxy clustering on $β$ at fixed halo mass as a function of redshift. By tracing back the evolution of individual haloes, we show that the amplitude of the galaxy assembly bias signal for the progenitors of $z=0$ galaxies increases with redshift, reaching a factor of 2 at $z = 1$ for haloes of $M_\mathrm{halo}=10^{11.5}-10^{12}$ $h^{-1}\mathrm{M}_\odot$. The measurement of the evolution of assembly bias along the merger tree provides a new theoretical perspective to the study of secondary bias. Our findings, which show a tight relationship between halo accretion and both the clustering and the observational properties of the galaxy population, have also important implications for the generation of mock catalogues for upcoming cosmological surveys.

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The physical origins of low-mass spin bias

At $z=0$, higher-spin haloes with masses above $\log(\text{M}_{\text{c}}/h^{-1}\text{M}_\odot)\simeq 11.5$ have a higher bias than lower-spin haloes of the same mass. However, this trend is known to invert below this characteristic crossover mass, $\text{M}_{\text{c}}$. In this paper, we measure the redshift evolution and scale dependence of halo spin bias at the low-mass end and demonstrate that the inversion of the signal is entirely produced by the effect of splashback haloes. These low-mass haloes tend to live in the vicinity of significantly more massive haloes, thus sharing their large-scale bias properties. We further show that the location of the redshift-dependent crossover mass scale $\text{M}_{\text{c}}(z)$ is completely determined by the relative abundance of splashbacks in the low- and high-spin subpopulations. Once splashback haloes are removed from the sample, the intrinsic mass dependence of spin bias is recovered. Since splashbacks have been shown to account for some of the assembly bias signal at the low-mass end, our results unveil a specific link between two different secondary bias trends: spin bias and assembly bias.

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On the kinetic Sunyaev-Zel'dovich effect as an observational probe for halo spin bias

We explore the potential of the kinetic Sunyaev-Zel'dovich (kSZ) effect as the cornerstone of a future observational probe for halo spin bias, the secondary dependence of halo clustering on halo spin at fixed halo mass. Using the IllustrisTNG magneto-hydrodynamical cosmological simulation, we measure both the kSZ and the thermal SZ (tSZ) effects produced by the baryonic content of more than 50,000 haloes within the halo mass range $11 < \log_{10} ({\rm M_{vir}}/ h^{-1} {\rm M_{\odot}}) \lesssim 14.5$. First, we confirm that the magnitude of both effects depends strongly on the total gas and virial mass of the haloes, and that the integrated kSZ signal displays a significant correlation with the angular momentum of the intra-halo gas, particularly for massive haloes. Second, we show that both the integrated kSZ signal and the ratio of the integrated kSZ and tSZ signals trace total halo spin, even though significant scatter exists. Finally, we demonstrate that, in the absence of observational and instrumental uncertainties, these SZ-related statistics can be used to recover most of the underlying IllustrisTNG halo spin bias signal. Our analysis represents the first attempt to develop a future observational probe for halo spin bias, bringing forward alternative routes for measuring the secondary bias effects.

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The manifestation of secondary halo bias on the galaxy population from IllustrisTNG300

We use the improved IllustrisTNG300 magneto-hydrodynamical cosmological simulation to revisit the effect that secondary halo bias has on the clustering of the central galaxy population. With a side length of 205 $h^{-1}$Mpc and significant improvements on the sub-grid model with respect to the previous Illustris boxes, IllustrisTNG300 allows us to explore the dependencies of galaxy clustering over a large cosmological volume and wide halo-mass range. We show, at high statistical significance, that the halo assembly bias signal (i.e., the secondary dependence of halo bias on halo formation redshift) manifests itself on the clustering of the central galaxy population when this is split by stellar mass, colour, specific star formation rate, and surface density. A significant detection is also obtained for galaxy size: at fixed halo mass, larger central galaxies are more tightly clustered than smaller central galaxies in haloes of mass M$_{\rm vir} \lesssim 10^{12.5}$ $h^{-1}$M$_{\odot}$. This effect, however, seems to be uncorrelated with halo formation time, unlike the rest of the secondary dependencies analysed. We also explore the transmission of the halo spin bias signal, i.e., the secondary dependence of halo bias on halo spin. Although galaxy spin retains little information about the total spin of the halo, the correlation is enough to produce a significant galaxy spin bias signal. We discuss possible ways to probe the spin bias effects with observations.

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The Multi-Tracer Optimal Estimator applied to VIPERS

We use mock galaxy data from the VIMOS Public Extragalactic Redshift Survey (VIPERS) to test the performance of the Multi-Tracer Optimal Estimator (MTOE) of Abramo et al. as a tool to measure the monopoles of the power spectra of multiple tracers of the large-scale structure, $P^{(0)}_α(k)$. We show that MTOE provides more accurate measurements than the standard technique of Feldman, Kaiser & Peacock (FKP), independently of the tracer-selection strategy adopted, on both small and large scales. The largest improvements on individual $P^{(0)}_α(k)$ are obtained using a colour-magnitude selection on small scales, due to MTOE being naturally better equipped to deal with shot noise: we report an average error reduction with respect to FKP of $\sim$ 40$\%$ at $k \, [h$ Mpc$^{-1}]\gtrsim 0.3$. On large scales ($k[h$ Mpc$^{-1}]\lesssim0.1$), the gain in accuracy resulting from cosmic-variance cancellation is $\sim$ 10$\%$ for the ratios of $P^{(0)}_α(k)$. We have carried out a Monte-Carlo Markov Chain analysis to determine the impact of these gains on several quantities derived from $P^{(0)}_α(k)$. If we push the measurement to scales $0.3 < k \, [h$ Mpc$^{-1}]< 0.5$, the average improvements are $\sim$ 30 $\%$ for the amplitudes of the monopoles, $\sim$ 70 $\%$ for the monopole ratios, and $\sim$ 20 $\%$ for the galaxy biases. Our results highlight the potential of MTOE to shed light upon the physics that operate both on large and small cosmological scales. The effect of MTOE on cosmological constraints using VIPERS data will be addressed in a separate paper.

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The dependence of halo bias on age, concentration and spin

Halo bias is the main link between the matter distribution and dark matter halos. In its simplest form, halo bias is determined by halo mass, but there are known additional dependencies on other halo properties which are of consequence for accurate modeling of galaxy clustering. Here we present the most precise measurement of these secondary-bias dependencies on halo age, concentration, and spin, for a wide range of halo masses spanning from 10$^{10.7}$ to 10$^{14.7}$ $h^{-1}$ M$_{\odot}$. At the high-mass end, we find no strong evidence of assembly bias for masses above M$_{vir}$ $\sim10^{14}$ $h^{-1}$ M$_{\odot}$. Secondary bias exists, however, for halo concentration and spin, up to cluster-size halos, in agreement with previous findings. For halo spin, we report, for the first time, two different regimes: above M$_{vir}\sim$10$^{11.5}$ $h^{-1}$ M$_{\odot}$, halos with larger values of spin have larger bias, at fixed mass, with the effect reaching almost a factor 2. This trend reverses below this characteristic mass. In addition to these results, we test, for the first time, the performance of a multi-tracer method for the determination of the relative bias between different subsets of halos. We show that this method increases significantly the signal-to-noise of the secondary-bias measurement as compared to a traditional approach. This analysis serves as the basis for follow-up applications of our multi-tracer method to real data.

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The mass-size relation of LRGs from BOSS and DECaLS

We use the DECaLS DR3 survey photometry matched to the SDSS-III/BOSS DR12 spectroscopic catalog to investigate the morphology and stellar mass-size relation of luminous red galaxies (LRGs) within the CMASS and LOWZ galaxy samples in the redshift range $0.2<z<0.7$. The large majority of both samples is composed of early-type galaxies with De Vaucouleurs profiles, while only less than 20% are late-type exponentials. We calibrate DECaLS effective radii using the higher resolution CFHT/MegaCam observations and optimise the correction for each morphological type. By cross-matching the photometric properties of the early-type population with the Portsmouth stellar mass catalog, we are able to explore the high-mass end of the distribution using a large sample of 313,026 galaxies over 4380 deg$^{2}$. We find a clear correlation between the sizes and the stellar masses of these galaxies, which appears flatter than previous estimates at lower masses. The sizes of these early-type galaxies do not exhibit significant evolution within the BOSS redshift range, but a slightly declining redshift trend is found when these results are combined with $z\sim0.1$ SDSS measurements at the high-mass end. The synergy between BOSS and DECaLS has important applications in other fields, including galaxy clustering and weak lensing.

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