1 | \secA{Introduction and getting going quickly} |
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2 | |
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3 | This document provides a user's guide to \duchamp, an object-finder |
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4 | for use on spectral-line data cubes. The basic execution of \duchamp\ |
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5 | is to read in a FITS data cube, find sources in the cube, and produce |
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6 | a text file of positions, velocities and fluxes of the detections, as |
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7 | well as a postscript file of the spectra of each detection. |
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8 | |
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9 | So, you have a FITS cube, and you want to find the sources in it. What |
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10 | do you do? First, you need to get \duchamp: there are instructions in |
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11 | Appendix~\ref{app-install} for obtaining and installing it. Once you |
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12 | have it running, the first step is to make an input file that contains |
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13 | the list of parameters. Brief and detailed examples are shown in |
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14 | Appendix~\ref{app-input}. This file provides the input file name, the |
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15 | various output files, and defines various parameters that control the |
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16 | execution. |
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17 | |
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18 | The standard way to run \duchamp\ is by the command |
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19 | \begin{quote} |
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20 | \texttt{Duchamp -p [parameter file]} |
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21 | \end{quote} |
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22 | replacing \texttt{[parameter file]} with the name of the file listing |
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23 | the parameters. |
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24 | |
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25 | An even easier way is to use the default values for all parameters |
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26 | (these are given in Appendix~\ref{app-param} and in the file |
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27 | InputComplete included in the distribution directory) and use the |
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28 | syntax |
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29 | \begin{quote} |
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30 | \texttt{Duchamp -f [FITS file]} |
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31 | \end{quote} |
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32 | where \texttt{[FITS file]} is the file you wish to search. |
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33 | |
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34 | In either case, the program will then work away and give you the list |
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35 | of detections and their spectra. The program execution is summarised |
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36 | below, and detailed in \S\ref{sec-flow}. Information on inputs is in |
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37 | \S\ref{sec-param} and Appendix~\ref{app-param}, and descriptions of |
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38 | the output is in \S\ref{sec-output}. |
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39 | |
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40 | \secB{A summary of the execution steps} |
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41 | |
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42 | The basic flow of the program is summarised here -- all steps are |
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43 | discussed in more detail in the following sections. |
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44 | \begin{enumerate} |
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45 | \item If the \texttt{-p} option is used, the parameter file given on |
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46 | the command line is read in, and the parameters absorbed. |
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47 | \item The FITS image is located and read in to memory. |
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48 | \item If requested, a FITS image with a previously reconstructed array |
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49 | is read in. |
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50 | \item If requested, BLANK pixels are trimmed from the edges, and |
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51 | the baseline of each spectrum is removed. |
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52 | \item If the reconstruction method is requested, and the reconstructed |
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53 | array has not been read in at Step 3 above, the cube is |
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54 | reconstructed using the \atrous\ wavelet method. |
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55 | \item Searching for objects then takes place, using the requested |
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56 | thresholding method. |
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57 | \item The list of objects is condensed by merging neighbouring objects |
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58 | and removing those deemed unacceptable. |
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59 | \item The baselines and trimmed pixels are replaced prior to output. |
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60 | \item The details of the detections are written to screen and to the |
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61 | requested output file. |
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62 | \item Maps showing the spatial location of the detections are written. |
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63 | \item The integrated spectra of each detection are written to a |
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64 | postscript file. |
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65 | \item If requested, the reconstructed array can be written to a new |
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66 | FITS file. |
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67 | \end{enumerate} |
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68 | |
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69 | \secB{Guide to terminology and conventions} |
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70 | |
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71 | First, a brief note on the use of terminology in this guide. \duchamp\ |
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72 | is designed to work on FITS ``cubes''. These are FITS\footnote{FITS is |
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73 | the Flexible Image Transport System -- see \citet{hanisch01} or |
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74 | websites such as |
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75 | \href{http://fits.cv.nrao.edu/FITS.html}{http://fits.cv.nrao.edu/FITS.html} |
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76 | for details.} image arrays with three dimensions -- they are assumed |
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77 | to have the following form: the first two dimensions (referred to as |
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78 | $x$ and $y$) are spatial directions (that is, relating to the position |
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79 | on the sky), while the third dimension, $z$, is the spectral |
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80 | direction, which can correspond to frequency, wavelength, or |
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81 | velocity. The three dimensional analogue of pixels are ``voxels'', or |
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82 | volume cells -- a voxel is defined by a unique $(x,y,z)$ location and |
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83 | has a unique flux or intensity value associated with it. |
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84 | |
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85 | Note that it is possible for the FITS file to have more than three |
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86 | dimensions (for instance, a fourth dimension representing Stokes |
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87 | parameters). Only the two spatial dimensions and the spectral |
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88 | dimension are read into the array of pixel values that is searched for |
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89 | objects. All other dimensions are ignored\footnote{This actually means |
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90 | that the first pixel only of that axis is used, and the array is read |
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91 | by the \texttt{fits\_read\_subsetnull} command from the |
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92 | \textsc{cfitsio} library.}. Herein, we discuss the data in terms of |
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93 | the three basic dimensions, but you should be aware it is possible for |
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94 | the FITS file to have more than three. Note that the order of the |
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95 | dimensions in the FITS file does not matter. |
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96 | |
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97 | Each spatial pixel (a given $(x,y)$ coordinate) can be said to be a |
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98 | single spectrum, while a slice through the cube perpendicular to the |
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99 | spectral direction at a given $z$-value is a single channel (the 2-D |
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100 | image is a channel map). |
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101 | |
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102 | Detection involves locating a contiguous group of voxels with fluxes |
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103 | above a certain threshold. \duchamp\ makes no assumptions as to the |
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104 | size or shape of the detected features, other than having |
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105 | user-selected minimum size criteria. Features that are detected are |
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106 | assumed to be positive. The user can choose to search for negative |
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107 | features by setting an input parameter -- this inverts the cube prior |
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108 | to the search (see \S\ref{sec-detection} for details). |
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109 | |
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110 | Finally, note that it is possible to run \duchamp\ on a |
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111 | two-dimensional image (\ie one with no frequency or velocity |
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112 | information), or indeed a one-dimensional array, and many of the |
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113 | features of the program will work fine. The focus, however, is on |
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114 | object detection in three dimensions. |
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115 | |
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116 | \secB{Why \duchamp?} |
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117 | |
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118 | Well, it's important for a program to have a name, and the initial |
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119 | working title of \emph{cubefind} was somewhat uninspiring. I wanted to |
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120 | avoid the classic astronomical approach of designing a cute acronym, |
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121 | and since it is designed to work on cubes, I looked at naming it after |
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122 | a cubist. \emph{Picasso}, sadly, was already taken \citep{minchin99}, |
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123 | so I settled on naming it after Marcel Duchamp, another cubist, but |
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124 | also one of the first artists to work with ``found objects''. |
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125 | |
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