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Register a new userThe Clusters Hiding in Plain Sight (CHiPS) survey: CHIPS1911+4455, a Rapidly-Cooling Core in a Merging Cluster
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Added by
Taweewat Somboonpanyakul
Publication date
2021
fields
Physics
and research's language is
English
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We present high-resolution optical images from the Hubble Space Telescope, X-ray images from the Chandra X-ray Observatory, and optical spectra from the Nordic Optical Telescope for a newly-discovered galaxy cluster, CHIPS1911+4455, at z=0.485+/-0.005. CHIPS1911+4455 was discovered in the Clusters Hiding in Plain Sight (CHiPS) survey, which sought to discover galaxy clusters with extreme central galaxies that were misidentified as isolated X-ray point sources in the ROSAT All-Sky Survey. With new Chandra X-ray observations, we find the core (r=10 kpc) entropy to be 17+2-9 keV cm^2, suggesting a strong cool core, which are typically found at the centers of relaxed clusters. However, the large-scale morphology of CHIPS1911+4455 is highly asymmetric, pointing to a more dynamically active and turbulent cluster. Furthermore, the Hubble images reveal a massive, filamentary starburst near the brightest cluster galaxy (BCG). We measure the star formation rate for the BCG to be 140--190 Msun/yr, which is one of the highest rates measured in a central cluster galaxy to date. One possible scenario for CHIPS1911+4455 is that the cool core was displaced during a major merger and rapidly cooled, with cool, star-forming gas raining back toward the core. This unique system is an excellent case study for high-redshift clusters, where such phenomena are proving to be more common. Further studies of such systems will drastically improve our understanding of the relation between cluster mergers and cooling, and how these fit in the bigger picture of active galactic nuclei (AGN) feedback.
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We present optical follow-up observations for candidate clusters in the Clusters Hiding in Plain Sight (CHiPS) survey, which is designed to find new galaxy clusters with extreme central galaxies that were misidentified as bright isolated sources in the ROSAT All-Sky Survey catalog. We identify 11 cluster candidates around X-ray, radio, and mid-IR bright sources, including six well-known clusters, two false associations of foreground and background clusters, and three new candidates which are observed further with Chandra. Of the three new candidates, we confirm two newly discovered galaxy clusters: CHIPS1356-3421 and CHIPS1911+4455. Both clusters are luminous enough to be detected in the ROSAT All Sky-Survey data if not because of their bright central cores. CHIPS1911+4455 is similar in many ways to the Phoenix cluster, but with a highly-disturbed X-ray morphology on large scales. We find the occurrence rate for clusters that would appear to be X-ray bright point sources in the ROSAT All-Sky Survey (and any surveys with similar angular resolution) to be 2+/-1%, and the occurrence rate of clusters with runaway cooling in their cores to be <1%, consistent with predictions of Chaotic Cold Accretion. With the number of new groups and clusters predicted to be found with eROSITA, the population of clusters that appear to be point sources (due to a central QSO or a dense cool core) could be around 2000. Finally, this survey demonstrates that the Phoenix cluster is likely the strongest cool core at z<0.7 -- anything more extreme would have been found in this survey.
Motivated by the recent, serendipitous discovery of the densest known galaxy, M60-UCD1, we present two initial findings from a follow-up search, using the Sloan Digital Sky Survey, Subaru/Suprime-Cam and Hubble Space Telescope imaging, and SOuthern Astrophysical Research (SOAR)/Goodman spectroscopy. The first object discovered, M59-UCD3, has a similar size to M60-UCD1 (half-light radius of r_h ~ 20 pc) but is 40% more luminous (M_V ~ -14.6), making it the new densest-known galaxy. The second, M85-HCC1, has a size like a typical globular cluster (GC; r_h ~ 1.8 pc) but is much more luminous (M_V ~ -12.5). This hypercompact cluster is by far the densest confirmed free-floating stellar system, and is equivalent to the densest known nuclear star clusters. From spectroscopy, we find that both objects are relatively young (~9 Gyr and ~3 Gyr, respectively), with metal-abundances that resemble those of galaxy centers. Their host galaxies show clear signs of large-scale disturbances, and we conclude that these dense objects are the remnant nuclei of recently accreted galaxies. M59-UCD3 is an ideal target for follow-up with high-resolution imaging and spectroscopy to search for an overweight central supermassive black hole as was discovered in M60-UCD1. These findings also emphasize the potential value of ultra-compact dwarfs and massive GCs as tracers of the assembly histories of galaxies.
Obscuration and confusion conspire to limit our knowledge of the inner Milky Way. Even at moderate distances, the identification of stellar systems becomes compounded by the extremely high density of background sources. Here we provide a very revealing example of these complications by unveiling a large, massive, young cluster in the Sagittarius arm that has escaped detection until now despite containing more than 30 stars brighter than $G=13$. By combining Gaia DR2 astrometry, Gaia and 2MASS photometry and optical spectroscopy, we find that the new cluster, which we name Valparaiso~1, located at $sim2.3:$kpc, is about 75~Ma old and includes a large complement of evolved stars, among which we highlight the 4~d classical Cepheid CM~Sct and an M-type giant that probably represents the first detection of an AGB star in a Galactic young open cluster. Although strong differential reddening renders accurate parameter determination unfeasible with the current dataset, direct comparison to clusters of similar age suggests that Valparaiso~1 was born as one of the most massive clusters in the Solar Neighbourhood, with an initial mass close to $10^{4}:$M$_{odot}$.
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Recent years have seen fast development in synthesizing realistic human faces using AI technologies. Such fake faces can be weaponized to cause negative personal and social impact. In this work, we develop technologies to defend individuals from becoming victims of recent AI synthesized fake videos by sabotaging would-be training data. This is achieved by disrupting deep neural network (DNN) based face detection method with specially designed imperceptible adversarial perturbations to reduce the quality of the detected faces. We describe attacking schemes under white-box, gray-box and black-box settings, each with decreasing information about the DNN based face detectors. We empirically show the effectiveness of our methods in disrupting state-of-the-art DNN based face detectors on several datasets.
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