European ALMA operations: the interaction with and support to the users

The Atacama Large Millimetre/submillimetre Array (ALMA) is one of the largest and most complicated observatories ever built. Constructing and operating an observatory at high altitude (5000m) in a cost effective and safe manner, with minimal effect on the environment creates interesting challenges. Since the array will have to adapt quickly to prevailing weather conditions, ALMA will be operated exclusively in service mode. By the time of full science operations, the fundamental ALMA data product shall be calibrated, deconvolved data cubes and images, but raw data and data reduction software will be made available to users as well. User support is provided by the ALMA Regional Centres (ARCs) located in Europe, North America and Japan. These ARCs constitute the interface between the user community and the ALMA observatory in Chile. For European users the European ARC is being set up as a cluster of nodes located throughout Europe, with the main centre at the ESO Headquarters in Garching. The main centre serves as the access portal and in synergy with the distributed network of ARC nodes, the main aim of the ARC is to optimize the ALMA science output and to fully exploit this unique and powerful facility. The aim of this article is to introduce the process of proposing for observing time, subsequent execution of the observations, obtaining and processing of the data in the ALMA epoch. The complete end-to-end process of the ALMA data flow from the proposal submission to the data delivery is described.Comment: 7 pages, three figure

The correct estimate of the probability of false detection of the matched filter in the detection of weak signals. II. (Further results with application to a set of ALMA and ATCA data)

The matched filter (MF) is one of the most popular and reliable techniques to the detect signals of known structure and amplitude smaller than the level of the contaminating noise. Under the assumption of stationary Gaussian noise, MF maximizes the probability of detection subject to a constant probability of false detection or false alarm (PFA). This property relies upon a priori knowledge of the position of the searched signals, which is usually not available. Recently, it has been shown that when applied in its standard form, MF may severely underestimate the PFA. As a consequence the statistical significance of features that belong to noise is overestimated and the resulting detections are actually spurious. For this reason, an alternative method of computing the PFA has been proposed that is based on the probability density function (PDF) of the peaks of an isotropic Gaussian random field. In this paper we further develop this method. In particular, we discuss the statistical meaning of the PFA and show that, although useful as a preliminary step in a detection procedure, it is not able to quantify the actual reliability of a specific detection. For this reason, a new quantity is introduced called the specific probability of false alarm (SPFA), which is able to carry out this computation. We show how this method works in targeted simulations and apply it to a few interferometric maps taken with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Australia Telescope Compact Array (ATCA). We select a few potential new point sources and assign an accurate detection reliability to these sources.Comment: 28 pages, 20 figures, Astronomy & Astrophysics, Minor changes and some typos correcte

Type 1 AGN and their Link to ULIRGS

Increasing observational evidence supports a picture for a close link among AGN phenomenum, star-formation processes and galaxy formation. Since the physical phenomena related to the onset of both AGN and star formation are very likely characterized by a strong far infrared (FIR) emission it becomes mandatory to investigate the FIR energy domain. However, because of their faintness in the FIR energy range, very little is known about the FIR properties of type 1 AGN, and type 2 AGN, which are supposed to be missed in classical searches, still lack definition and samples. Our aim is to investigate the FIR properties of optically selected type 1 AGN, compare them to Ultraluminous Infrared Galaxies (ULIRGs) and derive some general characteristics of the population. Expectations for future surveys are also presented.Comment: 6 pages, in "Issues in unifications of AGNs" Marciana Marina, May 2001; eds. R. Maiolino, A. Marconi and N. Naga

How many active galaxies and QSOs will future Space Missions detect?

Averaged spectral energy distributions (SEDs) of active and starburst galaxies from the 12 micron sample in the Local Universe and Quasars, from an optically selected sample at a mean redshift =0.7, are built from optical/near-IR/far-IR (IRAS & ISO) photometric observations. These SEDs are then used to predict at various redshifts the number of Seyfert type 1 and type 2, starburst, normal galaxies, and quasars, that will be detected by future Space Missions dedicated to far-infrared and submillimeter astronomy, like SIRTF and Herschel. These predictions are then compared with the expected capabilities and detection limits of future deep far-IR surveys. Possible ways to identify AGN candidates on far-IR colour-colour plots for follow-up observations are then explored.Comment: accepted in Ap

Matched filter in the low-number count Poisson noise regime: an efficient and effective implementation

The matched filter (MF) is widely used to detect signals hidden within the noise. If the noise is Gaussian, its performances are well-known and describable in an elegant analytical form. The treatment of non-Gaussian noises is often cumbersome as in most cases there is no analytical framework. This is true also for Poisson noise which, especially in the low-number count regime, presents the additional difficulty to be discrete. For this reason in the past methods have been proposed based on heuristic or semi-heuristic arguments. Recently, an analytical form of the MF has been introduced but the computation of the probability of false detection or false alarm (PFA) is based on numerical simulations. To overcome this inefficient and time consuming approach we propose here an effective method to compute the PFA based on the saddle point approximation (SA). We provide the theoretical framework and support our findings by means of numerical simulations. We discuss also the limitations of the MF in practical applications.Comment: 5 pages, 9 figures , accepted for publication in A&