Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Abstract 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 ΛCDM 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 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 constraint relaxes to σSHAM < 0.30 dex at 1σ and the proxy becomes consistent with clustering. However, the inferred selection threshold is extreme, implying that SPARC galaxies occupy the lowest ~15 per cent of the Vmax, halo 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.

Abstract:

Simulations predict that bars in galaxies should slow down over time. This is often attributed to the exchange of angular momentum between the bar and other regions of the galaxy, such as the outer disk and dark matter halo, which implies that galaxies with a more massive halo or disk should be able to slow down the bar more efficiently. However, observational evidence for this process has been limited. In this work, we provide observational support for the slowing down of bars as predicted by simulations. We combine bar kinematics measurements obtained with the Tremaine–Weinberg method and host galaxy mass estimates derived from Jeans anisotropic models for a sample of 30 galaxies from the MaNGA survey. We find a statistically significant anticorrelation (>4σ) between the bar pattern speed and both the stellar and total dynamical mass, which suggests that the slowest bars reside in the most massive galaxies. However, while the slope of the best-fit line between the pattern speed and dark matter mass is negative, it is not statistically significant (2.43σ). We also find that bars with lower pattern speeds have more extended NFW dark matter profiles with lower central densities. Additionally, we find statistically significant correlations (>3σ) between the corotation radius and the stellar mass, dark matter mass, and total dynamical mass. Finally, we find no significant correlations that involve the dark matter fraction or R , likely due to the inherent challenges associated with measuring these specific parameters accurately.

Abstract:

We constrain the difference in gravitational potential between our location and sources at (Formula presented.) using datasets at those redshifts. Our motivation is that the Hubble tension might be caused by a local void, as suggested by galaxy number counts. This would increase the redshift through outflow and gravitational redshift (GR). Only the latter is important at high redshift, where a void contributes a fixed additional GR contribution of (Formula presented.) due to our location on a potential hill. This (Formula presented.) model has various subtle effects that were not previously considered, including a hotter CMB and reduced BAO scale (Formula presented.). We test whether (Formula presented.) can have the previously expected value of 0.84%, which was based on the fitting of void parameters to galaxy number counts and local (Formula presented.) measurements. Combining BBN, CMB, BAO, and CC datasets at (Formula presented.), we find that (Formula presented.) = (Formula presented.), which rises to (Formula presented.) when extending our analysis down to (Formula presented.). Although the results prefer the standard value of (Formula presented.), the best-fitting model with (Formula presented.) fits the data almost as well as (Formula presented.) CDM, with (Formula presented.). We find that (Formula presented.) CDM faces a (Formula presented.) BAO anomaly in the standard (Formula presented.) parameter space, where different regions are preferred by BAO and non-BAO datasets from (Formula presented.). Fixing (Formula presented.) reduces this to (Formula presented.). This suggests that a local void large enough to solve the Hubble tension cannot be ruled out by higher-redshift datasets, despite its novel impacts on them.

Abstract:

Abstract The structure of dark matter haloes is often described by radial density profiles motivated by cosmological simulations. These are typically assumed to have a fixed functional form (e.g. NFW), with some free parameters. However, relying on simulations has the disadvantage that the resulting profiles depend on the dark matter model and the baryonic physics implementation, which are highly uncertain. Instead, we present a method to constrain halo density profiles directly from observations. This is done using a symbolic regression algorithm called Exhaustive Symbolic Regression (ESR). ESR searches for the optimal analytic expression to fit data, combining both accuracy and simplicity. We apply ESR to a sample of 149 galaxy clusters from the HSC-XXL survey to identify which functional forms perform best across the entire sample of clusters. We identify density profiles that statistically outperform NFW under a minimum-description-length criterion. Within the radial range probed by the weak-lensing data (R ~ 0.3 − 3 h−1 Mpc), the highest-ranked ESR profiles exhibit shallow inner behaviour and a maximum in the density profile. As a practical application, we show how the best-fitting ESR models can be used to obtain enclosed mass estimates. We find masses that are, on average, higher than those derived using NFW, highlighting a source of potential bias when assuming the wrong density profile. These results have important knock-on effects for analyses that utilise clusters, for example cosmological constraints on σ8 and Ωm from cluster abundance and clustering. Beyond the HSC dataset, the method is applicable to any data constraining the dark matter distribution in galaxies and galaxy clusters, such as other weak lensing surveys, galactic rotation curves, or complementary probes.