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Contents

• Contents
• 1. Synthesis Calibration
  • 1.1 Introduction
  • 1.2 Calibration philosophy
    • 1.2.1 The Measurement Equation
    • 1.2.2 Data representation and the calibration mechanism
    • 1.2.3 What are the current calibration capabilities in AIPS++?
  • 1.3 Practical use of the calibrater tool
    • 1.3.1 Setting up the calibrater tool
    • 1.3.2 Initial calibrator models
    • 1.3.3 Uv-data selection
    • 1.3.4 Calibration table conventions
    • 1.3.5 Solving for visibility-plane effects
    • 1.3.6 Establishing the flux density scale
    • 1.3.7 Correcting the observed data
    • 1.3.8 Extending calibration to bandpass, polarization, etc.
    • 1.3.9 Self-calibration
  • 1.4 References
• 2. Imaging, Deconvolution and Self-calibration
  • 2.1 Overview
    • 2.1.1 Required Tools
    • 2.1.2 Data Requirements
  • 2.2 Setting up Imager
    • 2.2.1 Construction
    • 2.2.2 Selecting Data
    • 2.2.3 Setting the Image Parameters
    • 2.2.4 Channel Selection and Combination
    • 2.2.5 Weighting
  • 2.3 Creating and Deconvolving Images
    • 2.3.1 Creating Images
    • 2.3.2 Deconvolution
    • 2.3.3 Specifying the deconvolution region
  • 2.4 Wizard interface to Imager
  • 2.5 Component Models and Primary Beams
  • 2.6 Multi-scale CLEAN
    • 2.6.1 General
    • 2.6.2 The imagermultiscale() function
  • 2.7 Wide-field imaging and Mosaicing
  • 2.8 Combining single dish and interferometer images
  • 2.9 Self-calibration
  • 2.10 Summary of Imager functions
    • 2.10.1 Setting/seeing the basic state
    • 2.10.2 uv selection and filtering
    • 2.10.3 Masking
    • 2.10.4 Create images
    • 2.10.5 Deconvolution
    • 2.10.6 Image Combination
    • 2.10.7 Utility
    • 2.10.8 Calibration and self-calibration
  • 2.11 Examples of Imaging Scripts
    • 2.11.1 Multi-frequency synthesis image of one field
    • 2.11.2 Multiple regions on the sky simultaneously
    • 2.11.3 Spectral-line imaging
    • 2.11.4 Using Clean and MEM
    • 2.11.5 Deconvolver and multi-scale CLEAN example
    • 2.11.6 Imaging and Self-Calibrating
• 3. Wide field imaging
  • 3.1 Background
    • 3.1.1 Possible solution to the wide-field imaging problem
  • 3.2 Available Tools
    • 3.2.1 Basic capabilities
    • 3.2.2 Faceting size
    • 3.2.3 Deconvolution
    • 3.2.4 Self-calibration
    • 3.2.5 Masking
    • 3.2.6 Outlier fields
    • 3.2.7 Models
  • 3.3 A worked example: VLA 4m imaging of Coma
  • 3.4 Special cases
  • 3.5 Troubleshooting
    • 3.5.1 Insufficient faceting
    • 3.5.2 Non-isoplanatism
    • 3.5.3 Asymmetric primary beams
    • 3.5.4 Clean diverging on the edges of the facets
  • 3.6 Bibliography
• 4. Mosaicing (Multi-field imaging)
  • 4.1 Mosaicing Background
    • 4.1.1 The AIPS++ Mosaicing Solution
    • 4.1.2 Advantages of Incremental Deconvolution with an Approximate PSF
  • 4.2 Mosaicwizard for Quick, Simple Mosaicing
  • 4.3 Fundamental and Necessary Details
    • 4.3.1 Set the Data Fields
    • 4.3.2 Set the Image
    • 4.3.3 Setting the Voltage Pattern (primary beam)
    • 4.3.4 Weighting
    • 4.3.5 Deconvolving
  • 4.4 Advanced Details
    • 4.4.1 Controlling the Major Cycles
    • 4.4.2 Details with Multi-Scale CLEAN
    • 4.4.3 The imagermultiscale() Function
    • 4.4.4 Details with MEM
    • 4.4.5 Using Convolutions Instead of Visibility Subtraction
    • 4.4.6 Outlier Fields
    • 4.4.7 Component Models
    • 4.4.8 Flux Scale Images
    • 4.4.9 Masks
  • 4.5 Self-calibration
  • 4.6 An Example Mosaicing Script
  • 4.7 Bibliography
• 5. GBT Continuum Single dish Imaging
  • 5.1 Introduction
  • 5.2 Filling single dish data into AIPS++
    • 5.2.1 GBT
    • 5.2.2 Loading the continuum calibration utilities
  • 5.3 Data examination and inspection
  • 5.4 Basic gain calibration
    • 5.4.1 gc.setdata(msname)
    • 5.4.2 gc.contcal(tcal=1.0,average=T,baseline=F,nfit=0,range=20)
  • 5.5 Imaging
    • 5.5.1 gc.makeimage(imname='scanimage',gridfn='SF',receptor=1)
    • 5.5.2 gc.covercorr(imname=F,wname=F)
    • 5.5.3 gc.plotsource(imname,nsource=1)
  • 5.6 Example
• 6. Single Dish Analysis
  • 6.1 Introduction
  • 6.2 Getting Data Into Dish
    • 6.2.1 MeasurementSets
    • 6.2.2 Facility filler (e.g., GBT)
    • 6.2.3 SDFITS data file (e.g., Arecibo Observatory)
    • 6.2.4 UniPOPS SDD data file
    • 6.2.5 Dish demo data
  • 6.3 The Dish Graphical User Interface
    • 6.3.1 Results Manager
    • 6.3.2 Menubar and Message Line
    • 6.3.3 Browsing
    • 6.3.4 Inspecting
    • 6.3.5 Operations
  • 6.4 Saving/Restoring State
  • 6.5 The Dish Plotter
  • 6.6 The Dish Command Line Interface
  • 6.7 Recipes
    • 6.7.1 Recipe 1: Change syntax to suit
    • 6.7.2 Recipe 3: Add a function to DISH (or fun with extensibility)
  • 6.8 sditerator
  • 6.9 SDFITS
    • 6.9.1 EXTNAME keyword
    • 6.9.2 Virtual columns
    • 6.9.3 The DATA column and the DATA axes
    • 6.9.4 CORE keywords and columns
    • 6.9.5 SHARED keywords and columns
    • 6.9.6 Other columns
    • 6.9.7 Multiple SDFITS tables in a single file