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How do I analyse a PACS point source spectrum if my source is in the central spaxel?
Posted by Mark Kidger, Last modified by Mark Kidger on 14 September 2018 10:05 AM

Assuming that you have watched the Herschel Science Centre short videotutorial called Starting with PACS Spectroscopy:

https://www.youtube.com/watch?v=rcY487Z9Kyg 

And the Herschel Science Centre short videotutorial Point Source Spectroscopy with PACS:

https://www.youtube.com/watch?v=nYWTccEQz_M

Or, at least, are familiar with the contents of both short videotutorials and their associated documentation, you will find that the Herschel Science Centre short videotutorial on Point source spectroscopy with PACS: point sources in the central spaxel, which you can find here:

https://www.youtube.com/watch?v=_cVncMct3NE

will show you how to proceed if your point source is in the central spaxel itself. The short videotutorial will show you how to use the Product Decision Tree to decide which products and tools to use. This case is valid if you have a point source, with a pointed observation, in which the target is centred within the central spaxel, or for a mapping observation, in which, for one of the raster positions, the point source is centred within one of the eight spaxels surrounding the central spaxel. You will learn to identify cases for which the process may not work well (contamination, poorly centred point sources, ...) You will learn how to identify the spaxel coordinates of a source and which HIPE scripts and tasks to apply in the different possible cases. 

The short videotutorial will show you how to use the extractCentralSpectrum task, which is designed for these cases, how it operates and the corrections that it applies. It will show you how to decide which extraction to apply to the data (c1 - extracts from just the central spaxel, c9 - extracts from the central 3x3 (i.e. 9) spaxels , or c129 - which extracts both and scales the central spaxel to the central 3x3 spaxel box), given the various possible combinations of source flux and centering, although as a general guide, whichever extraction gives the highest flux is the best one to use.

You will see examples of extractions of data showing you what the different extractions show and how to select the most adequate one for you, as well as simple Quality Control checks to apply on the results. It will also show you what other documentation and scripts may be useful to you, as well as giving you indications on how you can do these analysis outside HIPE too.
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