Cosmological 3D H I gas map with HETDEX Ly alpha emitters and eBOSS QSOs at z=2: IGM-Galaxy/QSO connection and a similar to 40 Mpc scale giant H ii bubble candidate
Astrophysical Journal IOP Publishing 903 (2020) 24
Abstract:
We present cosmological (30−400 Mpc) distributions of neutral hydrogen (H i) in the intergalactic medium (IGM) traced by Lyα emitters (LAEs) and QSOs at z = 2.1–2.5, selected with the data of the ongoing Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) and the eBOSS survey. Motivated by a previous study of Mukae et al., we investigate spatial correlations of LAEs and QSOs with H i tomography maps reconstructed from H i Lyα forest absorption in the spectra of background galaxies and QSOs obtained by the CLAMATO survey and this study, respectively. In the cosmological volume far from QSOs, we find that LAEs reside in regions of strong H i absorption, i.e., H i rich, which is consistent with results of previous galaxy−background QSO pair studies. Moreover, there is an anisotropy in the H i distribution plot of transverse and line-of-sight distances; on average the H i absorption peak is blueshifted by ~200 km s−1 from the LAE Lyα redshift, reproducing the known average velocity offset between the Lyα emission redshift and the galaxy systemic redshift. We have identified a ~40 Mpc scale volume of H i underdensity that is a candidate for a giant H ii bubble, where six QSOs and an LAE overdensity exist at $\left\langle z\right\rangle =2.16$. The coincidence of the QSO and LAE overdensities with the H i underdensity indicates that the ionizing photon radiation of the QSOs has created a highly ionized volume of multiple proximity zones in a matter overdensity. Our results suggest an evolutionary picture where H i gas in an overdensity of galaxies becomes highly photoionized when QSOs emerge in the galaxies.Probing jet launching in neutron star X-ray binaries: the variable and polarized jet of SAX J1808.4-3658
(2020)
Eclipses of jets and discs of X-ray binaries as a powerful tool for understanding jet physics and binary parameters
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 499:1 (2020) 957-973
Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI). VI. Crowdsourced lens finding with Space Warps
Astronomy and Astrophysics: a European journal EDP Sciences (2020)
Abstract:
Strong lenses are extremely useful probes of the distribution of matter on galaxy and cluster scales at cosmological distances, but are rare and difficult to find. The number of currently known lenses is on the order of 1,000. We wish to use crowdsourcing to carry out a lens search targeting massive galaxies selected from over 442 square degrees of photometric data from the Hyper Suprime-Cam (HSC) survey. We selected a sample of $\sim300,000$ galaxies with photometric redshifts in the range $0.2 < z_{phot} < 1.2$ and photometrically inferred stellar masses $\log{M_*} > 11.2$. We crowdsourced lens finding on this sample of galaxies on the Zooniverse platform, as part of the Space Warps project. The sample was complemented by a large set of simulated lenses and visually selected non-lenses, for training purposes. Nearly 6,000 citizen volunteers participated in the experiment. In parallel, we used YattaLens, an automated lens finding algorithm, to look for lenses in the same sample of galaxies. Based on a statistical analysis of classification data from the volunteers, we selected a sample of the most promising $\sim1,500$ candidates which we then visually inspected: half of them turned out to be possible (grade C) lenses or better. Including lenses found by YattaLens or serendipitously noticed in the discussion section of the Space Warps website, we were able to find 14 definite lenses, 129 probable lenses and 581 possible lenses. YattaLens found half the number of lenses discovered via crowdsourcing. Crowdsourcing is able to produce samples of lens candidates with high completeness and purity, compared to currently available automated algorithms. A hybrid approach, in which the visual inspection of samples of lens candidates pre-selected by discovery algorithms and/or coupled to machine learning is crowdsourced, will be a viable option for lens finding in the 2020s.The XXL Survey: XLII. Detection and characterisation of the galaxy population of distant galaxy clusters in the XXL-N/VIDEO field: A tale of variety
Astronomy and Astrophysics EDP Sciences 642 (2020) A124