Cosmology

Abstract:

We present Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) maps of the Cosmic Microwave Background temperature and polarization anisotropy at arcminute resolution over three frequency bands centered on 98, 150 and 220 GHz. The maps are based on data collected with the AdvancedACT camera over the period 2017–2022 and cover 19,000 square degrees with a median combined depth of 10 μK arcmin. We describe the instrument, mapmaking and map properties and illustrate them with a number of figures and tables. The ACT DR6 maps and derived products are available on LAMBDA at https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html. We also provide an interactive web atlas at https://phy-act1.princeton.edu/public/snaess/actpol/dr6/atlas and HiPS data sets in Aladin (e.g. https://alasky.cds.unistra.fr/ACT/DR4DR6/color_CMB).

Abstract:

Abstract Despite the vast amount of energy released by active galactic nuclei (AGN), their role in early galaxy formation and in regulating the growth of supermassive black holes (SMBHs) remains poorly understood. Through new high-resolution zoom-in cosmological simulations, we follow the co-evolution of 105 M⊙ black hole seeds with their host dwarf galaxy. We model ionizing feedback from a Pop III.1 progenitor, applicable to a wide range of internally or externally irradiated SMBH formation scenarios. The simulated suite progressively spans physics ranging from no AGN feedback to more complex setups including thermal, kinetic and radiative feedback – explored for both low and enhanced AGN power. Across all our models, we find that black hole seeds efficiently reach masses of ∼107 M⊙ within a ∼1010 M⊙ halo by z = 8. Although they exhibit notably different mass growth histories, these latter seem unimpeded by the presence of AGN feedback. The simulation including radiative feedback is the most distinct, with super-Eddington episodes driving fast and mass-loaded gas outflows (exceeding 2500 km s−1) up to ∼50 kpc, along with minor stellar mass suppression in the host galaxy. Our measurements are in broad agreement with moderate luminosity quasars recently observed by JWST, producing overmassive black holes (SMBH-to-galaxy mass ratios 0.01 − 1), dynamical masses of ∼109.5 M⊙, stellar masses of ∼108.5 M⊙, and high, though short-lived, Eddington fraction accretion rates. These results advocate for a scenario where AGN feedback allows for rapid SMBH growth during the reionisation era, while driving winds that extend deep into the intergalactic medium – shaping host galaxies as well as more distant surroundings.

Abstract:

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 Λ cold dark matter (CDM) model while supporting alternative theories such as modified Newtonian dynamics (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 CDM halo fits. However, a broader analysis on galaxies in the Spitzer Photometry & Accurate Rotation Curves (SPARC) data base reveals an excess of features in rotation curves that lack clear baryonic counterparts, with correlation statistics deviating up to on average from that predicted by both MOND and CDM 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.

Abstract:

Abstract 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 ≲ 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 S8 = 0.793 ± 0.035. The result is in good agreement with both weak lensing and Planck, but is in strong disagreement with some peculiar velocity studies.

Abstract:

To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations that evolve particles under gravity by estimating particle-particle interactions (𝑁-body simulations) are computationally expensive and prohibitive to scale to the large volumes and resolutions necessary for the upcoming datasets. Moreover, modeling the distribution of galaxies typically involves identifying virialized dark matter halos, which is also a time- and memory-consuming process for large 𝑁-body simulations, further exacerbating the computational cost. In this study, we introduce CHARM, a novel method for creating mock halo catalogs by matching the spatial, mass, and velocity statistics of halos directly from the large-scale distribution of the dark matter density field. We develop multistage neural spline flow-based networks to learn this mapping at redshift 𝑧 =0.5 directly with computationally cheaper low-resolution particle mesh simulations instead of relying on the high-resolution 𝑁-body simulations. We show that the mock halo catalogs and painted galaxy catalogs have the same statistical properties as obtained from 𝑁-body simulations in both real space and redshift space. Finally, we use these mock catalogs for cosmological inference using redshift-space galaxy power spectrum, bispectrum, and wavelet-based statistics using simulation-based inference, performing the first inference with accelerated forward model simulations and finding unbiased cosmological constraints with well-calibrated posteriors.