Ultra-deep K-band Imaging of the Hubble Frontier Fields

Galaxie

Ultra-deep K-band Imaging of the Hubble Frontier Fields

We present an overview of the "KIFF" project, which provides ultra-deep Ks-band imaging of all six of the Hubble Frontier Fields clusters Abell 2744, MACS-0416, Abell S1063, Abell 370, MACS-0717 and MACS-1149. All of these fields have recently been observed with large allocations of Directors' Discretionary Time with the HST and Spitzer telescopes covering 0.4 < lambda < 1.6 microns and 3.6--4.5 microns, respectively. VLT/HAWK-I integrations of the first four fields reach 5-sigma limiting depths of Ks~26.0 (AB, point sources) and have excellent image quality (FWHM ~ 0."4). Shorter Keck/MOSFIRE integrations of the MACS-0717 (MACS-1149) field better observable in the north reach limiting depths Ks=25.5 (25.1) with seeing FWHM ~0."4 (0."5). In all cases the Ks-band mosaics cover the primary cluster and parallel HST/ACS+WFC3 fields. The total area of the Ks-band coverage is 490 arcmin^2. The Ks-band at 2.2 microns crucially fills the gap between the reddest HST filter (1.6 micron ~ H-band) and the IRAC 3.6 micron passband. While reaching the full depths of the space-based imaging is not currently feasible from the ground, the deep Ks-band images provide important constraints on both the redshifts and the stellar population properties of galaxies extending well below the characteristic stellar mass across most of the age of the universe, down to, and including, the redshifts of the targeted galaxy clusters (z < 0.5).Comment: Submitted to ApJS, includes revisions after the first referee report. Reduced mosaics of all six survey fields are provided via the ESO Phase 3 query form at http://www.eso.org/sci/observing/phase3/news.html#kif

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press