Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

To understand the impact of radiation feedback during the formation of a globular cluster (GC), we simulate a head-on collision of two turbulent giant molecular clouds (GMCs). A series of idealized radiation-hydrodynamic simulations is performed, with and without stellar radiation or Type II supernovae. We find that a gravitationally bound, compact star cluster of mass M_GC ∼ 10⁵ M_⊙ forms within ≈3 Myr when two GMCs with mass M_GMC = 3.6 × 10⁵ M⊙ collide. The GC candidate does not form during a single collapsing event but emerges due to the mergers of local dense gas clumps and gas accretion. The momentum transfer due to the absorption of the ionizing radiation is the dominant feedback process that suppresses the gas collapse, and photoionization becomes efficient once a sufficient number of stars form. The cluster mass is larger by a factor of ∼2 when the radiation feedback is neglected, and the difference is slightly more pronounced (16%) when extreme Lyα feedback is considered in the fiducial run. In the simulations with radiation feedback, supernovae explode after the star-forming clouds are dispersed, and their metal ejecta are not instantaneously recycled to form stars.

Abstract:

We present a method for fast evaluation of the covariance matrix for a two-point galaxy correlation function (2PCF) measured with the Landy-Szalay estimator. The standard way of evaluating the covariance matrix consists in running the estimator on a large number of mock catalogs, and evaluating their sample covariance. With large random catalog sizes (random-to-data objects' ratio M >> 1) the computational cost of the standard method is dominated by that of counting the data-random and random-random pairs, while the uncertainty of the estimate is dominated by that of data-data pairs. We present a method called Linear Construction (LC), where the covariance is estimated for small random catalogs with a size of M = 1 and M = 2, and the covariance for arbitrary M is constructed as a linear combination of the two. We show that the LC covariance estimate is unbiased. We validated the method with PINOCCHIO simulations in the range r = 20-200 h(-1) Mpc. With M = 50 and with 2h(-1) Mpc bins, the theoretical speedup of the method is a factor of 14. We discuss the impact on the precision matrix and parameter estimation, and present a formula for the covariance of covariance.Peer reviewe

Abstract:

We study the nature of the faint radio source population detected in the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Early Science data in the COSMOS field, focusing on the properties of the radio-loud active galactic nuclei (AGNs). Using the extensive multiwavelength data available in the field, we are able to classify 88 per cent of the 5223 radio sources in the field with host galaxy identifications as AGNs (35 per cent) or star-forming galaxies (54 per cent). We select a sample of radio-loud AGNs with redshifts out to z ∼ 6 and radio luminosities 10²⁰ < L_1.4 GHz/W Hz⁻¹ < 10²⁷ and classify them as high-excitation and low-excitation radio galaxies (HERGs and LERGs). The classification catalogue is released with this work. We find no significant difference in the host galaxy properties of the HERGs and LERGs in our sample. In contrast to previous work, we find that the HERGs and LERGs have very similar Eddington-scaled accretion rates; in particular we identify a population of very slowly accreting AGNs that are formally classified as HERGs at these low radio luminosities, where separating into HERGs and LERGs possibly becomes redundant. We investigate how black hole mass affects jet power, and find that a black hole mass ≳ 10^7.8 M_⊙ is required to power a jet with mechanical power greater than the radiative luminosity of the AGN (L_mech/L_bol > 1). We discuss that both a high black hole mass and black hole spin may be necessary to launch and sustain a dominant radio jet.

Abstract:

Improving the theoretical description of galaxy clustering on small scales is an important challenge in cosmology, as it can considerably increase the scientific return of forthcoming galaxy surveys - e.g. tightening the bounds on neutrino masses and deviations from general relativity. In this paper, we propose and test a new model for the clustering of galaxies that is able to accurately describe redshift-space distortions even down to small scales. This model corresponds to a second-order perturbative Lagrangian bias expansion which is advected to Eulerian space employing a displacement field extracted from N-body simulations. Eulerian coordinates are then transformed into redshift space by directly employing simulated velocity fields augmented with nuisance parameters capturing various possible satellite fractions and intra-halo small-scale velocities. We quantify the accuracy of our approach against samples of physically motivated mock galaxies selected according to either stellar mass (SM) or star formation rate (SFR) at multiple abundances and at z = 0 and 1. We find our model describes the monopole, quadrupole, and hexadecapole of the galaxy-power spectra down to scales of k ≈ 0.6 [h Mpc-1] within the accuracy of our simulations. This approach could pave the way to significantly increase the amount of cosmological information to be extracted from future galaxy surveys.