Star-Gas Misalignment in Galaxies: II. Origins Found from the Horizon-AGN Simulation
Abstract:
There have been many studies aiming to reveal the origins of the star-gas misalignment found in galaxies, but there still is a lack of understanding of the contribution from each formation channel candidate. We aim to answer the question by investigating the misaligned galaxies in Horizon-AGN, a cosmological large-volume simulation of galaxy formation. There are 27,903 galaxies of stellar mass $M_* > 10^{10} M_\odot$ in our sample, of which 5,984 are in a group of the halo mass of $M_{200} > 10^{12} M_\odot$. We have identified four main formation channels of misalignment and quantified their level of contribution: mergers (35%), interaction with nearby galaxies (23%), interaction with dense environments or their central galaxies (21%), and secular evolution including smooth accretion from neighboring filaments (21%). We found in the simulation that the gas, rather than stars, is typically more vulnerable to dynamical disturbances; hence, misalignment formation is mainly due to the change in the rotational axis of the gas rather than stars, regardless of the origin. We have also inspected the lifetime (duration) of the misalignment. The decay timescale of the misalignment shows a strong anti-correlation with the kinematic morphology ($V/{\sigma}$) and the cold gas fraction of the galaxy. The misalignment has a longer lifetime in denser regions, which is linked with the environmental impact on the host galaxy. There is a substantial difference in the length of the misalignment lifetime depending on the origin, and it can be explained by the magnitude of the initial position angle offset and the physical properties of the galaxies.Star-gas misalignment in galaxies: I. The properties of galaxies from the Horizon-AGN simulation and comparisons to SAMI
Abstract:
Recent integral field spectroscopy observations have found that about 11\% of galaxies show star-gas misalignment. The misalignment possibly results from external effects such as gas accretion, interaction with other objects, and other environmental effects, hence providing clues to these effects. We explore the properties of misaligned galaxies using Horizon-AGN, a large-volume cosmological simulation, and compare the result with the result of the Sydney-AAO Multi-object integral field spectrograph (SAMI) Galaxy Survey. Horizon-AGN can match the overall misalignment fraction and reproduces the distribution of misalignment angles found by observations surprisingly closely. The misalignment fraction is found to be highly correlated with galaxy morphology both in observations and in the simulation: early-type galaxies are substantially more frequently misaligned than late-type galaxies. The gas fraction is another important factor associated with misalignment in the sense that misalignment increases with decreasing gas fraction. However, there is a significant discrepancy between the SAMI and Horizon-AGN data in the misalignment fraction for the galaxies in dense (cluster) environments. We discuss possible origins of misalignment and disagreement.Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI). VI. Crowdsourced lens finding with Space Warps
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 FIR/submm window on galaxy formation
The Birth of Galaxies