arXiv subjects

C. M. Baugh

Publications and source records attributed to C. M. Baugh.

At least 19 recordsLinked to original sources

arXiv2025

The PAU Survey: The $i$-band galaxy luminosity function from the present-day to $z = 2$

We present a measurement of the $i$-band galaxy luminosity function from the present-day to $z = 2$, using over 1.1 million galaxies from the Physics of the Accelerating Universe Survey (PAUS). PAUS combines broad-band imaging from the Canada-France-Hawaii Telescope Lensing Survey with narrow-band photometry from PAUCam, enabling high-precision photometric redshifts with an accuracy of $\sigma_{68} (\Delta z) = 0.019$ down to $i_{\textrm{AB}} = 23$. A synthetic lightcone mock catalogue built using the \texttt{GALFORM} semi-analytic model is used to simulate PAUS selection effects and photometric uncertainties, and to derive a machine-learning based estimate of the $k$-correction. We recover rest-frame $i$-band luminosities using a random forest regressor trained on simulated $ugriz$ photometry and redshifts. Luminosity functions are estimated using the $1/V_{\textrm{max}}$ method, accounting for photometric redshift and magnitude errors, and validated against mock data. We find good agreement between observations and models at $z < 1$, with increasing discrepancies at higher redshifts due to photometric redshift outliers. The bright-end of the luminosity function becomes flatter at high redshift, primarily driven by redshift errors. We show that the faint-end of the luminosity function becomes more incomplete with increasing redshift, but is still useful for constraining models. We analyze the red and blue galaxy populations separately, observing distinct evolutionary trends. The model overpredicts the number of both faint red and blue galaxies. Our study highlights the importance of accurate redshift estimation and selection modeling for robust luminosity function recovery, and demonstrates that PAUS can characterise the galaxy population with photometric redshifts across a wide redshift baseline.

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arXiv2025

Sub-millimeter galaxies in hierarchical models: revisiting the need for a top-heavy stellar initial mass function with Bayesian optimisation

The properties of high-redshift sub-millimetre galaxies (SMGs) remain controversial within hierarchical structure formation models. We revisit whether a top-heavy stellar initial mass function (IMF) in starbursts is required to reproduce both SMG observations and local galaxy properties. Using Bayesian optimisation, we perform an extensive search of the 15-dimensional parameter space of the GALFORM semi-analytical model. This efficient approach converges to optimal parameter values in fewer than 200 model evaluations, representing orders of magnitude fewer runs than traditional methods. We test whether GALFORM can simultaneously match three key observational constraints: the $z=0$ $K$-band luminosity function, the SMG number counts at 850~$\mu$m, and the SMG redshift distribution. We consider two model variants: one with a universal solar neighbourhood IMF for all star formation, and another allowing the IMF slope in starbursts to vary as a free parameter. When assuming a universal Chabrier IMF, we find no parameter combination that simultaneously reproduces all three datasets. The model either matches the SMG constraints while grossly overpredicting the local $K$-band luminosity function, or matches the local luminosity function while severely underpredicting SMG counts by factors of 3--100. In contrast, allowing a top-heavy IMF in starbursts enables excellent simultaneous fits to all constraints. The best-fitting model prefers an IMF slope parameter $x \approx 0.7$ (where d$n$/dlog$m \propto m^{-x}$), somewhat more top-heavy than recent models but less extreme than early proposals. Our comprehensive parameter space exploration definitively confirms that, within the GALFORM framework, a top-heavy IMF in starbursts is necessary to reconcile high-redshift dusty star-forming galaxies with local galaxy populations.

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arXiv2025

The PAU Survey: Measuring intrinsic galaxy alignments in deep wide fields as a function of colour, luminosity, stellar mass and redshift

We present the measurements and constraints of intrinsic alignments (IA) in the Physics of the Accelerating Universe Survey (PAUS) deep wide fields, which include the W1 and W3 fields from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) and the G09 field from the Kilo-Degree Survey (KiDS). Our analyses cover 51deg$^{2}$, in the photometric redshift (photo-$z$) range $0.1 < z_{\mathrm{b}} < 1$ and a magnitude limit $i_{\mathrm{AB}}<22$. The precise photo-$z$s and the luminosity coverage of PAUS enable robust IA measurements, which are key for setting informative priors for upcoming stage-IV surveys. For red galaxies, we detect an increase in IA amplitude with both luminosity and stellar mass, extending previous results towards fainter and less massive regimes. As a function of redshift, we observe strong IA signals at intermediate ($z_{\mathrm{b}}\sim0.55$) and high ($z_{\mathrm{b}}\sim0.75$) redshift bins. However, we find no significant trend of IA evolution with redshift after accounting for the varying luminosities across redshift bins, consistent with the literature. For blue galaxies, no significant IA signal is detected, with $A_{1}=0.68_{-0.51}^{+0.53}$ when splitting only by galaxy colour, yielding some of the tightest constraints to date for the blue population and constraining a regime of very faint and low-mass galaxies.

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arXiv2024

The PAU Survey: Enhancing photometric redshift estimation using DEEPz

We present photometric redshifts for 1 341 559 galaxies from the Physics of the Accelerating Universe Survey (PAUS) over 50.38 ${\rm deg}^{2}$ of sky to $i_{\rm AB}=23$. Redshift estimation is performed using DEEPz, a deep-learning photometric redshift code. We analyse the photometric redshift precision when varying the photometric and spectroscopic samples. Furthermore, we examine observational and instrumental effects on the precision of the photometric redshifts, and we compare photometric redshift measurements with those obtained using a template method-fitting BCNz2. Finally, we examine the use of photometric redshifts in the identification of close galaxy pairs. We find that the combination of samples from W1+W3 in the training of DEEPz significantly enhances the precision of photometric redshifts. This also occurs when we recover narrow band fluxes using broad bands measurements. We show that DEEPz determines the redshifts of galaxies in the prevailing spectroscopic catalogue used in the training of DEEPz with greater precision. For the faintest galaxies ($i_{\rm AB}=21-23$), we find that DEEPz improves over BCNz2 both in terms of the precision (20-50 per cent smaller scatter) and in returning a smaller outlier fraction in two of the wide fields. The catalogues were tested for the identification of close galaxy pairs, showing that DEEPz is effective for the identification of close galaxy pairs for samples with $i_{\rm AB} < 22.5$ and redshift $0.2 < z < 0.6$. In addition, identifying close galaxy pairs common between DEEPz and BCNz2 is a promising approach to improving the purity of the catalogues of these systems.

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arXiv2024

Euclid. I. Overview of the Euclid mission

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

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arXiv2024

The PAU Survey: a new constraint on galaxy formation models using the observed colour redshift relation

We use the GALFORM semi-analytical galaxy formation model implemented in the Planck Millennium N-body simulation to build a mock galaxy catalogue on an observer's past lightcone. The mass resolution of this N-body simulation is almost an order of magnitude better than in previous simulations used for this purpose, allowing us to probe fainter galaxies and hence build a more complete mock catalogue at low redshifts. The high time cadence of the simulation outputs allows us to make improved calculations of galaxy properties and positions in the mock. We test the predictions of the mock against the Physics of the Accelerating Universe Survey, a narrow band imaging survey with highly accurate and precise photometric redshifts, which probes the galaxy population over a lookback time of 8 billion years. We compare the model against the observed number counts, redshift distribution and evolution of the observed colours and find good agreement; these statistics avoid the need for model-dependent processing of the observations. The model produces red and blue populations that have similar median colours to the observations. However, the bimodality of galaxy colours in the model is stronger than in the observations. This bimodality is reduced on including a simple model for errors in the GALFORM photometry. We examine how the model predictions for the observed galaxy colours change when perturbing key model parameters. This exercise shows that the median colours and relative abundance of red and blue galaxies provide constraints on the strength of the feedback driven by supernovae used in the model.

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arXiv2023

The PAU Survey: Photometric redshift estimation in deep wide fields

We present photometric redshifts (photo-$z$) for the deep wide fields of the Physics of the Accelerating Universe Survey (PAUS), covering an area of $\sim$50 deg$^{2}$, for $\sim$1.8 million objects up to $i_{\textrm{AB}}<23$. The PAUS deep wide fields overlap with the W1 and W3 fields from CFHTLenS and the G09 field from KiDS/GAMA. Photo-$z$ are estimated using the 40 narrow bands (NB) of PAUS and the broad bands (BB) of CFHTLenS and KiDS. We compute the redshifts with the SED template-fitting code BCNZ, with a modification in the calibration technique of the zero-point between the observed and the modelled fluxes, that removes any dependence on spectroscopic redshift samples. We enhance the redshift accuracy by introducing an additional photo-$z$ estimate ($z_{\textrm{b}}$), obtained through the combination of the BCNZ and the BB-only photo-$z$. Comparing with spectroscopic redshifts estimates ($z_{\textrm{s}}$), we obtain a $\sigma_{68} \simeq 0.019$ for all galaxies with $i_{\textrm{AB}}<23$ and a typical bias $|z_{\textrm{b}}-z_{\textrm{s}}|$ smaller than 0.01. For $z_{\textrm{b}} \sim (0.10-0.75)$ we find $\sigma_{68} \simeq (0.003-0.02)$, this is a factor of $10-2$ higher accuracy than the corresponding BB-only results. We obtain similar performance when we split the samples into red (passive) and blue (active) galaxies. We validate the redshift probability $p(z)$ obtained by BCNZ and compare its performance with that of $z_{\textrm{b}}$. These photo-$z$ catalogues will facilitate important science cases, such as the study of galaxy clustering and intrinsic alignment at high redshifts ($z \lesssim 1$) and faint magnitudes.

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arXiv2021

Modelling emission lines in star forming galaxies

We present a new model to compute the luminosity of emission lines in star forming galaxies and apply this in the semi-analytical galaxy formation code GALFORM. The model combines a pre-computed grid of HII region models with an empirical determination of how the properties of HII regions depend on the macroscopic properties of galaxies based on observations of local galaxies. The new model gives a very good reproduction of the locus of star-forming galaxies on standard line ratio diagnostic diagrams. The new model shows evolution in the locus of star forming galaxies with redshift on this line ratio diagram, with a good match to the observed line ratios at $z=1.6$. The model galaxies at high redshift have gas densities and ionisation parameters that are predicted to be $\approx 2-3$ times higher than in local star forming galaxies, which is partly driven by the changing selection with redshift to mimic the observational selection. Our results suggest that the observed evolution in emission line ratios requires other HII region properties to evolve with redshift, such as the gas density, and cannot be reproduced by HII model grids that only allow the gas metallicity and ionisation parameter to vary.

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arXiv2020

Modelling the quenching of star formation activity from the evolution of the colour-magnitude relation in VIPERS

We study the evolution of the colour-magnitude relation for galaxies in the VIMOS Public Extragalactic Redshift Survey (VIPERS) by introducing the concept of the bright edge, and use this to derive constraints on the quenching of star formation activity in galaxies over the redshift range $0.5 < z < 1.1$. The bright-edge of the colour-magnitude diagram evolves with little dependence on galaxy colour, and therefore on the amount of star formation taking place in bright galaxies. We modelled this evolution with delayed exponential star formation histories (SFHs), to better understand the time-scale of the turn-off in star formation activity. We show that using SFHs without quenching, the transition from the blue cloud to the red sequence is too slow. This indicates that a scenario purely driven by the consumption of the gas inside each galaxy does not reproduce the observed evolution of the colour-magnitude bright edge. Among the quenching scenarios explored, the one that best matches the observations assumes that galaxies stop their star formation at a randomly selected time with a uniform distribution up to $2.5$ Gyr. We argue that quenching is required over a wide range of stellar masses. Qualitatively similar evolution of the bright edge is found in the predictions of a semi-analytical galaxy formation model, but quantitatively there are marked differences with the observations. This illustrates the utility of the bright edge as a test of galaxy formation models. The evolution changes and no longer matches the observed trend if feedback from heating by active galactic nuclei is turned off.

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arXiv2020

Are Lyα emitters segregated in protoclusters regions?

The presence of neutral hydrogen in the inter-stellar medium (ISM) and inter-galactic medium (IGM) induces radiative transfer (RT) effects on Lyα photons which affect the observability of Lyα emitters (LAEs). We use the GALFORM semi-analytic model of galaxy formation and evolution to analyse how these effects shape the spatial distribution of LAEs with respect to Hα emitters (HAEs) around high density regions at high redshift. We find that when a large sample of protoclusters is considered, HAEs showing also Lyα emission (HAEs+LAEs) populate the same regions as those that do not display the Lyα line at $z=2.2$. We compare against the protocluster USS1558-003, one of the most massive protoclusters located at $z=2.53$. Our results indicate that the strong depletion of HAEs+LAEs present in the high density regions of USS1558-003 may be due to cosmic variance. We find that at $z=2.2$ and $z=3.0$, RT of the ISM produces a strong decline ($30$-$50$ per cent) of the clustering amplitude of HAEs+LAEs with respect to HAEs towards the protoclusters centre. At $z=5.7$, given the early evolutionary state of protoclusters and galaxies, the clustering of HAEs+LAEs has a smaller variation ($10$-$20$ per cent) towards the protoclusters centre. Depending on the equivalent width and luminosity criteria of the emission-line galaxy sample, the IGM can have a mild or a null effect on galaxy properties and clustering in high density regions.

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arXiv2020

Do model emission line galaxies live in filaments at z~1?

Current and future cosmological surveys are targeting star-forming galaxies at $z\sim 1$ with nebular emission lines. We use a state-of-the-art semi-analytical model of galaxy formation and evolution to explore the large scale environment of star-forming emission line galaxies (ELGs). Model ELGs are selected such that they can be compared directly with the DEEP2, VVDS, eBOSS-SGC and DESI surveys. The large scale environment of the ELGs is classified using velocity-shear-tensor and tidal-tensor algorithms. Half of the model ELGs live in filaments and about a third in sheets. Model ELGs which reside in knots have the largest satellite fractions. We find that the shape of the mean halo occupation distribution of model ELGs varies widely for different large scale environments. To interpret our results, we also study fixed number density samples of ELGs and galaxies selected using simpler criteria, with single cuts in stellar mass, star formation rate and [OII] luminosity. The fixed number density ELG selection produces samples that are close to L[OII] and SFR selected samples for densities above $10^{-4.2}h^{3}{\rm Mpc}^{-3}$. ELGs with an extra cut in stellar mass applied to fix their number density, present differences in sheets and knots with respect to the other samples. ELGs, SFR and L[OII] selected samples with equal number density have similar large scale bias but their clustering below separations of $1h^{-1}$Mpc is different.

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arXiv2019

Euclid preparation III. Galaxy cluster detection in the wide photometric survey, performance and algorithm selection

Galaxy cluster counts in bins of mass and redshift have been shown to be a competitive probe to test cosmological models. This method requires an efficient blind detection of clusters from surveys with a well-known selection function and robust mass estimates. The Euclid wide survey will cover 15000 deg$^2$ of the sky in the optical and near-infrared bands, down to magnitude 24 in the $H$-band. The resulting data will make it possible to detect a large number of galaxy clusters spanning a wide-range of masses up to redshift $\sim 2$. This paper presents the final results of the Euclid Cluster Finder Challenge (CFC). The objective of these challenges was to select the cluster detection algorithms that best meet the requirements of the Euclid mission. The final CFC included six independent detection algorithms, based on different techniques, such as photometric redshift tomography, optimal filtering, hierarchical approach, wavelet and friend-of-friends algorithms. These algorithms were blindly applied to a mock galaxy catalog with representative Euclid-like properties. The relative performance of the algorithms was assessed by matching the resulting detections to known clusters in the simulations. Several matching procedures were tested, thus making it possible to estimate the associated systematic effects on completeness to $<3$%. All the tested algorithms are very competitive in terms of performance, with three of them reaching $>80$% completeness for a mean purity of 80% down to masses of $10^{14}$ M$_{\odot}$ and up to redshift $z=2$. Based on these results, two algorithms were selected to be implemented in the Euclid pipeline, the AMICO code, based on matched filtering, and the PZWav code, based on an adaptive wavelet approach. [abridged]

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arXiv2019

Galaxy formation in the Planck Millennium: the atomic hydrogen content of dark matter halos

We present recalibrations of the GALFORM semi-analytical model of galaxy formation in a new N-body simulation with the Planck cosmology. The Planck Millennium simulation uses more than 128 billion particles to resolve the matter distribution in a cube of $800$ Mpc on a side, which contains more than 77 million dark matter haloes with mass greater than $2.12 \times 10^{9} h^{-1} {\rm M_{\odot}}$ at the present day. Only minor changes to a very small number of model parameters are required in the recalibration. We present predictions for the atomic hydrogen content (HI) of dark matter halos, which is a key input into the calculation of the HI intensity mapping signal expected from the large-scale structure of the Universe. We find that the HI mass $-$ halo mass relation displays a clear break at the halo mass above which AGN heating suppresses gas cooling, $\approx 3 \times 10^{11} h^{-1} M_{\rm \odot}$. Below this halo mass, the HI content of haloes is dominated by the central galaxy; above this mass it is the combined HI content of satellites that prevails. We find that the HI mass - halo mass relation changes little with redshift up to $z=3$. The bias of HI sources shows a scale dependence that gets more pronounced with increasing redshift.

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arXiv2019

A new approach to finding galaxy groups using Markov Clustering

We present a proof of concept of a new galaxy group finder method, Markov graph Clustering (MCL; Van Dongen 2000) that naturally handles probabilistic linking criteria. We introduce a new figure of merit, the variation of information statistic (VI; Meila 2003), used to optimise the free parameter(s) of the MCL algorithm. We explain that the common Friends-of-Friends (FoF) method is a subset of MCL. We test MCL in real space on a realistic mock galaxy catalogue constructed from a N-body simulation using the GALFORM model. With a fixed linking length FoF produces the best group catalogues as quantified by the VI statistic. By making the linking length sensitive to the local galaxy density, the quality of the FoF and MCL group catalogues improve significantly, with MCL being preferred over FoF due to a smaller VI value. The MCL group catalogue recovers accurately the underlying halo multiplicity function at all multiplicities. MCL provides better and more consistent group purity and halo completeness values at all multiplicities than FoF. As MCL allows for probabilistic pairwise connections, it is a promising algorithm to find galaxy groups in photometric surveys.

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arXiv2018

Uncovering substructure with wavelets: proof of concept using Abell 2744

A recent comparison of the massive galaxy cluster Abell 2744 with the Millennium XXL (MXXL) N-body simulation has hinted at a tension between the observed substructure distribution and the predictions of LambdaCDM. Follow-up investigations indicated that this could be due to the contribution from the host halo and the subhalo finding algorithm used. To be independent of any subhalo finding algorithm, we therefore investigate the particle data of the MXXL simulation directly. We propose a new method to find substructures in 2D mass maps using a wavelet transform, which treats the simulation and observations equally. Using the same criteria to define a subhalo in observations and simulated data, we find three Abell 2744 analogues in the MXXL simulation. Thus the observations in Abell 2744 are in agreement with the predictions of LambdaCDM. We investigate the reasons for the discrepancy between the results obtained from the SUBFIND and full particle data analyses. We find that this is due to incompatible substructure definitions in observations and SUBFIND.

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arXiv2018

The PAU Survey: Spectral features and galaxy clustering using simulated narrow band photometry

We present a mock catalogue for the Physics of the Accelerating Universe Survey (PAUS) and use it to quantify the competitiveness of the narrow band imaging for measuring spectral features and galaxy clustering. The mock agrees with observed number count and redshift distribution data. We demonstrate the importance of including emission lines in the narrow band fluxes. We show that PAUCam has sufficient resolution to measure the strength of the 4000Å break to the nominal PAUS depth. We predict the evolution of a narrow band luminosity function and show how this can be affected by the OII emission line. We introduce new rest frame broad bands (UV and blue) that can be derived directly from the narrow band fluxes. We use these bands along with D4000 and redshift to define galaxy samples and provide predictions for galaxy clustering measurements. We show that systematic errors in the recovery of the projected clustering due to photometric redshift errors in PAUS are significantly smaller than the expected statistical errors. The galaxy clustering on two halo scales can be recovered quantatively without correction, and all qualitative trends seen in the one halo term are recovered. In this analysis mixing between samples reduces the expected contrast between the one halo clustering of red and blue galaxies and demonstrates the importance of a mock catalogue for interpreting galaxy clustering results. The mock catalogue is available on request at https://cosmohub.pic.es/home.

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arXiv2017

The host dark matter halos of [OII] emitters at 0.5< z< 1.5

Emission line galaxies (ELGs) are used in several ongoing and upcoming surveys (SDSS-IV/eBOSS, DESI) as tracers of the dark matter distribution. Using a new galaxy formation model, we explore the characteristics of [OII] emitters, which dominate optical ELG selections at $z\simeq 1$. Model [OII] emitters at $0.5<z<1.5$ are selected to mimic the DEEP2, VVDS, eBOSS and DESI surveys. The luminosity functions of model [OII] emitters are in reasonable agreement with observations. The selected [OII] emitters are hosted by haloes with $M_{\rm halo}\geq 10^{10.3}h^{-1}{\rm M}_{\odot}$, with ~90% of them being central star-forming galaxies. The predicted mean halo occupation distributions of [OII] emitters has a shape typical of that inferred for star-forming galaxies, with the contribution from central galaxies, $\langle N \rangle_{\left[OII\right]\, cen}$, being far from the canonical step function. The $\langle N \rangle_{\left[OII\right]\, cen}$ can be described as the sum of an asymmetric Gaussian for disks and a step function for spheroids, which plateaus below unity. The model [OII] emitters have a clustering bias close to unity, which is below the expectations for eBOSS and DESI ELGs. At $z\sim 1$, a comparison with observed g-band selected galaxy, which are expected to be dominated by [OII] emitters, indicates that our model produces too few [OII] emitters that are satellite galaxies. This suggests the need to revise our modelling of hot gas stripping in satellite galaxies.

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arXiv2017

Abell 2744: Too much substructure for Lambda CDM?

The massive substructures found in Abell 2744 by Jauzac et al. (2016) present a challenge to the cold dark matter paradigm due to their number and proximity to the cluster centre. We use one of the biggest N-body simulations, the Millennium XXL, to investigate the substructure in a large sample of massive dark matter haloes. A range of effects which influence the comparison with the observations is considered, extending the preliminary evaluation carried out by Jauzac et al. (2016). There are many tens of haloes in the simulation with a total mass comparable with or larger than that of Abell 2744. However, we find no haloes with a number and distribution of massive substructures (> 5 10^13 Msun) that is close to that inferred from the observations of Abell 2744. The application of extreme value statistics suggests that we would need a simulation of at least ten times the volume of the Millennium XXL to find a single dark matter halo with a similar internal structure to Abell 2744. Explaining the distribution of massive substructures in clusters is a new hurdle for hierarchical models to negotiate, which is not weakened by appeals to baryonic physics or uncertainty over the nature of the dark matter particle.

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