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Richard Stiskalek

Publications and source records attributed to Richard Stiskalek.

At least 19 recordsLinked to original sources

MEGATRON: how the first stars can create an iron metallicity plateau in the smallest dwarf galaxies

We study the stellar mass-iron metallicity relation of dwarf galaxies in the new high-resolution MEGATRON cosmological radiation-hydrodynamics simulations. These simulations model galaxy formation up to $z\approx8$ in a region that will collapse into a Milky-Way-like galaxy at $z=0$, while self-consistently tracking Population III and II (Pop.~III, Pop.~II) star formation, feedback and chemical enrichment. MEGATRON dwarf galaxies are in excellent agreement with the observed stellar mass-metallicity relation at $z=0$, including an over-abundance of dwarfs along a flat plateau in metallicity ($\langle [\rm{Fe}/\rm{H}] \rangle \approx -2.5$) at low stellar masses ($M_{\star} \leq 10^5 \, \rm{M}_{\odot}$). We tie this feature to the chemical enrichment of dwarf galaxies by Pop.~III pair-instability supernova (PISN) explosions. The strong Lyman-Werner background (LW) from the protogalaxy ensures that PISNe occur in haloes massive enough ($\approx 10^7\, \rm{M}_{\odot}$) to retain their ejecta. We also predict a tail of $\approx 20\%$ of iron-deficient ($\langle [\rm{Fe}/\rm{H}] \rangle \leq - 3$) dwarf galaxies. We show that both plateau and tail (i) are robust to large variations in Pop.~II feedback assumptions, and (ii) survive in bound satellites surrounding the central galaxy at $z=0$.

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Introducing sapphire: Towards Hybrid Physics-Informed, Data-Driven Modeling of Galaxy Formation

Semi-analytic models (SAMs) have been treating galaxy populations as dynamical systems for $\gtrsim50$ years, but their evolution equations remain poorly constrained. We introduce sapphire, a modular, automatically differentiable, GPU-accelerated SAM written in JAX. For the first time, we compute exact Jacobian and Hessian matrices of a galaxy formation SAM, using the Pandya et al. (2023) nonlinear differential equation system as an example. These allow efficient, interpretable local and global sensitivity analyses, which reveal that supernova energy loading is the key astrophysical parameter. We use gradient descent and Hamiltonian Monte Carlo (HMC) to perform comprehensive mock parameter recovery tests. These indicate that the $z=0$ stellar-to-halo-mass relation alone does not contain enough information to infer many astrophysical parameters. Using observations of star-forming galaxies from the MaNGA survey and the Behroozi et al. (2019) empirical model as one baseline, we derive multiple posteriors assuming different combinations of data, including $z=0$ interstellar medium gas fractions and metallicities. The inferred physical parameters suggest that galaxies self-regulate their star formation primarily through preventative rather than ejective feedback, though this remains uncertain due to the lack of satellite galaxies, black holes and multi-phase galactic atmosphere physics. Both Fisher and HMC forecasts demonstrate the potential of sapphire to enable precision inference for galaxy formation and cosmology in a hybrid physics-informed, data-driven way, but more work is needed to expand its library of models and methods. We make sapphire publicly available at https://github.com/virajpandya/sapphire.

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Learning the Universe with cosmological rescaling of merger trees and semi-analytic galaxy formation models

Learning cosmology from galaxy surveys requires large suites of simulations spanning the cosmological and astrophysical parameter space, yet hydrodynamical simulations of galaxy formation remain prohibitively expensive. Semi-analytic models offer an inexpensive, physically grounded alternative, but still require halo merger trees from $N$-body simulations, and densely sampling cosmological parameters in sufficient volume remains expensive. We address this by extending cosmological rescaling to operate directly on merger trees and applying it in the $Ω_{\rm m}$-$σ_8$ plane, running the Santa Cruz semi-analytic model for galaxy formation on the rescaled trees to produce galaxy populations across new cosmological and astrophysical parameters at negligible additional cost. A novel halo-profile-based correction, controlled by a single free parameter, suppresses systematic bias in rescaled halo masses to below the per cent level. We apply the method to parameter estimation of $Ω_{\rm m}$ and $σ_8$ given either the stellar mass function or the two-point correlation function, finding that as few as 64, and potentially fewer, base $N$-body simulations, rescaled to $\sim1000$ training samples, match the accuracy of 750 dedicated $N$-body simulations; rescaling to 3200 realisations improves the prediction of $Ω_{\rm m}$ by $\sim25\%$. Rescaling all merger trees from a single CAMELS-SAM $N$-body simulation costs $\sim0.1$ CPUh, compared to several thousand CPUh to run the simulation itself. We demonstrate a practical route to obtaining predictions of galaxy summary statistics across cosmological and astrophysical parameters, even with a relatively small number of base $N$-body simulations.

astro-ph.CO

$S_8$ from peculiar velocities: agreement with Planck for Tully--Fisher and supernovae, tension for the fundamental plane

Peculiar velocity measurements constrain the parameter combination $fσ_8$, the product of the linear growth rate $f$ and the fluctuation amplitude $σ_8$. Under the approximation that $f$ is a monotonic function of $Ω_{\rm m}$, this can be related to $S_8 \equiv σ_8 \sqrt{Ω_{\rm m}/0.3}$, enabling direct comparison with weak lensing and cosmic microwave background results. We use three classes of direct-distance tracers -- the Tully--Fisher relation, the fundamental plane, and Type Ia supernovae -- to infer peculiar velocities. A unified hierarchical forward model jointly calibrates each distance indicator and a linear theory reconstruction of the local Universe. This is the first consistent Bayesian analysis to treat all three major classes of distance indicators within a common framework, enabling cross-checks of systematics across diverse galaxy populations. Combining the Tully--Fisher and Type Ia supernova samples, we obtain $S_8 = 0.798 \pm 0.035$ ($fσ_8 = 0.412 \pm 0.018$), in agreement with Planck and robust under the choice of galaxy bias model, with the uncertainty dominated by the variance of the 2M++ galaxy field. The fundamental plane constraints are instead unstable under the inhomogeneous Malmquist bias treatment; the quadratic extension preferred by the fundamental plane data drives their $S_8$ values lower. These findings indicate that low-redshift peculiar velocity data are concordant with the cosmic microwave background and do not reinforce the early-versus-late $S_8$ tension, though the fundamental plane results call for further scrutiny of their systematics.

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Forward-modelling Milky Way Cepheids: selection effects and physical priors in the Gaia-HST calibration

The advent of high-precision Gaia parallaxes for Milky Way Cepheids enables per cent-level calibration of the local distance ladder and the Hubble constant $H_0$. We revisit the Milky Way Cepheid calibration from Gaia EDR3 parallaxes using a fully forward-modelled Bayesian framework that simultaneously infers the period--luminosity relation, the Gaia parallax zero-point offset, and individual stellar distances while explicitly incorporating the disc geometry of the Galaxy through the distance prior and the selection functions specified in two HST SH0ES campaigns. We derive an analytic treatment of the detection probability that accounts for magnitude, parallax, period, and extinction cuts and reduces it to a tractable integral over distance and sky position. Posterior predictive checks show that this generative model matches the observed distributions of parallaxes, magnitudes, and periods. Modelling Galactic structure and survey truncation self-consistently in a Bayesian framework yields period--luminosity parameters that agree with the SH0ES maximum-likelihood values at the ${<}0.5\,σ$ level, a consequence of the small intrinsic scatter of the Cepheid period--luminosity relation. Adopting the uniform-in-volume prior recently advocated by Högås & Mörtsell (2026), without simultaneously accounting for selection, leads to a ${\sim}\,0.05~\mathrm{mag}$ bias in the period--luminosity zero-point and posterior predictive distributions incompatible with the observed data; this shift is mostly driven by the omission of the selection model, and produces an apparent and unjustified shift in $H_0$ that reflects this mismodelling. A consistent Bayesian treatment of Galactic structure and selection effects reinforces the local distance-ladder determination of $H_0$, and hence the Hubble tension with early-Universe inferences.

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Forward-modelling the Tolman and distance-duality tests with IllustrisTNG

The Tolman surface-brightness test and the angular-size distance-duality test are two complementary probes of the same underlying relation between luminosity and angular-diameter distance, $D_L = (1+z)^2 D_A$, as holds in any metric theory of gravity where photon number is conserved. Both tests have recently delivered a priori surprising signals: JWST/ASTRODEEP measurements yield a surface brightness scaling with redshift much flatter than the expected value, and ultracompact radio sources also appear to follow a flatter $D_L/D_A$ scaling with redshift. These results have been suggested to support non-expanding cosmologies, however they are also sensitive to astrophysical and instrumental effects. We test whether these results indicate genuine departures from standard cosmology by forward-modelling observed surface-brightness evolution in the IllustrisTNG cosmological hydrodynamical simulation, with an empirical mock-spectroscopic selection trained on ASTRODEEP. We show that the astrophysical evolution relevant for both tests may be effectively parametrised as a single power-law exponent for the luminosity density as a function of redshift, for which the simulation gives $γ=2.23\pm0.20$ across realistic aperture conventions. This value is approximately sufficient to explain both the Tolman and distance-duality signals within standard cosmology and galaxy formation physics, with a small discrepancy for the latter suggesting that radio AGN evolve slightly more strongly than bright galaxies.

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The subtle statistics of the distance ladder: On the distance prior and selection effects

Statistical methodology is rarely considered significant in distance-ladder studies or a potential contributor to the Hubble tension. We suggest it should be, highlighting two appreciable issues. First, astronomical distances are inferred latent parameters, requiring a prior. We show that the (often implicit) uniform priors on distance moduli common to Bayesian distance-ladder analyses bias distances low due to objects being uniformly distributed in volume, which biases the Hubble constant high. Frequentist $χ^2$ methods are unbiased for volume- or redshift-limited samples only if the redshift uncertainty (including peculiar velocities) vanishes, though simulation-based calibration can correct the bias. Second, in a Bayesian framework, selection effects introduce additional posterior factors describing the probability of objects entering the sample under the model. These partly counteract the volume prior, depending on the nature of the selection. After detailed analytic and mock-based studies, we quantify the volume-prior effect in the CosmicFlows-4 and SH0ES samples. Both use frequentist methods, so the effect appears as a potential estimator bias rather than a missing prior. The implied Hubble constant shifts are significant but must not be applied na\"ıvely -- principled selection modelling is also required, as we investigate explicitly for CosmicFlows-4. Both effects should already be captured by the SH0ES pipeline's simulation-based bias corrections. Our work highlights the crucial need to model both distances and selection accurately, either directly in a Bayesian forward model, or via post-hoc simulation-based corrections with realistic source and selection distributions. Such modelling requires samples with known, homogeneous selection criteria, which future surveys should prioritise.

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Two per cent measurement of $H_0$ from Cepheids alone

One of the most pressing problems in current cosmology is the cause of the Hubble tension. We revisit a two-rung distance ladder, composed only of Cepheid periods and magnitudes, anchor distances in the Milky Way, Large Magellanic Cloud, NGC 4258, and host galaxy redshifts. We adopt the SH0ES data for the most up-to-date and carefully vetted measurements, where the Cepheid hosts were selected to harbour also Type Ia supernovae. We introduce two important improvements: a rigorous selection modelling and a state-of-the-art density and peculiar velocity model using Manticore-Local, based on the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm. We infer $H_0 = 71.1 \pm 1.4~\mathrm{km}\,\mathrm{s}^{-1}\,\mathrm{Mpc}^{-1}$, assuming the Cepheid host sample was selected by supernova magnitudes. However, the actual selection criteria are not clear, and other assumptions can increase $H_0$ by up to one statistical standard deviation. The posterior has a lower central value and a 41 per cent smaller uncertainty than a previous study using the same distance-ladder data. This result is lower than the supernova-based SH0ES inferred value of $H_0 = 73.2 \pm 0.9~\mathrm{km}\,\mathrm{s}^{-1}\,\mathrm{Mpc}^{-1}$ at about $1.3σ$, and is in $2.8σ$ tension with the latest cosmic microwave background results in the standard cosmological model. These results demonstrate that a measurement of $H_0$ of sufficient precision to weigh in on the Hubble tension is achievable using second-rung data alone, underscoring the importance of robust and accurate statistical and velocity-field modelling.

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Learning the Universe: Constrained simulations of the Coma galaxy cluster -- I. Radial X-ray and Compton-y signatures

We present a suite of 50 high-fidelity simulations of Coma cluster analogues constructed from BORG/MANTICORE constrained initial conditions and evolved with the IllustrisTNG galaxy formation model. Regions predicted to form massive clusters comparable to Coma in mass and environment are selected and followed through cosmic time, producing realistic galaxy populations and intracluster medium properties. The ensemble captures both cosmic variance and uncertainties in the local initial conditions, providing a statistically robust framework for interpreting Coma in a cosmological context. We focus on direct comparisons with observed thermodynamical profiles of the intracluster medium. Specifically, we extract X-ray surface brightness profiles from the simulated clusters and confront them with measurements from eROSITA, as well as compute the thermal Sunyaev--Zel'dovich effect via integrated Compton-$y$ profiles for comparison with Planck satellite data. The simulations reproduce the broad shape and normalisation of both observables, while also highlighting the range of scatter expected from environmental and assembly history differences. This enables us to assess how feedback processes, merger activity, and large-scale environment shape observable cluster properties. Our results demonstrate that combining constrained cosmological initial conditions with state-of-the-art galaxy formation physics provides an effective strategy for generating targeted, observation-driven analogues of specific clusters. The resulting dataset offers a valuable resource for testing models of intracluster medium physics, calibrating scaling relations, and interpreting upcoming joint X-ray and Sunyaev--Zel'dovich observations of nearby massive clusters.

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Validating Digital Twins of the Local Universe with the Thermal Sunyaev-Zel'dovich Signal

The thermal Sunyaev-Zel'dovich (tSZ) effect provides a powerful probe of the thermal pressure of ionised gas in galaxy clusters and the cosmic web; constrained simulations reconstruct the mass and velocity fields of the local Universe. We explore how these two may be mutually informative: the tSZ signal provides a benchmark for assessing the fidelity of constrained simulations, and constrained simulations contribute information on the positions, total masses and density profiles of cosmic web structures for use in tSZ studies. We focus on cluster predictions in the Bayesian Origin Reconstruction from Galaxies (BORG) paradigm, introducing CSiBORG-Manticore, a new state-of-the-art suite of digital twins -- data-constrained posterior simulations whose initial conditions are inferred via Bayesian forward modelling. We develop a framework for scoring constrained simulations on their ability to match measured Planck Compton-$y$ maps around clusters, and use it to demonstrate improvement from previous BORG reconstructions. We further validate halo masses against weak-lensing-calibrated X-ray masses from eROSITA. We also show how high-fidelity digital twins offer a practical route to extracting additional information from tSZ data through a novel calibration of the mass-observable relation, and provide a complementary framework to purely statistical analyses of Compton-$y$ maps. This paves the way for integrating the large-scale structure information inherent in constrained simulations into the study of CMB secondary anisotropies.

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Parameterizing Dark Energy at the density level: A two-parameter alternative to CPL

We introduce a minimal two-parameter formulation of the dark energy (DE) density evolution normalized to its present-day value, $f_{\rm DE}(z) \equiv ρ_{\rm DE}(z)/ρ_{\rm DE,0}$, in terms of $f_p\equiv f_{\rm DE}(z_p)$ and the DE equation of state $w_p\equiv w(z_p)$, at a pivot redshift $z_p$. This provides an alternative framework for assessing the evidence for evolving DE, complementary to the established Chevallier-Polarski-Linder (CPL) parameterization. By parameterizing the DE density directly, the $(w_p,\,f_p)$ formulation avoids the approximate degeneracies intrinsic to the $(w_0,\,w_a)$ basis -- in particular the weak sensitivity of the expansion history to $w_a$ -- while reproducing the background evolution of representative quintessence models with equivalent accuracy. Confronting it with the latest baryon acoustic oscillation (BAO) measurements from DESI, a prior on early-universe parameters from Planck cosmic microwave background (CMB) observations, and Type Ia supernovae (SNe) data, we find that the $w_p$ and $f_p$ parameters are both tightly constrained and sensitive to distinct subsets of the data. Specifically, $w_p$ is measured to percent-level precision by BAO and CMB alone, while $f_p$ is pinned down by the independent matter density constraint that only SNe provide. Including the Pantheon+ SNe sample, we obtain $w_p = -1.04 \pm 0.04$ and $f_p = 1.07 \pm 0.04$, with similar results when using the DESY5 SNe sample. The preference for evolving DE over $Λ$CDM remains below $3σ$ across all dataset combinations, comparable to that obtained with CPL. Notably, the proximity of both $w_p$ and $f_p$ to their cosmological constant values of $(-1,1)$ -- precisely at the epoch where the data are most sensitive -- deepens the coincidence previously identified in the CPL framework, reinforcing the case for caution in interpreting the current evidence for dynamical DE.

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Renzo's rule revisited: A statistical study of galaxies' baryon - dark matter coupling

We present a systematic statistical analysis of an informal astrophysical phenomenon known as Renzo's rule (or Sancisi's law), which states that "for any feature in a galaxy's luminosity profile, there is a corresponding feature in the rotation curve, and vice versa." This is often posed as a challenge for the standard LCDM model while supporting alternative theories such as MOND. Indeed, we identify clear features in the dwarf spiral NGC 1560 -- a prime example for Renzo's rule -- and find correlation statistics which support Renzo's rule with a slight preference for MOND over LCDM halo fits. However, a broader analysis on galaxies in the SPARC database reveals an excess of features in rotation curves that lack clear baryonic counterparts, with correlation statistics deviating up to $3σ$ on average from that predicted by both MOND and LCDM haloes, challenging the validity of Renzo's rule. Thus we do not find clear evidence for Renzo's rule in present galaxy data overall. We additionally perform mock tests, which show that a definitive test of Renzo's rule is primarily limited by the lack of clearly resolved baryonic features in current galaxy data.

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Revisiting the Great Attractor: The Local Group's streamline trajectory, cosmic velocity and dynamical fate

We revisit the Great Attractor using the Manticore-Local suite of digital twins of the nearby Universe. The Great Attractor concept has been proposed as an answer to three distinct questions: what sources the Local Group velocity in the cosmic microwave background frame, where present-day velocity streamlines converge, and where the Local Group is moving to. Addressing the original motivation of the Great Attractor -- explaining the Local Group cosmic velocity -- we find that mass within $155~h^{-1}\mathrm{Mpc}$ accounts for only ${\sim}72\%$ of that velocity magnitude with ${\sim}38\,°$ directional offset. We show that even in the purely linear regime convergence within this volume is not guaranteed, particularly when also accounting for small-scale contributions to the observer velocity; no single structure, including the proposed Great Attractor, would be expected to dominate the velocity budget. Streamline convergence is smoothing-scale-dependent, transitioning from Virgo at small scales through the Hydra--Centaurus region at intermediate scales to Shapley at large scales; at intermediate smoothing the convergence point lies near Abell 3565 with an asymmetric basin of mass $\log( M / (h^{-1} \mathrm{M}_\odot)) = 16.4 \pm 0.1$ that excludes Norma. To address the third question, we evolve the Manticore-Local realisations to scale factor $a = 10$ in a new Beyond-Present-Time simulation suite and identify the asymptotic future location of the Local Group. We find that the dominant motion is towards Virgo, but even it contributes at most one third of the Local Group velocity. Our results demonstrate that the classical Great Attractor is not a dynamically dominant structure but an artefact of the instantaneous velocity field, and that no single attractor is likely to account for the Local Group motion in the cosmic rest frame.

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Testing cosmic anisotropy with cluster scaling relations

We test claims of large-scale anisotropy in the local expansion rate using cluster scaling relations as distance indicators. Using a Bayesian forward model, we jointly fit the X-ray luminosity--temperature (LT) and thermal Sunyaev-Zel'dovich--temperature (YT) relations, marginalising over the latent cluster distances and modelling selection effects as well as peculiar velocities. The latter are modelled using reconstructions of the local peculiar velocity field where we self-consistently account for possible anisotropic redshift--distance relations via an approximate scheme. This treatment proves crucial to the inferred anisotropy and breaks the degeneracy between anisotropy in scaling relation normalisations and underlying cosmological anisotropy. We apply our method to 312 clusters at $z \lesssim 0.2$, testing dipolar, quadrupolar and general (pixelised) anisotropy models. Bayesian model selection finds no more than weak evidence for any anisotropic model. For dipole models, we obtain upper limits of $δH_0 / H_0 < 3.2\%$ and bulk flow magnitude $< 1300\,\mathrm{km\,s^{-1}}$. Our results contrast with previous claims of statistically significant anisotropy from the same data, which we attribute to our principled forward modelling of both redshifts and scaling relation observables through latent distances and our treatment of the impact of anisotropic redshift--distance relations when modelling the local peculiar velocity field. Our work highlights the importance of accurately modelling peculiar velocities when testing isotropy with distance indicators, and motivates the further development of reconstructions that self-consistently treat large-scale deviations from the Hubble flow.

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Constraining cosmological simulations with peculiar velocities: a forward-modeling approach

Numerical simulations are a key tool to decipher the dynamics of gravitation. Yet, they fail to spatially reproduce the Universe we observe, limiting comparison between observations and simulations to a statistical level. This is highly problematic for rare, faint or well studied nearby objects that are observed in a single environment. The computational cost of recovering this environment in random simulations is prohibitive. We present Hamlet-PM, a method that enables the constraining of initial conditions for cosmological simulations so as to produce evolved numerical universes that can be directly compared to observations of the Local Universe: constrained simulations. Our method implements the field-level forward modeling of the early-time density field from sparse and noisy measurements of late-time peculiar velocities. The dynamics are integrated with a particle-mesh gravity solver, thus probing the mildly non-linear regime. The code is applied to the Cosmicflows-4 compilation of peculiar velocities up to z < 0.05 (160 Mpc/h). The constrained ICs a re-simulated with a high precision N-body code. A series of one hundred dark-matter only cosmological constrained simulations with a resolution of 512^3 particles in a 500^3 [Mpc/h]3 box is presented. Special attention is given to twelve prominent nearby galaxy clusters, whose simulated counterparts are matched on criteria of mass and separation. We provide a mass estimate constrained by the dynamical environment for each cluster. Field-level forward modeling of the initial conditions produces highly constrained cosmological simulations. Currently, this method already overtakes in quality the pipeline in use in the peculiar-velocity community, although systematic biases still need to be addressed. Furthermore, improving the model is easy thanks to the inherent flexibility of the Bayesian approach.

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The galaxy-environment connection revealed by constrained simulations

The evolution of galaxies is known to be connected to their position within the large-scale structure and their local environmental density. We investigate the relative importance of these using the underlying dark matter density field extracted from the Constrained Simulations in BORG (CSiBORG) suite of constrained cosmological simulations. We define cosmic web environment through both dark matter densities averaged on a scale up to 16 Mpc/h, and through cosmic web location identified by applying DisPerSE to the CSiBORG haloes. We correlate these environmental measures with the properties of observed galaxies in large surveys using optical data (from the NASA-Sloan Atlas) and 21-cm radio data (from ALFALFA). We find statistically significant correlations between environment and colour, neutral hydrogen gas (HI) mass fraction, star formation rate and Sérsic index. Together, these correlations suggest that bluer, star forming, HI rich, and disk-type galaxies tend to reside in lower density areas, further from filaments, while redder, more elliptical galaxies with lower star formation rates tend to be found in higher density areas, closer to filaments. We find analogous trends with the quenching of galaxies, but notably find that the quenching of low mass galaxies has a greater dependence on environment than the quenching of high mass galaxies. We find that the relationship between galaxy properties and the environmental density is stronger than that with distance to filament, suggesting that environmental density has a greater impact on the properties of galaxies than their location within the larger-scale cosmic web.

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Testing subhalo abundance matching with galaxy kinematics

The rotation velocities of disc galaxies trace dark matter halo structure, providing direct constraints on the galaxy--halo connection. We construct a Bayesian forward model to connect the dark matter halo population predicted by $Λ$CDM with an observed sample of disc galaxies (SPARC) through their maximum rotation velocities. Our approach combines a subhalo abundance matching scheme (accounting for assembly bias) with a parameterised halo response to galaxy formation. When assuming no correlation between selection in the SPARC survey and halo properties, reproducing the observed velocities requires strong halo expansion, low abundance matching scatter ($<0.15$ dex at $1σ$) and a halo proxy that strongly suppresses the stellar masses in satellite haloes. This is in clear tension with independent clustering constraints. Allowing for SPARC-like galaxies to preferentially populate low $\Vmax$ haloes at fixed virial mass greatly improves the goodness-of-fit and resolves these tensions: the preferred halo response shifts to mild contraction, the abundance matching scatter increases to $\sint = 0.19^{+0.13}_{-0.11}$ dex and the proxy becomes consistent with clustering. However, the inferred selection threshold is extreme, implying that SPARC galaxies occupy the lowest ${\sim}16$ per cent of the $\Vmaxhalo$ distribution at fixed $\Mvir$. Moreover, even with selection, the inferred scatter remains in statistical disagreement with the low-mass clustering constraints, which are most representative of the SPARC galaxies in our sample. Our analysis highlights the advantage of augmenting clustering-based constraints on the galaxy--halo connection with kinematics and suggests a possible tension using current data.

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The Velocity Field Olympics: Assessing velocity field reconstructions with direct distance tracers

The peculiar velocity field of the local Universe provides direct insights into its matter distribution and the underlying theory of gravity, and is essential in cosmological analyses for modelling deviations from the Hubble flow. Numerous methods have been developed to reconstruct the density and velocity fields at $z \lesssim 0.05$, typically constrained by redshift-space galaxy positions or by direct distance tracers such as the Tully-Fisher relation, the fundamental plane, or Type Ia supernovae. We introduce a validation framework to evaluate the accuracy of these reconstructions against catalogues of direct distance tracers. Our framework assesses the goodness-of-fit of each reconstruction using Bayesian evidence, residual redshift discrepancies, velocity scaling, and the need for external bulk flows. Applying this framework to a suite of reconstructions -- including those derived from the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm and from linear theory -- we find that the non-linear BORG reconstruction consistently outperforms others. We highlight the utility of such a comparative approach for supernova or gravitational wave cosmological studies, where selecting an optimal peculiar velocity model is essential. Additionally, we present calibrated bulk flow curves predicted by the reconstructions and perform a density--velocity cross-correlation using a linear theory reconstruction to constrain the growth factor, yielding $S_8 = 0.793 \pm 0.035$. The result is in good agreement with both weak lensing and Planck, but is in strong disagreement with some peculiar velocity studies.

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