On the fundamentality of the radial acceleration relation for late-type galaxy dynamics

Galaxies have been observed to exhibit a level of simplicity unexpected in the complex galaxy formation scenario posited by standard cosmology. This is particularly apparent in their dynamics, where scaling relations display much regularity and little intrinsic scatter. However, the parameters responsible for this simplicity have not been identified. Using the Spitzer Photometry & Accurate Rotation Curves galaxy catalogue, we argue that the radial acceleration relation (RAR) between galaxies' baryonic and total dynamical accelerations is the fundamental $1$-dimensional correlation governing the radial (in-disk) dynamics of late-type galaxies. In particular, we show that the RAR cannot be tightened by the inclusion of any other available galaxy property, that it is the strongest projection of galaxies' radial dynamical parameter space, and that all other statistical radial dynamical correlations stem from the RAR plus the non-dynamical correlations present in our sample. We further provide evidence that the RAR's fundamentality is unique in that the second most significant dynamical relation does not possess any of these features. Our analysis reveals the root cause of the correlations present in galaxies' radial dynamics: they are nothing but facets of the RAR. These results have important ramifications for galaxy formation theory because they imply that to explain statistically late-type galaxy dynamics within the disk it is necessary and sufficient to explain the RAR and lack of any significant, partially independent correlation. While simple in some modified dynamics models, this poses a challenge to standard cosmology.Comment: 17 pages, 9 figures. Accepted in MNRA

Evaluating the reconstruction of individual haloes in constrained cosmological simulations

Constrained cosmological simulations play an important role in modelling the local Universe, enabling investigation of the dark matter content of local structures and their formation histories. We introduce a method for determining the extent to which individual haloes are reliably reconstructed between constrained simulations, and apply it to the Constrained Simulations in BORG (CSiBORG) suite of $101$ high-resolution realisations across the posterior probability distribution of initial conditions from the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm. The method is based on the overlap of the initial Lagrangian patch of a halo in one simulation with those in another, and therefore measures the degree to which the haloes' particles are initially coincident. By this metric we find consistent reconstructions of $M\gtrsim10^{14}~M_\odot / h$ haloes across the CSiBORG simulations, indicating that the constraints from the BORG algorithm are sufficient to pin down the masses, positions and peculiar velocities of clusters to high precision. The effect of the constraints tapers off towards lower mass however, and the halo spins and concentrations are largely unconstrained at all masses. We document the advantages of evaluating halo consistency in the initial conditions, describe how the method may be used to quantify our knowledge of the halo field given galaxy survey data analysed through the lens of probabilistic inference machines such as BORG, and describe applications to matched but unconstrained simulations.Comment: 11 pages, 11 figures. To be submitted to MNRAS. Comments are welcome

The dependence of subhalo abundance matching on galaxy photometry and selection criteria

Subhalo abundance matching (SHAM) is a popular technique for assigning galaxy mass or luminosity to haloes produced in N-body simulations. The method works by matching the cumulative number functions of the galaxy and halo properties, and is therefore sensitive both to the precise definitions of those properties and to the selection criteria used to define the samples. Further dependence follows when SHAM parameters are calibrated with galaxy clustering, which is known to depend strongly on the manner in which galaxies are selected. In this paper we introduce a new parametrisation for SHAM and derive the best-fit SHAM parameters as a function of various properties of the selection of the galaxy sample and of the photometric definition, including S\'ersic vs Petrosian magnitudes, stellar masses vs r-band magnitudes and optical (SDSS) vs HI (ALFALFA) selection. In each case we calculate the models' goodness-of-fit to measurements of the projected two-point galaxy correlation function. In the optically-selected samples we find strong evidence that the scatter in the galaxy-halo connection increases towards the faint end, and that AM performs better with luminosity than stellar mass. The SHAM parameters of optically- and HI-selected galaxies are mutually exclusive, with the latter suggesting the importance of properties beyond halo mass. We provide best-fit parameters for the SHAM galaxy-halo connection as a function of each of our input choices, extending the domain of validity of the model while reducing potential systematic error in its use.Comment: 19 pages and 15 figures. Matches the journal versio

Are stellar--mass binary black hole mergers isotropically distributed?

The Advanced LIGO and Advanced Virgo gravitational wave detectors have detected a population of binary black hole mergers in their first two observing runs. For each of these events we have been able to associate a potential sky location region represented as a probability distribution on the sky. Thus, at this point we may begin to ask the question of whether this distribution agrees with the isotropic model of the Universe, or if there is any evidence of anisotropy. We perform Bayesian model selection between an isotropic and a simple anisotropic model, taking into account the anisotropic selection function caused by the underlying antenna patterns and sensitivity of the interferometers over the sidereal day. We find an inconclusive Bayes factor of $1.3:1$, suggesting that the data from the first two observing runs is insufficient to pick a preferred model. However, the first detections were mostly poorly localised in the sky (before the Advanced Virgo joined the network), spanning large portions of the sky and hampering detection of potential anisotropy. It will be appropriate to repeat this analysis with events from the recent third LIGO observational run and a more sophisticated cosmological model.Comment: 8 pages, 8 figures. Accepted by MNRA

The scatter in the galaxy-halo connection: a machine learning analysis

We apply machine learning, a powerful method for uncovering complex correlations in high-dimensional data, to the galaxy-halo connection of cosmological hydrodynamical simulations. The mapping between galaxy and halo variables is stochastic in the absence of perfect information, but conventional machine learning models are deterministic and hence cannot capture its intrinsic scatter. To overcome this limitation, we design an ensemble of neural networks with a Gaussian loss function that predict probability distributions, allowing us to model statistical uncertainties in the galaxy-halo connection as well as its best-fit trends. We extract a number of galaxy and halo variables from the Horizon-AGN and IllustrisTNG100-1 simulations and quantify the extent to which knowledge of some subset of one enables prediction of the other. This allows us to identify the key features of the galaxy-halo connection and investigate the origin of its scatter in various projections. We find that while halo properties beyond mass account for up to 50 per cent of the scatter in the halo-to-stellar mass relation, the prediction of stellar half-mass radius or total gas mass is not substantially improved by adding further halo properties. We also use these results to investigate semi-analytic models for galaxy size in the two simulations, finding that assumptions relating galaxy size to halo size or spin are not successful.Comment: 20 pages, 11 figures. Accepted in MNRA