اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدWINGS: a WIde-field Nearby Galaxy-cluster Survey. I - Optical imaging
117
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
This is the first paper of a series that will present data and scientific results from the WINGS project, a wide-field, multiwavelength imaging and spectroscopic survey of galaxies in 77 nearby clusters. The sample was extracted from the ROSAT catalogs with constraints on the redshift (0.04<z<0.07) and distance from the galactic plane (|b|>20). The global goal of the WINGS project is the systematic study of the local cosmic variance of the cluster population and of the properties of cluster galaxies as a function of cluster properties and local environment. This data collection will allow to define a local Zero-Point reference against which to gauge the cosmic evolution when compared to more distant clusters. The core of the project consists of wide-field optical imaging of the selected clusters in the B and V bands. We have also completed a multi-fiber, medium resolution spectroscopic survey for 51 of the clusters in the master sample. In addition, a NIR (JK) survey of ~50 clusters and an H_alpha + UV survey of some 10 clusters are presently ongoing, while a very-wide-field optical survey has also been programmed. In this paper we briefly outline the global objectives and the main characteristics of the WINGS project. Moreover, the observing strategy and the data reduction of the optical imaging survey (WINGS-OPT) are presented. We have achieved a photometric accuracy of ~0.025mag, reaching completeness to V~23.5. Field size and resolution (FWHM) span the absolute intervals (1.6-2.7)Mpc and (0.7-1.7)kpc, respectively, depending on the redshift and on the seeing. This allows the planned studies to get a valuable description of the local properties of clusters and galaxies in clusters.
قيم البحث
اقرأ أيضاً
Aims. We present the results from a comprehensive spectroscopic survey of the WINGS (WIde-field Nearby Galaxy-cluster Survey) clusters, a program called WINGS-SPE. The WINGS-SPE sample consists of 48 clusters, 22 of which are in the southern sky and
26 in the north. The main goals of this spectroscopic survey are: (1) to study the dynamics and kinematics of the WINGS clusters and their constituent galaxies, (2) to explore the link between the spectral properties and the morphological evolution in different density environments and across a wide range in cluster X-ray luminosities and optical properties. Methods. Using multi object fiber fed spectrographs, we observed our sample of WINGS cluster galaxies at an intermediate resolu- tion of 6-9 A and, using a cross-correlation technique, we measured redshifts with a mean accuracy of about 45 km/s. Results. We present redshift measurements for 6137 galaxies and their first analyses. Details of the spectroscopic observations are reported. The WINGS-SPE has about 30% overlap with previously published data sets, allowing us to do both a complete comparison with the literature and to extend the catalogs. Conclusions. Using our redshifts, we calculate the velocity dispersion for all the clusters in the WINGS-SPE sample. We almost trip- licate the number of member galaxies known in each cluster with respect to previous works. We also investigate the X-ray luminosity vs. velocity dispersion relation for our WINGS-SPE clusters, and find it to be consistent with the form Lx proportional to sigma^4.
We have used the Westerbork array to carry out an unbiased wide-field survey for HI emission features, achieving an RMS sensitivity of about 18 mJy/Beam at a velocity resolution of 17 km/s over 1800 deg^2 and between -1000 < V_Hel<+6500 km/s. The pri
mary data consists of auto-correlation spectra with an effective angular resolution of 49 FWHM. We detect 155 external galaxies in excess of 8 sigma in integrated HI flux density. Plausible optical associations are found within a 30 search radius for all but one of our HI detections in DSS images, although several are not previously cataloged or do not have published red-shift determinations. Twenty-three of our objects are detected in HI for the first time. We classify almost half of our detections as ``confused, since one or more companions is cataloged within a radius of 30 and a velocity interval of 400 km/s. We identify a handful of instances of significant positional offsets exceeding 10 kpc of unconfused optical galaxies with the associated HI centroid, possibly indicative of severe tidal distortions or uncataloged gas-rich companions. A possible trend is found for an excess of detected HI flux in unconfused galaxies within our large survey beam relative to that detected previously in smaller telescope beams, both as function of increasing distance and increasing gas mass. This may be an indication for a diffuse gaseous component on 100 kpc scales in the environment of massive galaxies or a population of uncataloged low mass companions. We use our galaxy sample to estimate the HI mass function from our survey volume. Good agreement is found with the HIPASS BGC results, but only after explicit correction for galaxy density variations with distance.
We present preliminary results from a wide field near-IR imaging survey that uses the Cambridge InfraRed Survey Instrument (CIRSI) on the 2.5m Isaac Newton Telescope (INT). CIRSI is a JH-band mosaic imager that contains 4 Rockwell 1024$^{2}$ HgCdTe d
etectors (the largest IR camera in existence), allowing us to survey approximately 4 deg^2 per night to H ~ 19. Combining CIRSI observations with the deep optical imaging from the INT Wide Field Survey, we demonstrate a reddening independent quasar selection technique based on the (g - z) / (z - H) color diagram.
We combine deep, wide-field near-IR and optical imaging to demonstrate a reddening-independent quasar selection technique based on identifying outliers in the (g-z) / (z-H) colour diagram. In three fields covering a total of ~0.7 deg^2 to a depth of
m_H~18, we identified 68 quasar candidates. Follow-up spectroscopy for 32 objects from this candidate list confirmed 22 quasars (0.86<z<2.66), five with significant IR excesses. 2 of 8 quasars from a subsample with U band observations do not exhibit UVX colours. From these preliminary results, we suggest that this combined optical and near-IR selection technique has a high selection efficiency (> 65% success rate), a high surface density of candidates, and is relatively independent of reddening. We discuss the implications for star/galaxy separation for IR based surveys for quasars. We provide the coordinate list and follow-up spectroscopy for the sample of 22 confirmed quasars.
[Abriged] Astronomical Wide Field Imaging performed with new large format CCD detectors poses data reduction problems of unprecedented scale which are difficult to deal with traditional interactive tools. We present here NExt (Neural Extractor): a ne
w Neural Network (NN) based package capable to detect objects and to perform both deblending and star/galaxy classification in an automatic way. Traditionally, in astronomical images, objects are first discriminated from the noisy background by searching for sets of connected pixels having brightnesses above a given threshold and then they are classified as stars or as galaxies through diagnostic diagrams having variables choosen accordingly to the astronomers taste and experience. In the extraction step, assuming that images are well sampled, NExt requires only the simplest a priori definition of what an object is (id est, it keeps all structures composed by more than one pixels) and performs the detection via an unsupervised NN approaching detection as a clustering problem which has been thoroughly studied in the artificial intelligence literature. In order to obtain an objective and reliable classification, instead of using an arbitrarily defined set of features, we use a NN to select the most significant features among the large number of measured ones, and then we use their selected features to perform the classification task. In order to optimise the performances of the system we implemented and tested several different models of NN. The comparison of the NExt performances with those of the best detection and classification package known to the authors (SExtractor) shows that NExt is at least as effective as the best traditional packages.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
