A3: If the question means: where can I find the spectra of the sky (+telescope) then for chop-nod observations these are the spectra taken in the off-chop positions. The easiest way to see these data is to run the script Split On-Off, which you find in the HIPE Pipelines menu (Spectroscopy->both chopped menus -> Split On-Off. This is also explained in the pipeline chapters (chp 3) of the PACS Data Reduction Guide. This script will produce separate cubes of the on-source spectra and the off-source spectra.

Q4: can you subtract a baseline to spectra? Could it be included in the script?

A4: The currently best documented way is to fit the continuum with a poly and then get the residual (data - fit). This is explained in chapter 7 of the "Data Analysis Guide" (about the SpectrumFitter and SpectrumFitterGUI), which you can get via the HIPE Help->Help contents menu. The baseline fitter is a PACS specific task that you can also use but it is not well documented. This takes the data and identifies where the baseline is, i.e. it ignores lines, and then that baseline can be subtracted from the spectrum. If someone wants to use this task, or know more details, then please raise a helpdesk ticket to ask specifically for that.

Q5: is the split on-off applicable to unchopped observations?

A5: For the unchopped line scan mode, the off-source spectra are separated out from the on-source spectra within the pipeline (it will be very clear when this happens as you follow the interactive pipeline script Spectroscopy->unchopped line scan->"lineScan") and you can then compare them by plotting them together (this is also explained in the PDRG pipeline chap 4 and some additional information in chp 8). For the unchopped range scan, on and off (ie source and sky) are separate observations and once you have reduced each through to Level 2, you can compare them e.g. as cubes in the Spectrum Explorer.

Q&A

PACS Spectroscopy

Q1: I have a rather specific question. I am reducing unchopped line scans. I use oversample=2 and I get a warning for the specwaveRebinTask (not enough good values etc, try oversample=1). However when I look at the final result (end interactive L2) there doesn't seem to be a problem, for instance in the plotCubesStdev display there are only low exposure pixels at the edges. Is this something to worry about? I hope I managed to explain this clearly enough....

A1: Hi xxx, in many pipeline tasks you get warning messages (actually, many are just information, but the developers seem to like to scare people with WARNING!! comments ;-). so at first glance your message seems to be just a kind warning. if the end result looks ok then you don't need to worry. there is a task at the end of the pipeline that plots little yellow? squares on the bins that are "low exposure". If these are all at the end of the spectral range, you don't need to worry. In fact, yes, the task plotStdDev is the one that tells you which bins are low exposure. so it looks like you do not need to worry. but you can also change the wavelength grid up/over sample values and overplot the different end results to compare. More about up and over sampling is in the PDRG chapter…5 or 6 or 7, I forgot, and more about comparing spectra at the end of the pipeline is also in the PDRG (chap 5 or 6 or 7 also - a section that talks about flatfielding), or use the spectrum explorer.

Q2: can I use data cubes that we get from the archive for spectroscopic AND photometric studies?

A2: well, if you have enough continuum in your cube then you can of course use it for photometry. the question is "what is enough". The thing to remember is that the continuum you get at the end of the pipeline is subject to ± error. This error depends on the strength of your source with respect to the teelscope. The telescope spectrum is some 100 Jy or so, and so even 1% error is a ± error of 1 Jy in the continuum. In the calibration document that is on the pacs calibration and instrument wiki the errors for the end cubes are given. ± a few Jy you should expect will be the error in the continuum level. http://herschel.esac.esa.int/twiki/pub/Public/PacsCalibrationWeb/PacsSpectroscopyPerformanceAndCalibration_v2_4.pdf For full science quality you need to re-pipeline the data - take advantage of the latest calibrations as the HSA products don't run all the pipeline tasks. This is documented in chp 1 of the PDRG. You can get fluxes (Jy/spaxel) and wavelengths (microns). Though the fits files do have a rather awkward format. They can be hard to read directly into other software - we are working on this and if you have problems it is fastest to raise a helpdesk ticket. One last thing: for unchopped mode, the flux level of the continuum is not guaranteed to be correct. That mode was never intended for continuum studies.

PACS Photometry

Q1:

A1:

...

• PACSspec_demo_kexter_v2.pdf: PACSspec_demo_kexter_v2.pdf

• PACSspec_demo_kexter_v2.py.txt: PACSspec_demo_kexter_v2.py.txt

• PSF_comp.py.txt: PSF subtraction script by Zoltan Balog

SPIRE Photometry tutorials

• Remove_CoolerBurp.py.txt: tutorial to remove booler burp from affected observations

• MapMerged_TAR.py.txt: tutorial to merge 2 (or more) observations and calculate the absolute offset from cross-calibration with Planck.
  • The script assumes you have the 2 parallel mode observations of Rosette Nebula (1342186121, 1342186122) copied on your hard drive.
  • You also need to copy the following files in the same directory: DX9_map_545_smooth_8arcmin.fits, DX9_map_857_smooth_8arcmin.fits and SpireHfiColourCorrTab_v1.1.fits

• Remove_Glitches.py.txt: tutorial to find and remove undetected glitched from maps

• SPIRE_Photometry.py.txt: tutorial running different photometry algorithm on the calibration star Gamma Dra

(NOTE: you may need to remove the .txt from the filenames associated to the python scripts above so that these files can be recognized as python scripts by HIPE - the .txt suffix is added automatically by the twiki for security reasons)