echelle spectra reduction 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 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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Spring School of Spectroscopic Data Analyses 8-12 April 2013 Astronomical Institute of the University of Wroclaw Wroclaw, Poland. The art of cooking spectra with IRAF*. Echelle spectra reduction with IRAF*. - PowerPoint PPT Presentation

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Page 1: Echelle spectra reduction with IRAF*

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*

Page 2: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis2

What does reduction mean?

08/04/2013

We acquired images like this one We want to extract normalized spectra

like this one

Page 3: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis3 08/04/2013

bias flat field lamp Calibration lamp objects

Typical images acquired during a night

Page 4: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis4

The reduction process

08/04/2013

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

Page 5: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis5

Basic steps

08/04/2013

SCATTERED LIGHT SUBTRACTION

SPECTRA EXTRACTION

DIVISION BY FLAT SPECTRUM

WAVELENGTH CALIBRATION

NORMALIZATION TO THE CONTINUUM

OVERSCAN SUBTRACTION AND IMAGE TRIMMING

BIAS SUBTRACTION

Page 6: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis6

Bias

08/04/2013

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

Page 7: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis7

Overscan removal

08/04/2013

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

Page 8: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis8

Preparing master Flat

08/04/2013

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

Page 9: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis9

Scattered light subtraction

08/04/2013

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

Page 10: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis10

Aperture finding and tracing

08/04/2013

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

Page 11: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis11 08/04/2013

Page 12: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis12 08/04/2013

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

Page 13: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis13 08/04/2013

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.

Page 14: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis14 08/04/2013

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

Page 15: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis15

Spectra extraction

08/04/2013

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)

Page 16: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis16 08/04/2013

The echelle blazing has been largely removed. It is much more easy and safe to define a continuum in this spectrum

Page 17: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis17

Wavelength calibration: ThAr (Ne) lamp

08/04/2013

Page 18: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis18 08/04/2013

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

Page 19: Echelle spectra reduction with IRAF*

Spectroscopic School of Data Analysis19 08/04/2013

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

continuum task normalizes the spectra