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Jon Loveday

Publications and source records attributed to Jon Loveday.

At least 19 recordsLinked to original sources

DINGO/GAMA /WAVES: HI-halo mass relation

We investigate the relation between neutral atomic hydrogen (HI) and dark matter halo mass (HIHM) using observations from the Deep Investigation of Neutral Gas Origins (DINGO) pilot survey 100h data, combined with spectroscopic data from the Galaxy and Mass Assembly (GAMA) survey and photometric data from the Wide Area VISTA Extragalactic Survey (WAVES) photometric catalog. We employ a combination of direct detections and spectral stacking to probe the HI content of halos across a wide mass range ($10^{10.5} \lesssim M_\mathrm{h}/M_\odot \lesssim 10^{14.5}$). By incorporating WAVES photometric members on top of the existing GAMA group catalog, we present a novel approach of extending stacking analyses beyond spectroscopic completeness limits, enabling recovery of satellite HI content otherwise missed. We find that the HIHM relation exhibits a double power-law form, with a turnover near $M_\mathrm{h} \sim 10^{11.2} \text{ M}_\odot$. Central galaxies dominate the halo HI budget below $M_\mathrm{h} \sim 6 \times 10^{12} \text{ M}_\odot$, while satellites dominate at higher halo masses. Including photometric members increases the measured HI content in halos above $10^{13} \text{ M}_\odot$ by a factor of 1.5-3, highlighting the importance of gas-rich satellites in the group and cluster regime. Comparison with previous group-stacking studies shows that low-surface brightness galaxies, and intra-group HI structures contribute only a minor fraction to the total HI mass in group and cluster halos, as the summed galaxy HI masses are consistent with the total halo HI content.

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Mapping dark matter and the emergence of large-scale structure

We discuss a potential survey to map dark matter and the emergence of large-scale structure to redshift z ~ 1.5 (baseline) or z~3.5 (with near-IR extension) using a massively multiplexed spectrograph on a 10m-class telescope, such as the proposed Widefield Spectroscopic Telescope.

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4MOST Cosmology Redshift Survey (CRS): Clustering Properties of CRS Bright Galaxy and Luminous Red Galaxy Target Catalogues

The 4-metre Multi-Object Spectroscopic Telescope Cosmology Redshift Survey (4MOST CRS) will obtain 5.4 million spectroscopic redshifts over ~5700 deg^2 to map large-scale structure and enable measurements of baryon acoustic oscillations, growth rates via redshift-space distortions, and cross-correlations with weak-lensing surveys. We validate the target selections, photometry, masking, systematics, and redshift distributions of the bright galaxy (BG) and luminous red galaxy (LRG) target catalogues selected from the Dark Energy Spectroscopic Instrument (DESI) Legacy Survey DR10.1 (LS) imaging. We measure the angular two-point correlation function, $w(\theta)$, test masking strategies, and recover redshift distributions via cross-correlation with DESI DR1 spectroscopy. For BGs, we adopt LS MASKBITS that veto bright stars and extended sources; for LRGs, we pair these with unblurred coadds of the WISE imaging (unWISE) W1 artefact masks. These choices suppress small-scale excess power without imprinting large-scale modes. A Limber-scaling test across BG $r$-band magnitude slices shows that, after applying the scaling, the $w(\theta)$ curves collapse to a near-common power law, demonstrating photometric uniformity with depth and consistency between the North and South Galactic Caps. Cross-correlations with DESI spectroscopy recover the expected N(z), albeit with high shot noise at the brightest magnitudes. For LRGs, angular clustering in photo-$z$ slices ($0.4\le z<1.0$) is consistent between the Dark Energy Camera Legacy Survey (DECaLS) and Dark Energy Survey (DES) footprints and is well described by an approximate power law once photo-$z$ smearing is included; halo-occupation fits are consistent with recent LRG studies. Together, these tests indicate that the masks and target selections yield reliable clustering statistics, supporting precision large-scale structure analyses with 4MOST CRS.

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The 4MOST-Cosmology Redshift Survey: Target Selection of Bright Galaxies and Luminous Red Galaxies

The Cosmology Redshift Survey of the 4-metre Multi-Object Spectroscopic Telescope (4MOST-CRS) will provide redshift measurements of galaxies and quasars over 5700{\degsq} in the southern hemisphere. As targets for the 4MOST-CRS, we present a selection of an $r<19.25$ magnitude limited sample of Bright Galaxies (BG) and a colour selected sample of Luminous Red Galaxies (LRG) based on DESI Legacy Survey DR10.1 photometric data, in the redshift ranges $0.1<z<0.5$ and $0.4<z<1$, respectively. These samples are selected using the $g$, $r$, $z$, and $W1$ (from unWISE) photometric bands. For BGs, the star--galaxy separation is performed based on Gaia and Tycho-2 star catalogues. Following 4MOST requirements, the target densities of BGs and LRGs are 250{\mdegsq} and 400{\mdegsq}, respectively. We quantified the stellar contamination to be $<2-4\%$ for both galaxy samples using data from the first DESI data release. Using angular clustering, we show that both samples are robust against imaging systematics, confirming a low stellar contamination. Finally, we provide forecasts of the baryonic acoustic oscillation (BAO) and growth of structure ($\sigma_8$) measurements from the 4MOST-CRS alone and in combination with DESI. From the 4MOST-CRS, we expect 3\% and 25\% precision on BAO and $\sigma_8$ measurements, respectively. Combining 4MOST-CRS with DESI improves the constraints from DESI alone by 12$\%$ in the 0.4 < z < 0.8 redshift range, leading to the most stringent constraints on BAO measurements from spectroscopic galaxy clustering.

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Wide Area VISTA Extra-galactic Survey (WAVES): Unsupervised star-galaxy separation on the WAVES-Wide photometric input catalogue using UMAP and ${\rm{\scriptsize HDBSCAN}}$

Star-galaxy separation is a crucial step in creating target catalogues for extragalactic spectroscopic surveys. A classifier biased towards inclusivity risks including spurious stars, wasting fibre hours, while a more conservative classifier might overlook galaxies, compromising completeness and hence survey objectives. To avoid bias introduced by a training set in supervised methods, we employ an unsupervised machine learning approach. Using photometry from the Wide Area VISTA Extragalactic Survey (WAVES)-Wide catalogue comprising 9-band $u-K_s$ data, we create a feature space with colours, fluxes, and apparent size information extracted by ${\rm P{\scriptsize RO} F{\scriptsize OUND}}$. We apply the non-linear dimensionality reduction method UMAP (Uniform Manifold Approximation and Projection) combined with the classifier ${\rm{\scriptsize HDBSCAN}}$ to classify stars and galaxies. Our method is verified against a baseline colour and morphological method using a truth catalogue from Gaia, SDSS, GAMA, and DESI. We correctly identify 99.72% of galaxies within the AB magnitude limit of $Z = 21.2$, with an F1 score of $0.9971 \pm 0.0018$ across the entire ground truth sample, compared to $0.9879 \pm 0.0088$ from the baseline method. Our method's higher purity ($0.9967 \pm 0.0021$) compared to the baseline ($0.9795 \pm 0.0172$) increases efficiency, identifying 11% fewer galaxy or ambiguous sources, saving approximately 70,000 fibre hours on the 4MOST instrument. We achieve reliable classification statistics for challenging sources including quasars, compact galaxies, and low surface brightness galaxies, retrieving 95.1%, 84.6%, and 99.5% of them respectively. Angular clustering analysis validates our classifications, showing consistency with expected galaxy clustering, regardless of the baseline classification.

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Deep Investigation of Neutral Gas Origins (DINGO): HI stacking experiments with early science data

We present early science results from Deep Investigation of Neutral Gas Origins (DINGO), an HI survey using the Australian Square Kilometre Array Pathfinder (ASKAP). Using ASKAP sub-arrays available during its commissioning phase, DINGO early science data were taken over $\sim$ 60 deg$^{2}$ of the Galaxy And Mass Assembly (GAMA) 23 h region with 35.5 hr integration time. We make direct detections of six known and one new sources at $z < 0.01$. Using HI spectral stacking, we investigate the HI gas content of galaxies at $0.04 < z< 0.09$ for different galaxy colours. The results show that galaxy morphology based on optical colour is strongly linked to HI gas properties. To examine environmental impacts on the HI gas content of galaxies, three sub-samples are made based on the GAMA group catalogue. The average HI mass of group central galaxies is larger than those of satellite and isolated galaxies, but with a lower HI gas fraction. We derive a variety of HI scaling relations for physical properties of our sample, including stellar mass, stellar mass surface density, $NUV-r$ colour, specific star formation rate, and halo mass. We find that the derived HI scaling relations are comparable to other published results, with consistent trends also observed to $\sim$0.5 dex lower limits in stellar mass and stellar surface density. The cosmic HI densities derived from our data are consistent with other published values at similar redshifts. DINGO early science highlights the power of HI spectral stacking techniques with ASKAP.

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Exploring the effect of baryons on the radial distribution of satellite galaxies with GAMA and IllustrisTNG

We explore the radial distribution of satellite galaxies in groups in the Galaxy and Mass Assembly (GAMA) survey and the IllustrisTNG simulations. Considering groups with masses $12.0 \leq \log_{10} (\mathcal{M}_h / h^{-1} \mathrm{M}_{\odot}) < 14.8$ at $z<0.267$, we find a good agreement between GAMA and a sample of TNG300 groups and galaxies designed to match the GAMA selection. Both display a flat profile in the centre of groups, followed by a decline that becomes steeper towards the group edge, and normalised profiles show no dependence on group mass. Using matched satellites from TNG and dark matter-only TNG-Dark runs we investigate the effect of baryons on satellite radial location. At $z=0$, we find that the matched subhaloes from the TNG-Dark runs display a much flatter radial profile: namely, satellites selected above a minimum stellar mass exhibit both smaller halo-centric distances and longer survival times in the full-physics simulations compared to their dark-matter only analogues. We then divide the TNG satellites into those which possess TNG-Dark counterparts and those which do not, and develop models for the radial positions of each. We find the satellites with TNG-Dark counterparts are displaced towards the halo centre in the full-physics simulations, and this difference has a power-law behaviour with radius. For the `orphan' galaxies without TNG-Dark counterparts, we consider the shape of their radial distribution and provide a model for their motion over time, which can be used to improve the treatment of satellite galaxies in semi-analytic and semi-empirical models of galaxy formation.

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Galaxy And Mass Assembly (GAMA): Data Release 4 and the z < 0.1 total and z < 0.08 morphological galaxy stellar mass functions

In Galaxy And Mass Assembly Data Release 4 (GAMA DR4), we make available our full spectroscopic redshift sample. This includes 248682 galaxy spectra, and, in combination with earlier surveys, results in 330542 redshifts across five sky regions covering ~250deg^2. The redshift density, is the highest available over such a sustained area, has exceptionally high completeness (95 per cent to r_KIDS=19.65mag), and is well suited for the study of galaxy mergers, galaxy groups, and the low redshift (z<0.25) galaxy population. DR4 includes 32 value-added tables or Data Management Units (DMUs) that provide a number of measured and derived data products including GALEX, ESO KiDS, ESO VIKING, WISE and Herschel Space Observatory imaging. Within this release, we provide visual morphologies for 15330 galaxies to z<0.08, photometric redshift estimates for all 18million objects to r_KIDS~25mag, and stellar velocity dispersions for 111830 galaxies. We conclude by deriving the total galaxy stellar mass function (GSMF) and its sub-division by morphological class (elliptical, compact-bulge and disc, diffuse-bulge and disc, and disc only). This extends our previous measurement of the total GSMF down to 10^6.75 M_sol h^-2_70 and we find a total stellar mass density of rho_*=(2.97+/-0.04)x10^8 M_sol h_70 Mpc^-3 or Omega_*=(2.17+/-0.03)x10^-3 h^-1_70. We conclude that at z<0.1, the Universe has converted 4.9+/-0.1 per cent of the baryonic mass implied by Big Bang Nucleosynthesis into stars that are gravitationally bound within the galaxy population.

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An empirical measurement of the Halo Mass Function from the combination of GAMA DR4, SDSS DR12, and REFLEX II data

We construct the halo mass function (HMF) from the GAMA galaxy group catalogue over the mass range 10^12.7M_sol to 10^15.5M_sol, and find good agreement with the expectation from LambdaCDM. In comparison to previous studies, this result extends the mass range over which the HMF has now been measured over by an order of magnitude. We combine the GAMA DR4 HMF with similar data from the SDSS DR12 and REFLEX II surveys, and fit a four-parameter Murray-Robotham-Power (MRP) function, valid at z~0.1, yielding: a density normalisation of: log10 (phi Mpc^3)=-3.96[+0.55,-0.82], a high mass turn-over of: log10(M/M_sol)=14.13[+0.43,-0.40], a low mass power law slope of: alpha=-1.68[+0.21,-0.24] , and a high mass softening parameter of: beta= 0.63[+0.25,-0.11]. If we fold in the constraint on Omega_M from Planck 2018 Cosmology, we are able to reduce these uncertainties further, but this relies on the assumption that the power-law trend can be extrapolated from 10^12.7M_sol to zero mass. Throughout, we highlight the effort needed to improve on our HMF measurement: improved halo mass estimates that do not rely on calibration to simulations; reduced halo mass uncertainties needed to mitigate the strong Eddington Bias that arises from the steepness of the HMF low mass slope; and deeper wider area spectroscopic surveys. To our halo mass limit of 10^12.7 M_sol, we are directly resolving (`seeing') 41+/-5 per cent of the total mass density, i.e. Omega_[M>12.7]=0.128+/-0.016, opening the door for the direct construction of 3D dark matter mass maps at Mpc resolution.

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The galaxy power spectrum on the lightcone: deep, wide-angle redshift surveys and the turnover scale

We derive expressions for the survey-window convolved galaxy power spectrum in real space for a full sky and deep redshift survey, but taking into account the geometrical lightcone effect. We investigate the impact of using the standard mean redshift approximation as a function of survey depth, and show that this assumption can lead to both an overall amplitude suppression and scale-dependent error when compared to the `true' spectrum. However, we also show that by using a carefully chosen `effective fixed-time', one can find a range of scales where the approximation to the full model is highly accurate, but only on a more restricted set of scales. We validate the theory by constructing dark matter and galaxy lightcone mock surveys from a large $N$-body simulation with a high cadence of snapshots. We do this by solving the light cone equation exactly for every particle, where the particle worldlines are obtained in a piecewise fashion with cubic interpolation between neighbouring snapshots. We find excellent agreement between our measurements and the theory ($\sim \pm 5\%$) over scales $(0.004 h{\rm Mpc}^{-1} \leq k \leq 0.54 h {\rm Mpc}^{-1})$ and for a variety of magnitude limits. Finally, we look to see how accurately we can measure the turnover scale of the galaxy power spectrum $k_0$. Using the lightcone mocks we show that one can detect the turnover scale with a probability $P \geq 95\%$ in an all-sky catalogue limited to an apparent magnitude $m_{\rm lim}\sim 21$. We also show that the detection significance would remain high for surveys with $m_{\rm lim}\sim22$ and $20\%$ sky coverage.

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The Causes of the Red Sequence, the Blue Cloud, the Green Valley and the Green Mountain

The galaxies found in optical surveys fall in two distinct regions of a diagram of optical colour versus absolute magnitude: the red sequence and the blue cloud with the green valley in between. We show that the galaxies found in a submillimetre survey have almost the opposite distribution in this diagram, forming a `green mountain'. We show that these distinctive distributions follow naturally from a single, continuous, curved Galaxy Sequence in a diagram of specific star-formation rate versus stellar mass without there being the need for a separate star-forming galaxy Main Sequence and region of passive galaxies. The cause of the red sequence and the blue cloud is the geometric mapping between stellar mass/specific star-formation rate and absolute magnitude/colour, which distorts a continuous Galaxy Sequence in the diagram of intrinsic properties into a bimodal distribution in the diagram of observed properties. The cause of the green mountain is Malmquist bias in the submillimetre waveband, with submillimetre surveys tending to select galaxies on the curve of the Galaxy Sequence, which have the highest ratios of submillimetre-to-optical luminosity. This effect, working in reverse, causes galaxies on the curve of the Galaxy Sequence to be underrepresented in optical samples, deepening the green valley. The green valley is therefore not evidence (1) for there being two distinct populations of galaxies, (2) for galaxies in this region evolving more quickly than galaxies in the blue cloud and the red sequence, (c) for rapid quenching processes in the galaxy population.

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Galaxy And Mass Assembly: Automatic Morphological Classification of Galaxies Using Statistical Learning

We apply four statistical learning methods to a sample of $7941$ galaxies ($z<0.06$) from the Galaxy and Mass Assembly (GAMA) survey to test the feasibility of using automated algorithms to classify galaxies. Using $10$ features measured for each galaxy (sizes, colours, shape parameters \& stellar mass) we apply the techniques of Support Vector Machines (SVM), Classification Trees (CT), Classification Trees with Random Forest (CTRF) and Neural Networks (NN), returning True Prediction Ratios (TPRs) of $75.8\%$, $69.0\%$, $76.2\%$ and $76.0\%$ respectively. Those occasions whereby all four algorithms agree with each other yet disagree with the visual classification (`unanimous disagreement') serves as a potential indicator of human error in classification, occurring in $\sim9\%$ of ellipticals, $\sim9\%$ of Little Blue Spheroids, $\sim14\%$ of early-type spirals, $\sim21\%$ of intermediate-type spirals and $\sim4\%$ of late-type spirals \& irregulars. We observe that the choice of parameters rather than that of algorithms is more crucial in determining classification accuracy. Due to its simplicity in formulation and implementation, we recommend the CTRF algorithm for classifying future galaxy datasets. Adopting the CTRF algorithm, the TPRs of the 5 galaxy types are : E, $70.1\%$; LBS, $75.6\%$; S0-Sa, $63.6\%$; Sab-Scd, $56.4\%$ and Sd-Irr, $88.9\%$. Further, we train a binary classifier using this CTRF algorithm that divides galaxies into spheroid-dominated (E, LBS \& S0-Sa) and disk-dominated (Sab-Scd \& Sd-Irr), achieving an overall accuracy of $89.8\%$. This translates into an accuracy of $84.9\%$ for spheroid-dominated systems and $92.5\%$ for disk-dominated systems.

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The New Galaxy Evolution Paradigm Revealed by the Herschel Surveys

The Herschel Space Observatory has revealed a very different galaxyscape from that shown by optical surveys which presents a challenge for galaxy-evolution models. The Herschel surveys reveal (1) that there was rapid galaxy evolution in the very recent past and (2) that galaxies lie on a a single Galaxy Sequence (GS) rather than a star-forming `main sequence' and a separate region of `passive' or `red-and-dead' galaxies. The form of the GS is now clearer because far-infrared surveys such as the Herschel ATLAS pick up a population of optically-red star-forming galaxies that would have been classified as passive using most optical criteria. The space-density of this population is at least as high as the traditional star-forming population. By stacking spectra of H-ATLAS galaxies over the redshift range 0.001 < z < 0.4, we show that the galaxies responsible for the rapid low-redshift evolution have high stellar masses, high star-formation rates but, even several billion years in the past, old stellar populations - they are thus likely to be relatively recent ancestors of early-type galaxies in the Universe today. The form of the GS is inconsistent with rapid quenching models and neither the analytic bathtub model nor the hydrodynamical EAGLE simulation can reproduce the rapid cosmic evolution. We propose a new gentler model of galaxy evolution that can explain the new Herschel results and other key properties of the galaxy population.

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GAMA/G10-COSMOS/3D-HST: The 0<z<5 cosmic star-formation history, stellar- and dust-mass densities

We use the energy-balance code MAGPHYS to determine stellar and dust masses, and dust corrected star-formation rates for over 200,000 GAMA galaxies, 170,000 G10-COSMOS galaxies and 200,000 3D-HST galaxies. Our values agree well with previously reported measurements and constitute a representative and homogeneous dataset spanning a broad range in stellar mass (10^8---10^12 Msol), dust mass (10^6---10^9 Msol), and star-formation rates (0.01---100 Msol per yr), and over a broad redshift range (0.0 < z < 5.0). We combine these data to measure the cosmic star-formation history (CSFH), the stellar-mass density (SMD), and the dust-mass density (DMD) over a 12 Gyr timeline. The data mostly agree with previous estimates, where they exist, and provide a quasi-homogeneous dataset using consistent mass and star-formation estimators with consistent underlying assumptions over the full time range. As a consequence our formal errors are significantly reduced when compared to the historic literature. Integrating our cosmic star-formation history we precisely reproduce the stellar-mass density with an ISM replenishment factor of 0.50 +/- 0.07, consistent with our choice of Chabrier IMF plus some modest amount of stripped stellar mass. Exploring the cosmic dust density evolution, we find a gradual increase in dust density with lookback time. We build a simple phenomenological model from the CSFH to account for the dust mass evolution, and infer two key conclusions: (1) For every unit of stellar mass which is formed 0.0065---0.004 units of dust mass is also formed; (2) Over the history of the Universe approximately 90 to 95 per cent of all dust formed has been destroyed and/or ejected.

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Large Synoptic Survey Telescope Galaxies Science Roadmap

The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of galaxies, dark matter, and black holes over cosmic time. The LSST Galaxies Science Collaboration has identified a host of preparatory research tasks required to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. This Galaxies Science Roadmap provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The Galaxies Science Roadmap will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era.

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The stellar-to-halo mass relation of GAMA galaxies from 100 square degrees of KiDS weak lensing data

We study the stellar-to-halo mass relation of central galaxies in the range 9.7 5x10^10 h^-2 M_sun, the stellar mass increases with halo mass as ~M_h^0.25. The ratio of dark matter to stellar mass has a minimum at a halo mass of 8x10^11 h^-1 M_sun with a value of M_h/M_*=56_-10^+16 [h]. We also use the GAMA group catalogue to select centrals and satellites in groups with five or more members, which trace regions in space where the local matter density is higher than average, and determine for the first time the stellar-to-halo mass relation in these denser environments. We find no significant differences compared to the relation from the full sample, which suggests that the stellar-to-halo mass relation does not vary strongly with local density. Furthermore, we find that the stellar-to-halo mass relation of central galaxies can also be obtained by modelling the lensing signal and stellar mass function of satellite galaxies only, which shows that the assumptions to model the satellite contribution in the halo model do not significantly bias the stellar-to-halo mass relation. Finally, we show that the combination of weak lensing with the stellar mass function can be used to test the purity of group catalogues.

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First test of Verlinde's theory of Emergent Gravity using Weak Gravitational Lensing measurements

Verlinde (2016) proposed that the observed excess gravity in galaxies and clusters is the consequence of Emergent Gravity (EG). In this theory the standard gravitational laws are modified on galactic and larger scales due to the displacement of dark energy by baryonic matter. EG gives an estimate of the excess gravity (described as an apparent dark matter density) in terms of the baryonic mass distribution and the Hubble parameter. In this work we present the first test of EG using weak gravitational lensing, within the regime of validity of the current model. Although there is no direct description of lensing and cosmology in EG yet, we can make a reasonable estimate of the expected lensing signal of low redshift galaxies by assuming a background LambdaCDM cosmology. We measure the (apparent) average surface mass density profiles of 33,613 isolated central galaxies, and compare them to those predicted by EG based on the galaxies' baryonic masses. To this end we employ the ~180 square degrees overlap of the Kilo-Degree Survey (KiDS) with the spectroscopic Galaxy And Mass Assembly (GAMA) survey. We find that the prediction from EG, despite requiring no free parameters, is in good agreement with the observed galaxy-galaxy lensing profiles in four different stellar mass bins. Although this performance is remarkable, this study is only a first step. Further advancements on both the theoretical framework and observational tests of EG are needed before it can be considered a fully developed and solidly tested theory.

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Galaxy-Galaxy Lensing in EAGLE: comparison with data from 180 square degrees of the KiDS and GAMA surveys

We present predictions for the galaxy-galaxy lensing profile from the EAGLE hydrodynamical cosmological simulation at redshift z=0.18, in the spatial range 0.02 < R/(Mpc/h) < 2, and for five logarithmically equi-spaced stellar mass bins in the range 10.3 < $\log_{10}$(Mstar/ $M_{\odot}$) < 11.8. We compare these excess surface density profiles to the observed signal from background galaxies imaged by the Kilo Degree Survey around spectroscopically confirmed foreground galaxies from the GAMA survey. Exploiting the GAMA galaxy group catalogue, the profiles of central and satellite galaxies are computed separately for groups with at least five members to minimise contamination. EAGLE predictions are in broad agreement with the observed profiles for both central and satellite galaxies, although the signal is underestimated at R$\approx$0.5-2 Mpc/h for the highest stellar mass bins. When central and satellite galaxies are considered simultaneously, agreement is found only when the selection function of lens galaxies is taken into account in detail. Specifically, in the case of GAMA galaxies, it is crucial to account for the variation of the fraction of satellite galaxies in bins of stellar mass induced by the flux-limited nature of the survey. We report the inferred stellar-to-halo mass relation and we find good agreement with recent published results. We note how the precision of the galaxy-galaxy lensing profiles in the simulation holds the potential to constrain fine-grained aspects of the galaxy-dark matter connection.

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