; BSMAP ;--------------------------------------------------------------- ;! images weak sources with closure phases ;# Task Imaging ;----------------------------------------------------------------------- ;; Copyright (C) 1995, 2008 ;; Associated Universities, Inc. Washington DC, USA. ;; ;; This program is free software; you can redistribute it and/or ;; modify it under the terms of the GNU General Public License as ;; published by the Free Software Foundation; either version 2 of ;; the License, or (at your option) any later version. ;; ;; This program is distributed in the hope that it will be useful, ;; but WITHOUT ANY WARRANTY; without even the implied warranty of ;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ;; GNU General Public License for more details. ;; ;; You should have received a copy of the GNU General Public ;; License along with this program; if not, write to the Free ;; Software Foundation, Inc., 675 Massachusetts Ave, Cambridge, ;; MA 02139, USA. ;; ;; Correspondence concerning AIPS should be addressed as follows: ;; Internet email: aipsmail@nrao.edu. ;; Postal address: AIPS Project Office ;; National Radio Astronomy Observatory ;; 520 Edgemont Road ;; Charlottesville, VA 22903-2475 USA ;----------------------------------------------------------------------- BSMAP LLLLLLLLLLLLUUUUUUUUUUUU CCCCCCCCCCCCCCCCCCCCCCCCCCCCC BSMAP Task for Bi-Spectrum imaging of simple, weak objects INNAME Input UV file name (name) INCLASS Input UV file name (class) INSEQ 0.0 9999.0 Input UV file name (seq. #) INDISK 0.0 9.0 Input UV file disk unit # OUTNAME Output image name (name) OUTSEQ -1.0 9999.0 Output image name (seq. #) OUTDISK 0.0 9.0 Output image disk unit #. IMSIZE 3.0 21.0 Image size CELLSIZE 0.00001 Cell size in arcseconds ERROR 0.0 Error per weight in uv data UVWT Weighting 'UN' => uniform, else natural DETIME 0.0 Vector averaging time (mins) ---------------------------------------------------------------- BSMAP Task: This will perform bi-spectrum imaging of weak objects for which self-cal is required but not possible. It replaces the combination of ASCAL, UVSRT and MX. NOTE: this task does NOT apply flagging or calibration tables to the input UV data. Run SPLIT first if that operation is desired. Adverbs: INNAME.....Input UV file name (name). Standard defaults. The sort order must be 'TB'. INCLASS....Input UV file name (class). Standard defaults. INSEQ......Input UV file name (seq. #). 0 => highest. INDISK.....Disk drive # of input UV file. 0 => any. OUTNAME....Output image file name (name). Standard defaults. OUTCLASS...Output image file name (class). Standard defaults. OUTSEQ.....Output image file name (seq. #). 0 => highest unique. OUTDISK....Disk drive # of output image file. 0 => highest with space for the file. IMSIZE.....Sizes of output images in pixels CELLSIZE...Cell sizes of output images in arcseconds ERROR......Error per weight in uv data in Jy UVWT.......Weighting 'UN' => uniform, else natural DETIME.....Vector averaging time for input visibilities (min) 0 = > 1/6 minute. ---------------------------------------------------------------- Task: BSMAP Purpose: Bi-Spectrum imaging of simple, weak objects Programmer: T.J. Cornwell Documentor: T.J. Cornwell Date of Documentation: 8 Jul 1986 Version: 15OCT86 Related Programs: None INTRODUCTION: BSMAP will image simple objects which are too weak for self-calibration. Generally, this means objects for which the visibility is comparable or less than the noise in an atmospheric coherence time. BSMAP does not attempt to estimate the atmospheric phase error at each antenna, instead it averages the Bi-Spectrum (hence the name), onto a very coarse grid. The bi-spectrum is a function of two pairs of (u,v) coordinates and is the triple product of three visibilities around a loop of three antennas specified by the coordinates. The phase part is just the closure phase, which self-calibration exploits. BSMAP is then just a smart way of averaging the closure phase for many atmospheric coherence times to build up signal to noise. The Bi-Spectrum data is analyzed in two ways: 1. The complete Bi-Spectrum is averaged to find the best estimate of the flux of any point source present. This is more sensitive than the second method, in which an image is formed. 2. After the averaged bi-spectrum is formed from the data, the corresponding visibility function is found by a least-squares fit. This visibility function is then inverted to form an image. A beam is also output. Only very small images can be supported at the moment, but this may change sometime. The image classes are 'BSMAP' and 'BSBEAM' respectively. Sometimes this fit will fail; this is a very good indication that either no source is present or that it really is buried in the noise. The gridding used is simple cell-summing so don't expect the dynamic range to be great. About a few hundred to one for a 21**2 pixel image and 20,000 visibilities is reasonable. Noise will probably kick in before this limit anyway. ******* Note that all positional information is lost *******. Unlike ASCAL, BSMAP has no input positional reference frame to refer to. Roughly speaking the centriod of emission is shifted to the center of the field. The resulting map and beam can be cleaned using APCLN. Use LGEOM to expand the images to, say 64**2 pixels, and then use APCLN. Remember to restrict the box to less than half the BSMAP image size e.g. for 21*21 BSMAP images you can only CLEAN a 10*10 box! IMSIZE: BSMAP can only estimate very small images at the moment. The gridding of the data is related to the image size: smaller images cause more averaging of the bi-spectrum and thus, in marginal cases, image size can be traded off against SNR. The current limit in image size is =< 21**2 pixels split between the two axes. CELLSIZE: In view of the poor SNR of most data which will be passed through BSMAP, fairly coarse grids can be used, say 2 pixels per beam. BSMAP will tell you how many points fall off the edge of the grid so you could adjust to keep this small. UVWT: The final image and beam can be naturally or uniformly weighted. Natural weighting is the default, and is, of course, recommended for weak sources. DETIME: The input visibilities can be averaged coherently before forming the bi-spectrum. This will help the SNR considerably. DETIME must be less than the atmospheric coherence time! ERROR: ERROR is the expected noise per weight per complex correlator. It is not really very critical so the default of 25 mJy per weight will probably do for most VLA data except 1.3cm. COMMENTS: This is an extremely experimental task. Please talk to Tim Cornwell about any problems you encounter. RUNNING TIME: Currently about 15 minutes of CPU time for about 200,000 visibilities. This may seem a lot but remember: BSMAP replaces several passes of (ASCAL, UVSRT, MX). Large amounts of core are used. For large images on a VAX some paging will undoubtedly occur. 15*15 pixel images require about 1000 pages working set.