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Alfonso Aragón-Salamanca

Publications and source records attributed to Alfonso Aragón-Salamanca.

At least 19 recordsLinked to original sources

Searching for signatures of fuzzy dark matter in cosmic filament profiles

Current observations reveal persistent tensions with the standard cold dark matter paradigm, raising the question of whether these can be explained by baryonic physics alone or require alternative dark matter models. One such alternative is fuzzy (or wave) dark matter, consisting of ultralight particles with mass $m \sim 10^{-22}$ eV and de Broglie wavelengths on kpc to Mpc scales, which may give rise to large--scale interference patterns in non-linear structures around the cosmic web, such as filaments and clusters. In this work, we search for possible signatures of these interference fringes by investigating periodicities in the distribution of galaxies around cosmic web filaments. To demonstrate our methodology, we compare the filament profiles to a simple model that includes a periodic component of the form $A\cos(2πd/ λ)$, where $A$ is the maximum density contrast (amplitude) of the periodic component, with wavelength $λ=λ_0 \cosθ$ for some face-on wavelength $λ_0$ inclined at an angle $θ$ to the line of sight. Exploiting the large Sloan Digital Sky Survey (SDSS) Main Galaxy Sample, we analyse a sample of 4,394 filaments from the Tempel et al. filament catalogue, each containing at least 10 member galaxies. We find a vast portion of the parameter space is consistent with the observations at the $2σ$ level, including all models with $A = 0$ (no periodicity). We identify a region of the parameter space in tension with the observations, allowing us to exclude values of $A > 0.16 λ_0 + 0.18$ for $0.2\,\text{Mpc}\,\lesssim λ_0 \lesssim 2\,\text{Mpc}$ at the $3σ$ level, demonstrating the ability to test models of filament dark matter structure using this methodology.

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Identifying group galaxies merging with massive clusters using machine learning

The environment plays a critical role in galaxy evolution, with galaxy clusters and their infall regions offering diverse conditions that shape galaxies before they enter the dense cluster core, a process known as ``pre-processing''. However, identifying environmental substructures, particularly galaxy groups in these transitional zones, remains challenging due to projection effects and ``fingers-of-god'' distortions. In this work, we present a supervised machine learning framework for classifying galaxies into three environmental categories: main cluster, group, and neither, using observable galaxy properties such as positions, line-of-sight velocities, and stellar mass. The model is trained on mock observations derived from cosmological simulations designed to replicate survey conditions and achieves an overall accuracy and class-size-weighted precision of 81%. The neither and main cluster populations are reliably recovered, whereas group galaxies remain the most challenging to identify, achieving 30% completeness and 76% purity. Within $1\times R_{200}$, classification performance is suppressed, but it improves beyond this radius, reaching 40% completeness and 80% purity. Resampling and thresholding strategies allow the model to be tuned toward either higher purity or higher completeness; in this study, we adopt first-past-the-post thresholding to emphasise purity. Model performance is consistent across cluster masses and dynamical states, and it outperforms both Friends-of-Friends and Gaussian Mixture Modelling. This flexibility makes it well suited to upcoming spectroscopic surveys of cluster infall regions, providing a robust statistical tool for disentangling environmental influences on galaxy evolution.

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The effect of cosmic web filaments on galaxy evolution

Galaxy properties are known to be affected by their environment. This is well established for the extremes of the density scales, between the high-density cluster environment and the low-density field. It is however not fully understood how the intermediate-density regime of cosmic web filaments affects galaxy evolution. We investigate this environmental effect using a mass complete sample of 23,441 galaxies in the Sloan Digital Sky Survey DR8 Main Galaxy Sample (${M}_{\text{Stellar}} > 10^{9.91} \text{M}_{\odot}$). We define 6 environments, probing different density regimes and representing unique stages in the structure formation process, comparing the differences in star formation activity and morphology between them. We find that galaxies in filaments tend to be less star forming and favour more early-type morphologies than those in the field. These differences persist when considering stellar mass-matched samples, suggesting that this is a consequence of the environment. We further investigate whether these trends are a result of the large scale or local environment through constructing samples matched both in stellar mass and local galaxy density. We find that when also matching in local galaxy density, the differences observed between the filament and field population vanishes, concluding that the environmental effect of filaments can be entirely parameterised by a local galaxy density index. We find that differences can still be seen in comparisons with the interiors of clusters, suggesting these are unique environments which can impart additional physical processes not characterised by local galaxy density.

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The separate effect of halo mass and stellar mass on the evolution of massive disk galaxies

We analyse a sample of massive disk galaxies selected from the SDSS-IV/MaNGA survey to investigate how the evolution of these galaxies depends on their stellar and halo masses. We applied a semi-analytic spectral fitting approach to the data from different regions in the galaxies to derive several of their key physical properties. From the best-fit model results, together with direct observables such as morphology, colour, and the Mgb/$\langle$Fe$\rangle$ index ratio measured within $1 R_{\rm e}$, we find that for central galaxies both their stellar and halo masses have a significant influence in their evolution. For a given halo mass, galaxies with higher stellar mass accumulate their stellar mass and become chemically enriched earlier than those with smaller stellar mass. Furthermore, at a given stellar mass, galaxies living in more massive halos have longer star-formation timescales and are delayed in becoming chemically enriched. In contrast, the evolution of massive satellite galaxies is mostly determined by their stellar mass. The results indicate that both the assembled halo mass and the halo assembly history impact the evolution of central galaxies. Our spatially resolved analysis indicates that only the galaxy properties in the central region ($0.0$--$0.5 R_{\rm e}$) show the dependencies described above. This fact supports a halo-driven formation scenario since the galaxies' central regions are more likely to contain old stars formed along with the halo itself, keeping a memory of the halo formation process.

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The wide-field, multiplexed, spectroscopic facility WEAVE: Survey design, overview, and simulated implementation

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z<0.5$ cluster galaxies; (vi) survey stellar populations and kinematics in $\sim25\,000$ field galaxies at $0.3\lesssim z \lesssim 0.7$; (vii) study the cosmic evolution of accretion and star formation using $>1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.

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Where have all the low-metallicity galaxies gone? Tracing evolution in the mass--metallicity plane since a redshift of 0.7

Even over relatively recent epochs, galaxies have evolved significantly in their location in the mass-metallicity plane, which must be telling us something about the latter stages of galaxy evolution. In this paper, we analyse data from the LEGA-C survey using semi-analytic spectral and photometric fitting to determine these galaxies' evolution up to their observed epoch at $z \sim 0.7$. We confirm that, at $z \sim 0.7$, many objects already lie on the present-day mass-metallicity relation, but with a significant tail of high-mass low-metallicity galaxies that is not seen in the nearby Universe. Similar modelling of the evolution of galaxies in the nearby MaNGA survey allows us to reconstruct their properties at $z \sim 0.7$. Once selection criteria similar to those of LEGA-C are applied, we reassuringly find that the MaNGA galaxies populate the mass-metallicity plane in the same way at $z \sim 0.7$. Matching the LEGA-C sample to their mass-metallicity "twins" in MaNGA at this redshift, we can explore the likely subsequent evolution of individual LEGA-C galaxies. Galaxies already on the present-day mass--metallicity relation form few more stars and their disks fade, so they become smaller and more bulge-like. By contrast, the high-mass low-metallicity galaxies grow their disks through late star formation, and evolve rapidly to higher metallicities due to a cut-off in their wind-driven mass loss. There are significant indications that this late cut-off is associated with the belated end of strong AGN activity in these objects.

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The localization of galaxy groups in close proximity to galaxy clusters using cosmic web nodes

We investigate the efficacy of using the cosmic web nodes identified by the DisPerSE topological filament finder to systematically identify galaxy groups in the infall regions around massive clusters. The large random motions and infall velocities of galaxies in the regions around clusters complicate the detection and characterisation of substructures through normal group-finding algorithms. Yet understanding the co-location of galaxies within filaments and/or groups is a key part of understanding the role of environment on galaxy evolution, particularly in light of next-generation wide-field spectroscopic surveys. Here we use simulated massive clusters from TheThreeHundred collaboration and compare the derived group catalogues, (haloes with $σ_{v} > 300 h^{-1}$ km/s) with the critical points from DisPerSE, ran on haloes with more than 100 particles. We find that in 3D, 56\% of DisPerSE nodes are correctly identified as groups (purity) while 68\% of groups are identified as nodes (completeness). The fraction of matches increases with group mass and with distance from the host cluster centre. This rises to a completeness of 100\% for the most massive galaxy groups ($M>10^{14}$ M$_{\odot}$) in 3D, or 63\% when considering the projected 2D galaxy distribution. When a perfect match occurs between a cosmic web node and a galaxy group, the DisPerSE node density ($δ$) serves as an estimate of the group's mass, albeit with significant scatter. We conclude that the use of a cosmic filament finder shows promise as a useful and straightforward observational tool for disentangling substructure within the infall regions of massive clusters.

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The probability of identifying the cosmic web environment of galaxies around clusters motivated by the Weave Wide Field Cluster Survey

Upcoming wide-field spectroscopic surveys will observe galaxies in a range of cosmic web environments in and around galaxy clusters. In this paper, we test and quantify how successfully we will be able to identify the environment of individual galaxies in the vicinity of massive galaxy clusters, reaching out to $\sim5R_{200}$ into the clusters' infall region. We focus on the WEAVE Wide Field Cluster Survey (WWFCS), but the methods we develop can be easily generalised to any similar spectroscopic survey. Using numerical simulations of a large sample of massive galaxy clusters from \textsc{TheThreeHundred} project, we produce mock observations that take into account the selection effects and observational constraints imposed by the WWFCS. We then compare the `true' environment of each galaxy derived from the simulations (cluster core, filament, and neither core nor filament, {``NCF''}) with the one derived from the observational data, where only galaxy sky positions and spectroscopic redshifts will be available. We find that, while cluster core galaxy samples can be built with a high level of completeness and moderate contamination, the filament and NCF galaxy samples will be significantly contaminated and incomplete due to projection effects exacerbated by the galaxies' peculiar velocities. We conclude that, in the infall regions surrounding massive galaxy clusters, associating galaxies with the correct cosmic web environment is highly uncertain. However, with large enough spectroscopic samples like the ones the WWFCS will provide (thousands of galaxies per cluster, {out to $5R_{200}$}), and the correct statistical treatment that takes into account the probabilities we provide here, we expect we will be able to extract robust and well-quantified conclusions on the relationship between galaxy properties and their environment.

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Are Milky-Way-like galaxies like the Milky Way? A view from SDSS-IV/MaNGA

In this paper, we place the Milky Way (MW) in the context of similar-looking galaxies in terms of their star-formation and chemical evolution histories. We select a sample of 138 Milky-Way analogues (MWAs) from the SDSS-IV/MaNGA survey based on their masses, Hubble types, and bulge-to-total ratios. To compare their chemical properties to the detailed spatially-resolved information available for the MW, we use a semi-analytic spectral fitting approach, which fits a self-consistent chemical-evolution and star-formation model directly to the MaNGA spectra. We model the galaxies' inner and outer regions assuming that some of the material lost in stellar winds falls inwards. We also incorporate chemical enrichment from type II and Ia supernovae to follow the alpha-element abundance at different metallicities and locations. We find some MWAs where the stellar properties closely reproduce the distribution of age, metallicity, and alpha enhancement at both small and large radii in the MW. In these systems, the match is driven by the longer timescale for star formation in the outer parts, and the inflow of enriched material to the central parts. However, other MWAs have very different histories. These divide into two categories: self-similar galaxies where the inner and outer parts evolve identically; and centrally-quenched galaxies where there is very little evidence of late-time central star formation driven by material accreted from the outer regions. We find that, although selected to be comparable, there are subtle morphological differences between galaxies in these different classes, and that the centrally-quenched galaxies formed their stars systematically earlier.

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The impact of environment on the lives of disk galaxies as revealed by SDSS-IV MaNGA

Environment has long been known to have significant impact on the evolution of galaxies, but here we seek to quantify the subtler differences that might be found in disk galaxies, depending on whether they are isolated, the most massive galaxy in a group (centrals), or a lesser member (satellites). The MaNGA survey allows us to define a large mass-matched sample of 574 galaxies with high-quality integrated spectra in each category. Initial examination of their spectral indices indicates significant differences, particularly in low-mass galaxies. Semi-analytic spectral fitting of a full chemical evolution model to these spectra confirms these differences, with low-mass satellites having a shorter period of star formation and chemical enrichment typical of a closed box, while central galaxies have more extended histories, with evidence of on-going gas accretion over their lifetimes. The derived parameters for gas infall timescale and wind strength suggest that low-mass satellite galaxies have their hot halos of gas effectively removed, while central galaxies retain a larger fraction of gas than isolated galaxies due to the deeper group potential well in which they sit. S0 galaxies form a distinct subset within the sample, particularly at higher masses, but do not bias the inferred lower-mass environmental impact significantly. The consistent picture that emerges underlines the wealth of archaeological information that can be extracted from high-quality spectral data using techniques like semi-analytic spectral fitting.

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Forecasting the success of the WEAVE Wide-Field Cluster Survey on the extraction of the cosmic web filaments around galaxy clusters

Next-generation wide-field spectroscopic surveys will observe the infall regions around large numbers of galaxy clusters with high sampling rates for the first time. Here we assess the feasibility of extracting the large-scale cosmic web around clusters using forthcoming observations, given realistic observational constraints. We use a sample of 324 hydrodynamic zoom-in simulations of massive galaxy clusters from TheThreeHundred project to create a mock-observational catalogue spanning $5R_{200}$ around 160 analogue clusters. These analogues are matched in mass to the 16 clusters targetted by the forthcoming WEAVE Wide-Field Cluster Survey (WWFCS). We consider the effects of the fibre allocation algorithm on our sampling completeness and find that we successfully allocate targets to 81.7 $\% \pm$ 1.3 of the members in the cluster outskirts. We next test the robustness of the filament extraction algorithm by using a metric, $D_{\text{skel}}$, which quantifies the distance to the filament spine. We find that the median positional offset between reference and recovered filament networks is $D_{\text{skel}} = 0.13 \pm 0.02$ Mpc, much smaller than the typical filament radius of $\sim$ 1 Mpc. Cluster connectivity of the recovered network is not substantially affected. Our findings give confidence that the WWFCS will be able to reliably trace cosmic web filaments in the vicinity around massive clusters, forming the basis of environmental studies into the effects of pre-processing on galaxy evolution.

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SDSS-IV MaNGA: the chemical co-evolution of gas and stars in spiral galaxies

We investigate archaeologically how the metallicity in both stellar and gaseous components of spiral galaxies of differing masses evolve with time, using data from the SDSS-IV MaNGA survey. For the stellar component, we can measure this evolution directly by decomposing the galaxy absorption-line spectra into populations of different ages and determining their metallicities. For the gaseous component, we can only measure the present-day metallicity directly from emission lines. However, there is a well-established relationship between gas metallicity, stellar mass and star formation rate which does not evolve significantly with redshift; since the latter two quantities can be determined directly for any epoch from the decomposition of the absorption-line spectra, we can use this relationship to infer the variation in gas metallicity over cosmic time. Comparison of present-day values derived in this way with those obtained directly from the emission lines confirms the validity of the method. Application of this approach to a sample of 1619 spiral galaxies reveals how the metallicity of these systems has changed over the last 10 billion years since cosmic noon. For lower-mass galaxies, both stellar and gaseous metallicity increase together, as one might expect in well-mixed fairly isolated systems. In higher-mass systems, the average stellar metallicity has not increased in step with the inferred gas metallicity, and actually decreases with time. Such disjoint behaviour is what one might expect if these more massive systems have accreted significant amounts of largely pristine gas over their lifetimes, and this material has not been well mixed into the galaxies.

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SDSS-IV MaNGA: Cannibalism Caught in the Act -- on the Frequency of Occurrence of Multiple Cores in Brightest Cluster Galaxies

Although it is generally accepted that massive galaxies form in a two-phased fashion, beginning with a rapid mass buildup through intense starburst activities, followed by primarily dry mergers that mainly deposit stellar mass at outskirts, the late time stellar mass growth of brightest cluster galaxies (BCGs), the most massive galaxies in the universe, is still not well understood. Several independent measurements have indicated a slower mass growth rate than predictions from theoretical models. We attempt to resolve the discrepancy by measuring the frequency of BCGs with multiple-cores, which serve as a proxy of the merger rates in the central region and facilitate a more direct comparison with theoretical predictions. Using 79 BCGs at $z=0.06-0.15$ with integral field spectroscopic (IFS) data from the Mapping Nearby Galaxies at APO (MaNGA) project, we obtain a multiple-core fraction of $0.11 \pm 0.04$ at $z\approx 0.1$ within a 18 kpc radius from the center, which is comparable to the value of $0.08 \pm 0.04$ derived from mock observations of 218 simulated BCGs from the cosmological hydrodynamical simulation IllustrisTNG. We find that most of cores that appear close to the BCGs from imaging data turn out to be physically associated systems. Anchoring on the similarity in the multiple-core frequency between the MaNGA and IllustrisTNG, we discuss the mass growth rate of BCGs over the past 4.5 Gyr.

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An inventory of galaxies in cosmic filaments feeding galaxy clusters: galaxy groups, backsplash galaxies, and pristine galaxies

Galaxy clusters grow by accreting galaxies from the field and along filaments of the cosmic web. As galaxies are accreted they are affected by their local environment before they enter (pre-processing), and traverse the cluster potential. Observations that aim to constrain pre-processing are challenging to interpret because filaments comprise a heterogeneous range of environments including groups of galaxies embedded within them and backsplash galaxies that contain a record of their previous passage through the cluster. This motivates using modern cosmological simulations to dissect the population of galaxies found in filaments that are feeding clusters, to better understand their history, and aid the interpretation of observations. We use zoom-in simulations from The ThreeHundred project to track halos through time and identify their environment. We establish a benchmark for galaxies in cluster infall regions that supports the reconstruction of the different modes of pre-processing. We find that up to 45% of all galaxies fall into clusters via filaments (closer than 1Mpc/h from the filament spine). 12% of these filament galaxies are long-established members of groups and between 30 and 60% of filament galaxies at R200 are backsplash galaxies. This number depends on the cluster's dynamical state and sharply drops with distance. Backsplash galaxies return to clusters after deflecting widely from their entry trajectory, especially in relaxed clusters. They do not have a preferential location with respect to filaments and cannot collapse to form filaments. The remaining pristine galaxies (30 - 60%) are environmentally effected by cosmic filaments alone.

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H$α$-based Star Formation Rates in and around z $\sim$ 0.5 EDisCS clusters

We investigate the role of environment on star-formation rates of galaxies at various cosmic densities in well-studied clusters. We present the star-forming main sequence for 163 galaxies in four EDisCS clusters in the range 0.4 $<$ z $<$ 0.7. We use {\em Hubble Space Telescope}/Wide Field Camera 3 observations of the H$α$ emission line to span three distinct local environments: the cluster core, infall region, and external field galaxies. The main sequence defined from our observations is consistent with other published H$α$ distributions at similar redshifts, but differs from those derived from star-formation tracers such as 24$μ$m. We find that the H$α$-derived star-formation rates for the 67 galaxies with stellar masses greater than the mass-completeness limit of M$_*>$ 10$^{9.75}$M\textsubscript{\(\odot\)} show little dependence on environment. At face value, the similarities in the star-formation rate distributions in the three environments may indicate that the process of finally shutting down star formation is rapid, however, the depth of our data and size of our sample make it difficult to conclusively test this scenario. Despite having significant H$α$ emission, 21 galaxies are classified as {\em UVJ}-quiescent and may represent a demonstration of the quenching of star formation caught in the act.

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Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks

We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3 data based on Convolutional Neural Networks (CNN). Monochromatic $i$-band DES images with linear, logarithmic, and gradient scales, matched with debiased visual classifications from the Galaxy Zoo 1 (GZ1) catalogue, are used to train our CNN models. With a training set including bright galaxies ($16\le{i}<18$) at low redshift ($z<0.25$), we furthermore investigate the limit of the accuracy of our predictions applied to galaxies at fainter magnitude and at higher redshifts. Our final catalogue covers magnitudes $16\le{i}<21$, and redshifts $z<1.0$, and provides predicted probabilities to two galaxy types -- Ellipticals and Spirals (disk galaxies). Our CNN classifications reveal an accuracy of over 99\% for bright galaxies when comparing with the GZ1 classifications ($i<18$). For fainter galaxies, the visual classification carried out by three of the co-authors shows that the CNN classifier correctly categorises disky galaxies with rounder and blurred features, which humans often incorrectly visually classify as Ellipticals. As a part of the validation, we carry out one of the largest examination of non-parametric methods, including $\sim$100,000 galaxies with the same coverage of magnitude and redshift as the training set from our catalogue. We find that the Gini coefficient is the best single parameter discriminator between Ellipticals and Spirals for this data set.

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Beyond the Hubble Sequence -- Exploring Galaxy Morphology with Unsupervised Machine Learning

We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantised variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that includes: (1) consideration of the clustering performance simultaneously when learning features from images; (2) allowing for various distance thresholds within the HC algorithm; (3) using the galaxy orientation to determine the number of clusters. This setup provides 27 clusters created with this unsupervised learning which we show are well separated based on galaxy shape and structure (e.g., Sérsic index, concentration, asymmetry, Gini coefficient). These resulting clusters also correlate well with physical properties such as the colour-magnitude diagram, and span the range of scaling-relations such as mass vs. size amongst the different machine-defined clusters. When we merge these multiple clusters into two large preliminary clusters to provide a binary classification, an accuracy of $\sim87\%$ is reached using an imbalanced dataset, matching real galaxy distributions, which includes 22.7\% early-type galaxies and 77.3\% late-type galaxies. Comparing the given clusters with classic Hubble types (ellipticals, lenticulars, early spirals, late spirals, and irregulars), we show that there is an intrinsic vagueness in visual classification systems, in particular galaxies with transitional features such as lenticulars and early spirals. Based on this, the main result in this work is not how well our unsupervised method matches visual classifications and physical properties, but that the method provides an independent classification that may be more physically meaningful than any visually based ones.

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Cosmic filaments in galaxy cluster outskirts: quantifying finding filaments in redshift space

Inferring line-of-sight distances from redshifts in and around galaxy clusters is complicated by peculiar velocities, a phenomenon known as the "Fingers of God" (FoG). This presents a significant challenge for finding filaments in large observational data sets as these artificial elongations can be wrongly identified as cosmic web filaments by extraction algorithms. Upcoming targeted wide-field spectroscopic surveys of galaxy clusters and their infall regions such as the WEAVE Wide-Field Cluster Survey motivate our investigation of the impact of FoG on finding filaments connected to clusters. Using zoom-in resimulations of 324 massive galaxy clusters and their outskirts from The ThreeHundred project, we test methods typically applied to large-scale spectroscopic data sets. This paper describes our investigation of whether a statistical compression of the FoG of cluster centres and galaxy groups can lead to correct filament extractions in the cluster outskirts. We find that within 5 R200 (~15 Mpc/h) statistically correcting for FoG elongations of virialized regions does not achieve reliable filament networks compared to reference filament networks based on true positions. This is due to the complex flowing motions of galaxies towards filaments in addition to the cluster infall, which overwhelm the signal of the filaments relative to the volume we probe. While information from spectroscopic redshifts is still important to isolate the cluster regions, and thereby reduce background and foreground interlopers, we expect future spectroscopic surveys of galaxy cluster outskirts to rely on 2D positions of galaxies to extract cosmic filaments.

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