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Register a new userPre-Processing and Post-Processing in Group-Cluster Mergers
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Added by
Rukmani Vijayaraghavan
Publication date
2013
fields
Physics
and research's language is
English
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Galaxies in clusters are more likely to be of early type and to have lower star formation rates than galaxies in the field. Recent observations and simulations suggest that cluster galaxies may be `pre-processed by group or filament environments and that galaxies that fall into a cluster as part of a larger group can stay coherent within the cluster for up to one orbital period (`post-processing). We investigate these ideas by means of a cosmological $N$-body simulation and idealized $N$-body plus hydrodynamics simulations of a group-cluster merger. We find that group environments can contribute significantly to galaxy pre-processing by means of enhanced galaxy-galaxy merger rates, removal of galaxies hot halo gas by ram pressure stripping, and tidal truncation of their galaxies. Tidal distortion of the group during infall does not contribute to pre-processing. Post-processing is also shown to be effective: galaxy-galaxy collisions are enhanced during a groups pericentric passage within a cluster, the merger shock enhances the ram pressure on group and cluster galaxies, and an increase in local density during the merger leads to greater galactic tidal truncation.
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We use a high-resolution cosmological dark matter-only simulation to study the orbital trajectories of haloes and subhaloes in the environs of isolated hosts. We carefully tally all apsis points and use them to distinguish haloes that are infalling for the first time from those that occupy more evolved orbits. We find that roughly 21 per cent of subhaloes within a hosts virial radius are currently on first infall, and have not yet reached their first orbital pericentre; roughly 44 per cent are still approaching their first apocentre after infall. For the range of host masses studied, roughly half of all accreted systems were pre-processed prior to infall, and about 20 per cent were accreted in groups. We confirm that the entire population of accreted subhaloes -- often referred to as associated subhaloes -- extend far beyond the virial radii of their hosts, with roughly half currently residing at distances that exceed $approx 1.2times r_{200}$. Many of these backsplash haloes have gained orbital energy since infall, and occupy extreme orbits that carry them well past their initial turnaround radii. Such extreme orbits are created during the initial accretion and dissolution of loosely bound groups, but also through penetrating encounters between subhaloes on subsequent orbits. The same processes may also give rise to unexpectedly abrupt losses of orbital energy. These effects combine, giving rise to a large variation in the ratio of sequent apocentres for accreted systems. We find that, within 2 virial radii from host centres, the concentrations of first-infall halos are remarkably similar those of isolated field halos, whereas backsplash haloes, as well as systems that were pre-processed, are considerably more concentrated.
We present MeerKAT neutral hydrogen (HI) observations of the Fornax A group, that is likely falling into the Fornax cluster for the first time. Our HI image is sensitive to 1.4 x 10$^{19}$ cm$^{-2}$ over 44.1 km s$^{-1}$, where we detect HI in 10 galaxies and a total of 1.12 x 10$^{9}$ Msol of HI in the intra-group medium (IGM). We search for signs of pre-processing in the 12 group galaxies with confirmed optical redshifts that reside within our HI image. There are 9 galaxies that show evidence of pre-processing and we classify the pre-processing status of each galaxy, according to their HI morphology and gas (atomic and molecular) scaling relations. Galaxies yet to experience pre-processing have extended HI disks, a high HI content with a H$_2$-to-HI ratio an order of magnitude lower than the median for their stellar mass. Galaxies currently being pre-processed display HI tails, truncated HI disks with typical gas ratios. Galaxies in the advanced stages of pre-processing are HI deficient. If there is any HI, they have lost their outer HI disk and efficiently converted their HI to H$_2$, resulting in H$_2$-to-HI ratios an order of magnitude higher than the median for their stellar mass. The central, massive galaxy in our group underwent a 10:1 merger 2 Gyr ago, and ejected 6.6 - 11.2 x 10$^{8}$ Msol of HI that we detect as clouds and streams in the IGM, some forming coherent structures up to 220 kpc in length. We also detect giant (100 kpc) ionised hydrogen (H$alpha$) filaments in the IGM, likely from cool gas being removed (and ionised) from an infalling satellite. The H$alpha$ filaments are situated within the hot halo of NGC 1316 and some regions contain HI. We speculate that the H$alpha$ and multiphase gas is supported by magnetic pressure (possibly assisted by the AGN), such that the hot gas can condense and form HI that survives in the hot halo for cosmological timescales.
The PyProcar Python package plots the band structure and the Fermi surface as a function of site and/or s,p,d,f - projected wavefunctions obtained for each $k$-point in the Brillouin zone and band in an electronic structure calculation. This can be performed on top of any electronic structure code, as long as the band and projection information is written in the PROCAR format, as done by the VASP and ABINIT codes. PyProcar can be easily modified to read other formats as well. This package is particularly suitable for understanding atomic effects into the band structure, Fermi surface, spin texture, etc. PyProcar can be conveniently used in a command line mode, where each one of the parameters define a plot property. In the case of Fermi-surfaces, the package is able to plot the surface with colors depending on other properties such as the electron velocity or spin projection. The mesh used to calculate the property does not need to be the same as the one used to obtain the Fermi surface. A file with a specific property evaluated for each $k$-point in a $k-$mesh and for each band can be used to project other properties such as electron-phonon mean path, Fermi velocity, electron effective mass, etc. Another existing feature refers to the band unfolding of supercell calculations into predefined unit cells.
As the computing power of modern hardware is increasing strongly, pre-trained deep learning models (e.g., BERT, GPT-3) learned on large-scale datasets have shown their effectiveness over conventional methods. The big progress is mainly contributed to the representation ability of transformer and its variant architectures. In this paper, we study the low-level computer vision task (e.g., denoising, super-resolution and deraining) and develop a new pre-trained model, namely, image processing transformer (IPT). To maximally excavate the capability of transformer, we present to utilize the well-known ImageNet benchmark for generating a large amount of corrupted image pairs. The IPT model is trained on these images with multi-heads and multi-tails. In addition, the contrastive learning is introduced for well adapting to different image processing tasks. The pre-trained model can therefore efficiently employed on desired task after fine-tuning. With only one pre-trained model, IPT outperforms the current state-of-the-art methods on various low-level benchmarks. Code is available at https://github.com/huawei-noah/Pretrained-IPT and https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/IPT
We present a study of the spatial distribution and kinematics of star-forming galaxies in 30 massive clusters at 0.15<z<0.30, combining wide-field Spitzer 24um and GALEX NUV imaging with highly-complete spectroscopy of cluster members. The fraction (f_SF) of star-forming cluster galaxies rises steadily with cluster-centric radius, increasing fivefold by 2r200, but remains well below field values even at 3r200. This suppression of star formation at large radii cannot be reproduced by models in which star formation is quenched in infalling field galaxies only once they pass within r200 of the cluster, but is consistent with some of them being first pre-processed within galaxy groups. Despite the increasing f_SF-radius trend, the surface density of star-forming galaxies actually declines steadily with radius, falling ~15x from the core to 2r200. This requires star-formation to survive within recently accreted spirals for 2--3Gyr to build up the apparent over-density of star-forming galaxies within clusters. The velocity dispersion profile of the star-forming galaxy population shows a sharp peak of 1.44-sigma_v at 0.3r500, and is 10--35% higher than that of the inactive cluster members at all cluster-centric radii, while their velocity distribution shows a flat, top-hat profile within r500. All of these results are consistent with star-forming cluster galaxies being an infalling population, but one that must also survive ~0.5--2Gyr beyond passing within r200. By comparing the observed distribution of star-forming galaxies in the stacked caustic diagram with predictions from the Millennium simulation, we obtain a best-fit model in which SFRs decline exponentially on quenching time-scales of 1.73pm0.25 Gyr upon accretion into the cluster.
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