49 new T dwarfs identified using methane imaging

We present the discovery of 49 new photometrically classified T dwarfs from the combination of large infrared and optical surveys combined with follow-up TNG photometry. We used multi-band infrared and optical photometry from the UKIRT and Sloan Digital Sky Surveys to identify possible brown dwarf candidates, which were then confirmed using methane filter photometry. We have defined a new photometric conversion between CH4s - CH4l colour and spectral type for T4 to T8 brown dwarfs based on a part of the sample that has been followed up using methane photometry and spectroscopy. Using methane differential photometry as a proxy for spectral type for T dwarfs has proved to be a very efficient technique. Of a subset of 45 methane selected brown dwarfs that were observed spectroscopically, 100% were confirmed as T dwarfs. Future deep imaging surveys will produce large samples of faint brown dwarf candidates, for which spectroscopy will not be feasible. When broad wavelength coverage is unavailable, methane imaging offers a means to efficiently classify candidates from such surveys using just a pair of near-infrared images.Peer reviewe

Statistics of extreme objects in the Juropa Hubble Volume simulation

We present the first results from the JUropa huBbLE volumE (Jubilee) project, based a large N-body, dark matter-only cosmological simulation with a volume of $V=(6 h^{-1}\mathrm{Gpc})^3$, containing 6000$^3$ particles, performed within the concordance $\Lambda$CDM cosmological model. The simulation volume is sufficient to probe extremely large length scales in the universe, whilst at the same time the particle count is high enough so that dark matter haloes down to $1.5\times10^{12} h^{-1}\mathrm{M}_\odot$ can be resolved. At $z = 0$ we identify over 400 million haloes. The cluster mass function is derived using three different halofinders and compared to fitting functions in the literature. The distribution of clusters of maximal mass across redshifts agrees well with predicted masses of extreme objects, and we explicitly confirm that the Poisson distribution is very good at describing the distribution of rare clusters. The Poisson distribution also matches well the level to which cosmic variance can be expected to affect number counts of high mass clusters. We find that objects like the Bullet cluster exist in the far-tail of the distribution of mergers in terms of relative collisional speed. We also derive the number counts of voids in the simulation box for $z = 0$, $0.5$ and $1$.Comment: Version 2. 12 pages, 9 figures. Accepted by MNRA

The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST

We present TXPipe, a modular, automated and reproducible pipeline for ingesting catalog data and performing all the calculations required to obtain quality-assured two-point measurements of lensing and clustering, and their covariances, with the metadata necessary for parameter estimation. The pipeline is developed within the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC), and designed for cosmology analyses using LSST data. In this paper, we present the pipeline for the so-called 3x2pt analysis -- a combination of three two-point functions that measure the auto- and cross-correlation between galaxy density and shapes. We perform the analysis both in real and harmonic space using TXPipe and other LSST-DESC tools. We validate the pipeline using Gaussian simulations and show that it accurately measures data vectors and recovers the input cosmology to the accuracy level required for the first year of LSST data under this simplified scenario. We also apply the pipeline to a realistic mock galaxy sample extracted from the CosmoDC2 simulation suite (Korytov et al. 2019). TXPipe establishes a baseline framework that can be built upon as the LSST survey proceeds. Furthermore, the pipeline is designed to be easily extended to science probes beyond the 3x2pt analysis....ISSN:2565-612