Data Reduction in the Optical and Infrared An …slai/Classes/Fundamentals...•A basic, general introduction to common steps and terms in optical/infrared imaging observations •

Data Reduction in the Optical and Infrared

An IntroductionJennifer Karr,

ASIAA

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• A basic, general introduction to common steps and terms in optical/infrared imaging observations

• Imaging only, no spectroscopy

• The details vary depending on the wavelength (optical, NIR, MIR), the telescope and the instrument

• If you are working with data, read the observers guide for that instrument and telescope

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Outline• Telescope Optics and Detectors

• Filters

• Basic Observing and Image Reduction

• Observing Strategies

• Photometry

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• light paths

• detectors and images

• Filters



• Photometry

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Telescope OpticsAn example (MacDonald Observatory)

Primary Mirror

Secondary Mirror

Instrumentation

Light Path

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Detectors

CCD: Charged Couple Device (optical)

A series of pixels in a grid. When a photon hits the detector, it creates an electron. We observe an exposure of time t. After the exposure is done, the number of electrons in each pixels is measured, or read out.

InSb, HbCdTe, Si:As: (infrared)

The technical details between optical, near-IR and mid-IR are different, but too much to go into now.

PhotonPixel

Detectors are generally cooled

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• Filters

• narrow band

• wide band

• photometric systems



• Photometry

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FiltersIn photometry we don’t measure a single wavelength: we measure light over a range of wavelengths or a passband

A single band is produced with the use of a filter which only lets light in a certain frequency range through.

A filter can be described by its spectral response function or the fraction of light transmitted by the filter at each wavelength

Spectral Response Function

Spitzer IRAC (mid-IR)

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FiltersThere are two main types of filters

Broad-band filters: pass light from a broad range of frequencies and are most useful in measuring continuum emission or broad features.

Narrow-band filters: pass light from a small range of frequencies, often centred on a spectral line (Hα)

Wide Field Camera (HST)

Narrow Band Filters

Broad Band Filters

IRAC (Spitzer)

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Photometric SystemsDifferent ways of naming filters/photometric bands

Standard Photometric Systems: Examples

Band Effective Wavelength

J 1.235 μm

H 1.662 μm

Ks 2.159 μm

2MASS


U 3600 ÅB 4400 ÅV 5500 ÅR 7100 ÅI 9700 ÅJ 1.25 μmH 1.60 μmK 2.22 μmL 3.54 μmM 4.80 μmN 10.6 μmO 21.0 μm

Johnson


1 3.6 μm

2 4.5 μm

3 5.8 μm

4 8 μm

Spitzer IRAC

Effective Wavelength: A measure of the central wavelength of the filter. Can also talk about Filter Width.

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Photometric SystemsWatch Out: The same letter usually means the same approximate wavelength, but the details differ between systems. This is important when comparing measurements!

Different telescopes and instruments often have their own definitions of the filters. In a paper the authors will specify which system they are using. You need to apply correction factors between systems.

For example: Johnson-Morgan, 2MASS, UKIRT, MIRLIN, SDSS, Kron, AB, Cousin, Strom, .....

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• Filters


• data from the telescope

• Artifacts

• dark current & flat fields

• bad pixels & cosmic rays

• ghosts & scattered light

• saturation

• the standard pipeline


• Photometry12

At the TelescopeThings you may observe at the telescope

- bias frames- dark current images- flat field images- sky frames- photometric references- data frames

Exactly what data you take at the telescope, and how you do it, depends on your science goals, the telescope, and the instrumentation you are using. Read the observers manual to be sure!

Calibration

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ArtifactsArtifact: a signal on the detector that is not part of the ‘true’ observation of the target

You want to avoid artifacts if possible, get rid of them if not, and suppress the effects if you can’t get rid of it completely.

The artifacts depend on - the location in the sky of the source you are observing - the brightness of the source - the length of the observation - the wavelength of the observations - the telescope and detectors used

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Dark Frames and BiasThe detector can read current and background noise as signal. Dark current refers to the background level of signal from the electronics etc. To measure this, we take a dark frame.

We take an exposure t seconds long with no light falling on the detector. Then we divide the image by t to get the dark current per pixel per second. This is the dark frame and it must be subtracted from other images.

The bias is a residual charge left on the detector and is a constant value To correct this, we take an image of 0s duration and subtract from the other images.

Example Dark Frame

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Flat FieldsThe sensitivity of individual pixels can vary. In addition, you can get effects in sensitivity due to the optics and light path in the telescope. To get rid of this we use a flat-field.

We expose using a blank, uniformly illuminated field, typically either a white sheet on the inside of the telescope dome (dome flat), or the sky just after sunset (sky flat). This image contains only the variation of the sensitivity of the pixels. We normalize (divide by the total flux) and we divide the other images by the flat field.

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Bad PixelsIndividual pixels in a detector can burn out (no signal) or become ‘hot’ (too much signal). We want to remove this effect. This is usually done with a mask of the CCD which has the bad pixels flagged. We then use software to interpolate over these bad pixels.

Bad pixels change with time: the older the detector, the more bad pixels (check for archived data)

There are standard routines to deal with this.

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Cosmic RaysCosmic rays are energetic elementary particles in space that can strike the detector, causing a signal. The longer the exposure the larger the number of cosmic ray events. This is worse at high altitudes or in space, where there is less shielding from the atmosphere

There are standard routines for cosmic ray removal: generally they use the pixel brightness to detect cosmic rays, as cosmic ray hits are very bright. As with bad pixels, we can interpolate over the cosmic rays.

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Inspect images and remove bad frames

The next steps depend on the data, instrument and telescope

Combine individual dark frames to make a single dark frame

Subtract dark frame from all flat field frames

Combine flat field frames to make a single flat field

Subtract dark frame from all images, then divide by flat field

Mask bad pixels

Remove cosmic rays

Calculate and subtract bias frames‘Standard Pipeline’

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Scattered LightLight from bright sources can scatter off of the optics in the telescope. The result is extended emission which is not real: Scattered Light

Scattered can be produced by bright stars outside the field of view of the telescope.

You can avoid it sometimes by carefully planning observations, and there are some routines for removing it, but it can be difficult.

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Ghost ImagesGhost Images are similar to stray light, but are produced by scattered light within the instrument. Ghost images and scattered light are worse for bright sources

Ghost Images

DSS

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Saturation and Non-linearity

A single pixel can only hold a certain amount of charge. When it exceeds this, we have saturation.

Normally, the detected flux is varies linearly with the flux of the source. When you get close to saturation, this isn’t generally true: the detector becomes non linear.

If a source is saturated, you cannot accurately measure the flux: you want to avoid this as much as possible. Saturated pixels bleed into neighbouring pixels as well. The saturation levels for an instrument will be be provided in the users’ manual.

2MASS Ks band

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• Filters



• exposures

• dithering

• nodding & chopping

• Photometry

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ObservingGoal of observations:

- Observe our science target- minimize noise- maximize sensitivity- avoid saturation- avoid, remove or minimize artifacts- remove sky emission and atmospheric effects

Do this all as efficiently as possible

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Multiple exposuresIn OIR observations, we don’t normally take a single long exposure; we take a number of small exposures and add them together after the observations.

Why?

This makes it easier to - correct for artifacts

- cosmic rays- satellite trails

- correct pointing errors (drift) - avoid saturation of bright sources while increasing sensitivity

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Infrared StrategiesDithering: shift the field of view slightly between exposures

- correcting for artifacts as they will show up on different parts of the image

- scattered light & ghosts- bad pixels- flat fields

- improve resolution- undersampled images

- more common in the infrared than optical

This makes combining the images much more complicated!

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Dithering and MappingFor a large area map (larger than the detector) a combination of mapping and dithering might be used

Each pointing has a dither cycle and multiple pointings are combined into a map.

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Nodding and ChoppingMid-IR has high, varying sky background. This can be very difficult to remove, particularly for large field observations.

Chopping: Move the secondary mirror at a few Hz to observe off source region of the sky.

Nodding: A few times a minute the telescope is moved to image a nearby field.

The on and off source images are combined to determine the ‘true’ image. This is particularly hard for observations of extended emission.

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AirmassFor sources in different parts of the sky, the light travels through different amounts of atmosphere.The relative amount of atmosphere the light passes through is referred to as the airmass.

- scattering, absorption, diffraction- one at zenith (directly overhead)- can affect measurements and exposure times

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• Filters



• Photometry

• PSFs

• aperture photometry

• PSF modelling

• calibration

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ResolutionThe resolution of the telescope is limited by

The size of the telescope:This is the diffraction limited resolution

Atmospheric Conditions: motions of the atmosphere can smear out the image. The quality of the atmosphere is called the seeing. This can be partially corrected by Adaptive Optics, and is not an issue for space observations.

The telescope structure and optics cause additional distortions of the observations

! = 1.22"

D

Resolution for a circular aperture. λ: wavelengthD: diameter of telescope

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Point Spread FunctionsAs a result, a point source, such as a star, has a non point source image. This is called the Point Spread Function (PSF).

PSF for a ‘perfect’ system: Diffraction pattern Airy Ring

The atmosphere and the optics mean that there is never a perfect diffraction pattern.

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Point Spread Functions

Airy Ring

2MASS

Spitzer 24 micron

Ground Based PSF

Space Based PSF

For bright sources the diffraction pattern is also clearly seen: secondary mirror effect. 2MASS

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PhotometryIn photometry, we want to measure the brightness of a source.

The first step is to apply a photometric calibration as the images from the telescope are typically in units of ADU (analogue to digital units), not flux units (Jy, mag)

For this, we observe a non-variable star of known brightness (standard star) and calculate the conversion factor to go to flux units.

The second step is to calculate the flux of a source. There are a couple of ways to approach this.

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Aperture Photometry

Use a circular aperture around the source, and calculate the flux inside it. Define a sky annulus at a larger radius to calculate the average background, which is subtracted from the source flux.

Sky Annulus

Aperture

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Aperture PhotometryNeed to apply an aperture correction for missing flux

The flux of the PSF drops off slowly: you will miss part of the flux when using a reasonable aperture.Multiply the flux by an aperture correction (different for each telescope) to compensate. A few percent to ten percent effect.

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PSF FittingAperture photometry doesn’t work well if the field is crowded. This happens when the distance between sources is similar to or less than the aperture and sky annulus you want to use. You can’t get a good flux measurement with an aperture as a result. Or, you may want to study the extended emission and want to remove the point sources from the data.

In these cases, you can try to fit the shape of the PSF to determine the flux.

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PSF FittingTechniques

Assume that the shape is roughly Gaussian and fit that - good for smooth, reasonably symmetric PSFs

Make a model PSF from the data and fit a scaled version of that to the data - more complex or asymmetric PSFs - need to find good model for the data

Use a computer generated model of the PSF - particularly for space missions where the shape doesn’t change

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Large Scale PhotometryOften you want to do photometry of large fields with a large number of sources (hundreds to millions)

In this case, you need to use an automated point source detection routine to find the point sources before doing the photometry.

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Units

Per unit area- MJy/sr- mag/arcsec^2- Jy/pixel

Typical units for optical/infrared observations

Point sources

m = !2.5 log(F!) + C

magnitudes -- constant depends on filter system

flux units- Janskies (Jy)- erg/s/cm2/Hz

Extended Emission

(Not Jy/Beam!)

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SoftwareIndividual telescopes may have their own software, or software written by users.

A standard package for image reduction, with a lot of routines is IRAF (Image Reduction and Analysis Facility) - general software for image reduction - one of the most commonly used - lots of contributed software

Common routines for photometry- DAOphot (IRAF/IDL)- Sextractor (Separate Code: fitting)- Starfinder (IDL PSF fitting)

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Documents

Data Reduction in the Optical and Infrared An …slai/Classes/Fundamentals...•A basic, general introduction to common steps and terms in optical/infrared imaging observations •