Echelle spectra reduction with IRAF* Giovanni Catanzaro INAF – Osservatorio Astrofisico di Catania Spring School of Spectroscopic Data Analyses 8-12 April 2013 Astronomical Institute of the University of Wroclaw Wroclaw, Poland 08/04/2013 Spectroscopic School of Data Analysis 1 Warning! This is not the “theory” (if any…) of spectra reduction. I show you just the main steps for the reduction of echelle spectra acquired with a fiber-fed spectrograph and I provide you with a “recipe” for “cooking” (extracting) your spectra * IRAF (Image Reduction and Analysis Facility) is distributed by the National Optical Astronomy Observatories, which is operated by the Association of the Universities for Research in Astronomy, inc. (AURA) under cooperative agreement with the National Science Foundation The art of cooking spectra with IRAF*
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Echelle spectra reduction with IRAF* Giovanni Catanzaro INAF – Osservatorio Astrofisico di Catania Spring School of Spectroscopic Data Analyses 8-12 April.
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Spectroscopic School of Data Analysis1
Echelle spectra reduction with IRAF*Giovanni Catanzaro
INAF – Osservatorio Astrofisico di Catania
Spring School of Spectroscopic Data Analyses8-12 April 2013
Astronomical Institute of the University of WroclawWroclaw, Poland
08/04/2013
Warning! This is not the “theory” (if any…) of spectra reduction. I show you just the main steps for the reduction of echelle spectra acquired with a fiber-fed spectrograph and I provide you with a “recipe” for “cooking” (extracting) your spectra
*IRAF (Image Reduction and Analysis Facility) is distributed by the National Optical Astronomy Observatories, which is operated by the Association of the Universities for Research in Astronomy, inc. (AURA) under cooperative agreement with the National Science Foundation
The art of cooking spectra with IRAF*
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What does reduction mean?
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We acquired images like this one
We want to extract normalized spectra like this one
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bias flat field lamp Calibration lamp objects
Typical images acquired during a night
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The reduction process
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The reduction process consists of a series of operations aimed at removing and/or taking into account the defects and the problems that affect the star signal, before the extraction of the stellar spectrum. These are due both to the optics and the detector.
Echelle orders
Scattered light
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Basic steps
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SCATTERED LIGHT SUBTRACTION
SPECTRA EXTRACTION
DIVISION BY FLAT SPECTRUM
WAVELENGTH CALIBRATION
NORMALIZATION TO THE CONTINUUM
OVERSCAN SUBTRACTION AND IMAGE TRIMMING
BIAS SUBTRACTION
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Bias
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Exposures with texp=0 sec and closed shutter We produce a “master” bias by averaging the individual bias frames in order to remove cosmic rays.zerocombine task
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Overscan removal
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The overscan level in ADUs is only an “offset” related to the electronics which reads out the CCD. Its value could slightly change from one line to the other due to very small variations in the reading conditions. We can account for this effect even if it is normally negligible. During this operation, performed with the task ccdproc, we can also trim the image leaving only the true pixels in the final image. The r.m.s of the overscan values is a good measure of the read-out noise in ADUs.
In this example we are performing in the same time the overscan and bias removal and the image trimming
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Preparing master Flat
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We average flat frames – which are indeed images of a continuum, featureless spectrum (tungstene or quartz lamp) - after the bias subtraction with the imcombine or flatcombine task
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Scattered light subtraction
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Scattered light is clearly seen between the spectral orders where the star signal is higher and the orders are closer; it can be due to several causes: dust grains, defects in the optics, spurious orders (ghosts), etc. that bring light away from its path. It can be removed to a very large extent.
scattered light contribution to the background
Background after subtraction
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Aperture finding and tracing
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We use the apscatter task inside the echelle package
We must tell IRAF where the spectral orders are, for evaluating the scattered light in the inter-order regions. The apscatter task allows us both to define the apertures (echelle orders) and to evaluate and subtract the scattered light
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Each aperture is traced by fitting the traced points with a Legendre polynomial
For HERMES spectra, I used an order n=7
This fitting has been done for all orders
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The level of scattered light is evaluated line by line by fitting the x-cuts where the echelle orders have been removed.
A new image, with the fits in each line is temporarily created
The vertical cuts of the new image containing the x-cut fits are taken and fitted with a spline. Thus, a 2-dimensional fit of the scattered light is performed and this “smooth” scatter image is subtracted to the original one.
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Since the fiber is in a fixed position, for all the other images we can do automatically the subtraction of scattered light taking the previous image (refstar) as a reference for the aperture parameters
Whenever the position of the star along the entrance slit changes, one must define the apertures for each individual image
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Spectra extraction
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For object frames: clean yes (Optimal extraction)
For flat field and Th-Ar frames: clean no
As for apscatter, for all the other objects we use an input list and extract automatically by choosing an image as aperture and a “profile” reference-frame (for cosmic ray rejection)
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The echelle blazing has been largely removed. It is much more easy and safe to define a continuum in this spectrum
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Wavelength calibration: ThAr (Ne) lamp
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We identify for each order some line and then we type “l” to automatically find additional lines in the spectrum, whose wavelength is contained into a file inside IRAF linelists$thar.dat
We type “f” to perform a fit of wavelength as a function of pixel number. In the plot the residuals (in Ǻ) are plotted
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We assign reference Th-Ar spectra with refspectra task
Dispcor is the task that corrects the dispersion and resample the spectra with a linear dispersion