Optimal Inflationary Potentials

ArXiv 2310.16786 (2023)

Authors:

Tomás Sousa, Deaglan J Bartlett, Harry Desmond, Pedro G Ferreira

On the Origin of the Variety of Velocity Dispersion Profiles of Galaxies

(2023)

Authors:

San Han, Sukyoung K Yi, Sree Oh, Mina Pak, Scott M Croom, Julien Devriendt, Yohan Dubois, Taysun Kimm, Katarina Kraljic, Christophe Pichon, Marta Volonteri

The formation of cores in galaxies across cosmic time -- the existence of cores is not in tension with the LCDM paradigm

(2023)

Authors:

RA Jackson, S Kaviraj, SK Yi, S Peirani, Y Dubois, G Martin, JEG Devriendt, A Slyz, C Pichon, M Volonteri, T Kimm, K Kraljic

Cosmology from LOFAR Two-metre Sky Survey data release 2: angular clustering of radio sources

Monthly Notices of the Royal Astronomical Society Oxford University Press 527:3 (2023) 6540-6568

Authors:

Cl Hale, Dj Schwarz, Pn Best, Sj Nakoneczny, David Alonso, D Bacon, L Böhme, N Bhardwaj, M Bilicki, S Camera, Cs Heneka, M Pashapour-Ahmadabadi, P Tiwari, J Zheng, Kj Duncan, Mj Jarvis, R Kondapally, M Magliocchetti, Hja Rottgering, Tw Shimwell

Abstract:

Covering ∼ 5600 deg2 to rms sensitivities of ∼70−100 μJy beam−1, the LOFAR Two-metre Sky Survey Data Release 2 (LoTSS-DR2) provides the largest low-frequency (∼150 MHz) radio catalogue to date, making it an excellent tool for large-area radio cosmology studies. In this work, we use LoTSS-DR2 sources to investigate the angular two-point correlation function of galaxies within the survey. We discuss systematics in the data and an improved methodology for generating random catalogues, compared to that used for LoTSS-DR1, before presenting the angular clustering for ∼900 000 sources ≥1.5 mJy and a peak signal-to-noise ≥ 7.5 across ∼80 per cent of the observed area. Using the clustering, we infer the bias assuming two evolutionary models. When fitting angular scales of 0.5 ≤ θ < 5◦, using a linear bias model, we find LoTSS-DR2 sources are biased tracers of the underlying matter, with a bias of bC = 2.14+0.22 −0.20 (assuming constant bias) and bE(z = 0) = 1.79+0.15 −0.14 (for an evolving model, inversely proportional to the growth factor), corresponding to bE = 2.81+0.24 −0.22 at the median redshift of our sample, assuming the LoTSS Deep Fields redshift distribution is representative of our data. This reduces to bC = 2.02+0.17 −0.16 and bE(z = 0) = 1.67+0.12 −0.12 when allowing preferential redshift distributions from the Deep Fields to model our data. Whilst the clustering amplitude is slightly lower than LoTSS-DR1 (≥2 mJy), our study benefits from larger samples and improved redshift estimates.

LimberJack.jl: auto-differentiable methods for angular power spectra analyses

ArXiv 2310.08306 (2023)

Authors:

J Ruiz-Zapatero, D Alonso, C García-García, A Nicola, A Mootoovaloo, JM Sullivan, M Bonici, PG Ferreira