TheHerschelVirgo Cluster Survey

Abstract

Aims. We present three independent catalogs of point-sources extracted from SPIRE images at 250, 350, and 500 µm, acquired with the Herschel Space Observatory as a part of the Herschel Virgo Cluster Survey (HeViCS). The catalogs have been cross-correlated to consistently extract the photometry at SPIRE wavelengths for each object. Methods. Sources have been detected using an iterative loop. The source positions are determined by estimating the likelihood to be a real source for each peak on the maps, according to the criterion defined in the sourceExtractorSussextractor task. The flux densities are estimated using the sourceExtractorTimeline, a timeline-based point source fitter that also determines the fitting procedure with the width of the Gaussian that best reproduces the source considered. Afterwards, each source is subtracted from the maps, removing a Gaussian function in every position with the full width half maximum equal to that estimated in sourceExtractorTimeline. This procedure improves the robustness of our algorithm in terms of source identification. We calculate the completeness and the flux accuracy by injecting artificial sources in the timeline and estimate the reliability of the catalog using a permutation method. Results. The HeViCS catalogs contain about 52 000, 42 200, and 18 700 sources selected at 250, 350, and 500 µm above 3σ and are ∼75%, 62%, and 50% complete at flux densities of 20 mJy at 250, 350, 500 µm, respectively. We then measured source number counts at 250, 350, and 500 µm and compare them with previous data and semi-analytical models. We also cross-correlated the catalogs with the Sloan Digital Sky Survey to investigate the redshift distribution of the nearby sources. From this crosscorrelation, we select ∼2000 sources with reliable fluxes and a high signal-to-noise ratio, finding an average redshift z ∼ 0.3 ± 0.22 and 0.25 (16-84 percentile). Conclusions. The number counts at 250, 350, and 500 µm show an increase in the slope below 200 mJy, indicating a strong evolution in number of density for galaxies at these fluxes. In general, models tend to overpredict the counts at brighter flux densities, underlying the importance of studying the Rayleigh-Jeans part of the spectral energy distribution to refine the theoretical recipes of the models. Our iterative method for source identification allowed the detection of a family of 500 µm sources that are not foreground objects belonging to Virgo and not found in other catalogs.

TheHerschelVirgo Cluster Survey

“…Its main advantage is the sensitivity and the uniformity of data: the 84 sq. deg of the survey have been observed with eight orthogonal cross scans, reaching at 250 µm a depth in flux density close to the confusion noise limit (see Pappalardo et al 2015). HeViCS has several advantages over other large Herschel surveys.…”

“…The catalog that we used as a starting point to construct our sample is the point source catalog of Pappalardo et al (2015) selected at 250 µm from HeViCS. This survey observed about 84 sq.…”

The WISSH quasars project

“…The input is the source position, a radius containing the source, and an aperture identifying the background annulus. Following the prescriptions of Pappalardo et al (2015), we set a search radius for the target of 22 , 30 , and 42 , at 250 µm, 350 µm, and 500 µm, respectively. For the background annulus we define a set of different apertures between 140 and 220 , and we estimate the background from the median of all the values recovered.…”

“…Following Pappalardo et al (2015), two fits were performed to the timeline data. The first fit was performed using a circular Gaussian function in which the FWHM was allowed to vary.…”

How did the Virgo cluster form?

“…Thus, it is probably the best known cluster (e.g. Binggeli & Huchra 2000;Wong & Kenney 2009;Roediger et al 2011a;Vollmer et al 2012;Roediger et al 2011b;Fritz & Hevics Collaboration 2011;Ferrarese et al 2012;Taylor et al 2012;Corbett Moran et al 2014;Karachentsev et al 2014;Pappalardo et al 2015;Grossauer et al 2015, for a non-extensive list). Its formation history however, and more particularly its assembly history, is not directly accessible via observations.…”