Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

ABSTRACT The advent of high-precision Gaia parallaxes for Milky Way Cepheids enables percent-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 ${\lt }0.5\, \sigma $ level, a consequence of the small intrinsic scatter of the Cepheid period–luminosity relation. Adopting the uniform-in-volume prior recently advocated by M. Högås & E. Mörtsell, 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.

Abstract:

There is tentative evidence for a mismatch between the rest frames of matter and the cosmic microwave background, the “quasar dipole anomaly.” We consider such a dipole in tilted anisotropic models, for a range of scenarios and sources: spatial curvature, cosmic heat flux, large scale electromagnetic fields, and a Khronon field. Crucially, we determine the ancillary effects on other cosmological observables in each of these models, and we show that, apart from the case of the Khronon field, it is unlikely that one can obtain a dipole with the amplitude that is being observed unless one considers additional exotica.

Abstract:

Abstract The galaxy luminosity and stellar mass function (LF, SMF), and halo mass function (HMF), are fundamental quantities in astrophysics and crucial inputs to a range of astrophysical and cosmological analyses. They are typically parametrised by fitting functions that have been chosen ‘by eye’ to match observed or simulated data. We apply symbolic regression—specifically the Exhaustive Symbolic Regression (ESR) algorithm—to automate the search for optimal LF, SMF and HMF functional forms. ESR scores all functions up to a maximum complexity composed of a user-defined basis set of operators using the description length, an approximation to the Bayesian evidence that balances accuracy with complexity. We find many functions that outperform the Schechter and double Schechter functions for the LF and SMF, and that outperform all investigated literature functions (that outperform the Press–Schechter, Warren, Tinker, Sheth–Tormen and Jenkins) for the HMF. By additionally imposing ‘physicality checks’ on functions’ extrapolation and integration properties, we identify the optimal, low-complexity functional forms in terms of accuracy, simplicity and behaviour beyond the data range. As well as providing drop-in replacements for literature LF, SMF and HMF fitting functions, and identifying robust behaviour across well-fitting functions, we present a framework with which symbolic regression may be used to automate the discovery of optimal functions for any astrophysical dataset.

Abstract:

The pristine underdense patches of the Universe, cosmic voids, are powerful cosmological laboratories, uniquely sensitive to dark energy, modified gravity, and neutrino masses, yet their baryonic content remains uncharacterized. We present the first constraint on baryon underdensity in voids, exploiting the dispersion measures (DMs) of fast radio bursts (FRBs) as tracers of the electron column. By stacking 3455 sight lines from CHIME/FRB with ∼15′ localizations on 1228 Sloan Digital Sky Survey (SDSS) BOSS voids over redshifts 0.2 < z < 0.7, we measure a DM deficit toward void centers at 3.2σ significance, indicating that diffuse baryons inhabit the emptiest corners of the cosmic web at a suppressed level. The measured signal amplitude is consistent with an effective Universe model built directly from the observed galaxy underdensity in these voids, and a baryonic model calibrated to the FRB DM–redshift relation (αv = 1.80 ± 0.87). A uniform-density void model yields an electron density contrast of δe,v = −0.58 ± 0.30, implying a tentative ∼60% ± 30% underdensity of baryons in void interiors relative to the cosmic mean. Jointly interpreting our FRB measurement with existing stacks of the thermal Sunyaev–Zel’dovich effect on voids further constrains the mean gas temperature to Te ≲ (1.1 ± 0.7) × 10⁶ K, pointing to a warm-hot diffuse phase, consistent with hydrodynamical simulations. With forthcoming FRB and galaxy surveys, this approach opens a new window onto baryon mapping, with direct implications for feedback models governing gas expulsion into low-density environments, and for the use of cosmic voids to extract cosmological constraints.