imaging and photometry - california institute of...

Imaging and PhotometryImaging and Photometry

Hermann-Josef RöserMax-Planck-Institut für Astronomie

Heidelberg (Germany)

NEON 2005 H.-J. Röser (MPIA): Imaging and Photometry 2

OverviewOverview

Instrumentation

Preparation of observations

detector characteristics

flat fielding

Planning the nighttwilight flats

focusing

photometric calibration

Data reductionflat fielding

image cosmetics

Data analysisastrometry

determination of the observed count rate

photometry

Applications


InstrumentationInstrumentation

Instrument layoutCassegrain

Prime focus


CamerasCameras

Pure imaging (LAICA, O2k)filters

detector

Focal reducer (CAFOS, MOSCA)

intermediate focusmasks / spots

parallel beamanalysers

—grism—Fabry-Pérot interferometer—Wollaston prism


O2k atO2k at thethe 3.5m3.5m--telescopetelescope


MOSCA at MOSCA at the the 3.5m3.5m--telescopetelescope


DetectorsDetectors

Charge-Coupled Devices (CCD)

Infrared Focal-plane Arrays (FPA)


HowHow a CCD a CCD worksworks

bulk chipbulk chip

thinned chipthinned chip


ChargeCharge--coupled device coupled device (CCD)(CCD)


CCDCCD--DetectorDetector

anti-reflectioncoating !

100

80

40

60

20

0200 300 400 500 700600 800 900 1000 1100

wavelength [ nm ]

MPIA December 1995Quantum ef ficiency curves of Calar Alto CCDs

* only relati ve scale

TEK 13TEK 12TEK 11TEK 7*TEK 6*TEK 4


CCD CCD specific defectsspecific defects

bloomingexcess charge flow along column

charge-transfer efficiency

dead columnscorrupted columns

fringinginterference in thin detector layers

dependent on λ and ΔλCCD column


How How an IR an IR detector worksdetector works

sapphire

HgCdTe detector

silicon multiplexer (MUX)indium bumps

photons

pixel accessed individually

non-destructive read-out HAWAII 2 detector


Difference Difference CCD / IR CCD / IR detectordetector

Martin Beckett PhD thesis

CCD

IR FPA


overscan andoverscan area

(bias)

CCD terminologyCCD terminology

dead column corrupted column

number ofdetected photones =(signal - bias) * EPC

statistics areafor FR_STAT(FR_AREA)

prescan

pixelcoordinates

worldcoordinates (RA / DEC)

physical pixel area


RawRaw CCD imageCCD image

dead columns

fringes

dead spots

objectscosmic ray hits


CCD characteristicsCCD characteristics

spectral responsedynamic rangeread-out noiselinearityflat fielddark “current”bad pixels (columns)charge transfer

standard starfull well, gain settingperform “chip test”spectroscopic flat fielddome, twilight, internaldark exposuresmap them to avoid(nothing you can fix)


CCD typesCCD types

Choice of detectorthick (bulk) chip

thinned chip

coated, thick chip

Consequencesquantum efficiency

relatively low (50%)very low blue sensitivity

sensitive to “cosmic rays”low read-out noise

quantum efficiencyhigh (over 80%)blue/UV sensitive

interference fringesgood blue sensitivity


Selection of CCD typeSelection of CCD type

pixel size

12 ... 30μm

number of pixels

up to 4 x 4 k

gain

binning

windowing

image resolution

image area

“digital” dynamic range

resolution / storage

read-out noise

image area

read-out time

storage requirements


Preparation of observationsPreparation of observations

Determination of detector characteristicsread-out noiseconversion factor EPC (electrons per count)linearity

Shutter performanceFilter transmission curvesFlat fields (in part)Dark exposures Planning the night


Detector characteristicsDetector characteristics

Noise contributionsread-out noise R

photon noise √Nfixed-pattern noise F

Unknown quantitiesREPC = e− / count

uncorrected Fbias level

Chip test:series of flat fields

internal lamp / windowillumination level

— near zero ... saturation

independent flat fieldsstandard reduction

bias subtractionflat field correction

variance in small area



Poisson statistics + error propagation2 2 2 22 2

ck R k Fk CCσ≡ = + +variance

22 2 2

2cR C F Ck k

σ = + +

fit parabola: y = a+bC+cC 2

coefficients give desired quantities:EPC = k = 1 / b [electrons per count]

RON = R = √ (a / b2) [electrons]



10

100

1000

10000

100000

1000000

0.1 1 10 100 1000 10000 100000 1000000log (signal)

log

(var

ianc

e) RON dominates

photon noise dominates

problems !



Check of linearity regimespectroscopic flat fields with focal reducer

modest illumination

maximum illumination

ratio of average spectrashould be flat, if linear

if not, deviation from

horizontal line gives

limit of linearity wavelength

inte

nsity

saturation !


Shutter performanceShutter performance

Each pixel should see same exposure timeDifficult to realise in practice

large field of viewshort exposures (standard stars are bright!)

Many shutters are of iris or similar type !Test minimum acceptable exposure time

flat field series from short to long exposurescheck level in centre & corner as function of Δt


Shutter performanceShutter performance

sign

al le

vel

exposure time

effect of finiteopening/closing time

non-linearity ?


Filter transmission curvesFilter transmission curves

Synthetic photometryrequires knowledge offilter transmissionMeasured in a focal reducer with a grism

spectrum without filter

spectrum with filter

ratio as a function of λ gives filter transmission

λ-calibration with comparison lamp


FlatfieldingFlatfielding

Raw imageraw counts ≠ photometric signal

Reduced imageflat sky background

counts above background ∝ signal from object

multiplicative flatfields

additive flatfields


Multiplicative flat fieldingMultiplicative flat fielding

Pixel-to-pixel sensitivity variations

large scale sensitivity variations due tovariable thinning of chip

variations in anti-reflection coating

vignetting (if present)

dust on opticslenses, filter

dewar entrance window


Multiplicative flat fields Multiplicative flat fields

internal flatsdome flats

twilight flats

easiest, but least useful

better, but illumination?

mirror cover open/close ?sun light contribution?do not illuminate structure of telescope!

best results

only short period of time availablepoint away from sun!


Dome flatsDome flats

Use dome (or internal) flats forchip test (RON, linearity)

treatment of bad columns (see below)

Take dome flats if there is not enough time for twilight flats (many filters, few nights)

dome flats will not properly correct vignetting due to dust on filters / optics

different light path

lamp must not emit line radiationinterference fringes


Additive Additive flatfieldsflatfields

Variation due to interference fringeshighly wavelength dependent

night-sky line emission

not present in signal from objectcontinuum source

scattered lighte.g. Fabry-Perot imaging

see example later on


0

10

20

30

40

50

60

70

80

7000 7500 8000 8500 9000 9500 10000

wavelength [Å]

Flux

[Ray

leig

h/Å

]Spectrum Spectrum of of the night skythe night sky

0

10

20

30

40

50

60

70

80

3000 4000 5000 6000 7000 8000 9000 10000

wavelength [Å]

Flux

[Ray

leig

h/Å

]

narrow-band emission→ interference fringes


Flat field componentsFlat field components

line illuminationfrom sky (fringes)

objects + sky

continuumilluminationfrom sky

position


Dark exposuresDark exposures

Dark with zero exposure time (only read-out)bias level (overscan)structure in bias frame

long dark (typically > 1000 sec)dark “current” levelstructure in dark sensitivityseries of >3 dark exposures with increasing Δt

— detect un-correctable pixels— elimination of cosmic ray events

smooth or model before subtracting from images


Planning the nightPlanning the night

24 2 4 6 8 10

UT

1.2

1.4

1.6

1.8

1.0

Airm

ass

ofob

ject

s object 1

object 2


Exposure Exposure time time calculators calculators (ETC)(ETC)

Tools provided by observatories

inputfilter

source spectrum

outputS/N = fkt(exposure time)

use with caution !


SignalSignal--toto--noise ratio (S/N)noise ratio (S/N)

source signal Obackground level Bread-out noise R, aperture size p [pixels]exposure time Δt, number of exposures n

2/

( ) nO n tS N

O RB p n t p∗

∗ ∗ Δ

+ +∗ ∗Δ ∗∗=

background limited / detector limited cases


Brightness of night skyBrightness of night sky((LeinertLeinert et al.et al. 1998: A&A 1998: A&A SupplSuppl. . 127127 11--99)99)

0.01

0.10

1.00

10.00

100.00

1000.00

0 500 1000 1500 2000 2500 3000 3500 4000wavelength [nm]

flux

[pho

tons

/sec

/m2 /n

m/�

" ]

ESOKPNORiekeMoorwood


Planning the nightPlanning the night

Time requirements per object:set up of field

acquisition frame

number of exposures / integration time per filteroverhead per image (CCD read out)

short exposures for each filter / fieldsaturation of bright objects / calibration

Photometric calibrationdo only if night is known to be photometric

check: photometric telescope / own test exposures


TwilightTwilight

Flat field exposuresoptimum multiplicative flat fields

Standard star measurementsonly needed if photometric calibration desired

Focusingsequence for each filter with unknown focus

Acquisition of first fieldcheck telescope pointing

determine offset to be applied to co-ordinates


Twilight flatsTwilight flats

Field devoid of bright starstowards east for dusk, towards west for dawn

Mirror cover open

Start with narrow filtercheck level in small window with fast read out

Exposure level to about 3/4 of valid range

Offset telescope between exposures (~ 30”)

> 2 exposures per filterfor averaging procedure see below


First standard star measurementsFirst standard star measurements

Photometric calibration starts in twilightonly if night is (or seems to be) photometric

Check of photometric quality(1) sum in window around standard star

(2) sum in window of same size in background

(3) counts/second for 2 or 3 standard starsconsistency check of relative magnitudes

proceed with photometry or not ?


FocusingFocusing

Focus sequenceuse standard star if possible / save imageexposures with different focus settings

move telescope between exposures or

shift charge on detector

use exposure times of > 10 sec (image motion!)

Relative focus of all filters to be used

Adjust focus during night usingtemperature coefficient (telescope structure)

focus wedge


Focus testFocus test


ScienceScience exposuresexposures

Obtaining science exposures

estimate exposure times (seeing)decide on positioningadjust guiding (TV guider)

sampling interval— image motion

adjust gain not to saturate guide starlight curve of guide star → photometric quality

planning the nightplanning the night


Science exposuresScience exposures

Ditheringnecessary for construction of fringe patternavoids bad pixelshelps recognition of internal reflections

offset not too large (loss of field of view!)

Check of exposure timeBackground limit reached (if feasible)?

at least 1 short exposure for each filter— astrometric & photometric reference stars not saturated


Photometric calibrationPhotometric calibration

Classical photometry [mag]photometric standard stars (filter system)

range of airmasses 1 ... 2 and higher

regressioncatalogue magnitude = f (obs. magnitude, colour)

works fine for stars

problematic for non-thermal objects, galaxies ...

Synthetic photometry [ Jansky = 10-26 W/m2/Hz]

exploits knowledge of your system


Photometric calibrationPhotometric calibration

Synthetic photometry (cont.)

spectrophotometric standard stars in each filterrange of airmasses 1 ... 2 and higher

flux at central wavelength of filter

Photometric calibration is time consuming!attempt only, if night is most likely photometricchoose standard stars from elevation plot

good coverage in airmass and spectral type of stars

standard stars easily saturate (shutter, focus !)


Data reductionData reduction

Standard reduction steps:bias and dark subtraction

multiplicative flat field correction

additive flat field correction

extraction of useful area

image cosmeticscosmic rays, corrupted columns

superposition of dithered images in same filter

definition of world co-ordinates (astrometry)

photometric calibration

from science frames


Procedure Procedure FLAT/AVERAGEFLAT/AVERAGE

stack imagesremove stars, cosmics

from twilight flat fields

from images for fringe pattern

“median” in pixel coordinatesκ−σ-clipped average

scaling by exposure level

optional

repeat for smoothed image to remove wings of stars

4

3

2

1

1+21+2+3+4


Data reduction: dark exposuresData reduction: dark exposures

I. Bias (DC-offset, Dark0)frame specific level from overscanstructure from average over DARK0 framessmooth or model before subtraction

reduce noise

II. Dark “counts”average over several DARKX frames

scaling by exposure time instead of level

smooth or model before subtraction


Data reduction: flat fieldingData reduction: flat fielding

III. Average of twilight flats for each filterfixed-pattern noise / global sensitivity variation

normalisation by average level in central window

(use same window for all images)

IV. Correct for multiplicative flat fielddivision by result of average for twilight flats

Corrections for I,II and IV applied in single task for all

images in given filter.



raw flat

corrected

mult. add.



Interference fringesnight sky emission lines

additive flat field:only in backgroundnot in objectsproblem:emission line objects

Flat/average science frames in given filter

scale by backgroundFLAT_BKGsubtract


Flat fieldingFlat fielding

Example: Sensitivity to separation of multiplicative and additive flat field

Fabry-Pérot imaging with a focal reducerorder selection with pre-filter (width 25nm)

resolution of FPI 1.8nm

Comparison of flat fieldspre-filter alone

pre-filter + FPI

scattered light must be present due to FPI


Flat fielding FPI images:Flat fielding FPI images:example for complexityexample for complexity

Flat with pre-filter only Flat with pre-filter+FPI


FPI flatFPI flat fieldingfielding

Mask with pre-filter only Mask with pre-filter + FPI


FPI FPI flat fieldingflat fielding


NearNear--IR IR data reductiondata reduction

Flatfielding as in optical rangetwilight flats not necessarily flat !

Sky brightness and illuminationstrong changes on short time scales

determine sky from neighbouring images

takes care also of dark subtraction

Check flatfielding with 2MASS photometry


Removal of cosmic ray eventsRemoval of cosmic ray events

Median of images in world co-ordinates

Compare each pixel with median image

Replace deviating pixels by scaled medianrequires > 2 images per field & filter

Only one or two images available:gradient to neighbouring pixels compare with what is allowed by Poisson statistics

replace deviating pixels by average over neighbourhood

Keep mask with event positions


Removal of cosmic ray eventsRemoval of cosmic ray events

star

Jet of quasar 3C 273(HST WFPC2)


Corrupted and dead columnsCorrupted and dead columns

Dead or hot columns cannot be restoredinterpolate between neighbouring columns

Column offsetsconstant for each columnmay depend on illumination leveladd constant to fully restore column

done in raw image

If detector shows such columns, obtain flats for the full range of illumination levels !


Corrupted columnsCorrupted columns

Offset for each column = function of count levelFitting function

( )[ ]critoffset CCCC /exp1 −−×= ∞column

aver

age

leve

lillumination level

Cof

fset

C∞C∞ and Ccrit determined from flat fields over range of levels

Coffset applied to each column


Data analysisData analysis

Astrometry ⇒ astronomical positionsplate co-ordinates X,Y ⇔ RA, DEC

Photometry ⇒ brightness of objectsunresolved sources

resolved sources

multi-waveband studies

(imaging) Polarimetrysame philosophy as photometry


AstrometryAstrometry

tangent plane

focal plane

focallength f

C

O

L

M

N APlate centre O at A, DObject L at α, δCo-ordinates in focal plane at M η and ξ

unit = focal length f

Projection onto sky’s tangential plane in N

Smart: Handbook of Spherical Astronomy page 278ff


AstrometryAstrometry

Transformation equations α,δ ⇔ η,ξ

)cos(coscotsin)cos(sincotcos

ADDADD

−+−−

=αδαδη

)cos(cotcossin)sin(cot

ADDA

−+−

=αδ

αδξ

DDA

tan1sec)tan(η

ξα−

=−D

DAtan

sec)sin(cot+

=−ηξαδ


Astrometry stepsAstrometry steps

Select secondary astrometric reference stars on science frame and get their plate coordinates η,ξ

Objects measurable on sky survey plates

Select primary reference stars from PPM, TYCHO …30 to 40 objects

Obtain plate solution via least square fittransformation α,δ ⇔ η,ξ

Determine α,δ of secondary reference stars from POSS via plate solution


Astrometry stepsAstrometry steps

Obtain plate solution for science frameuse α,δ of secondary standard stars

Proper motionminimised using POSS II

Systematic errorsmeasure on digital scans

Accuracy about 0.1"distortion of optics determined independently


PhotometryPhotometry

Determine count rate for program objectsphoton counting photometer with apertureevaluation of signal on CCD frame

Set up photometric system with standardsclassical photometric systems

Johnson U, B, V, R (broad band)Strömgren u, b, v, y (narrow band)Gunn g, r, z (optimised for S/N, sky background)

Synthetic photometry


Determining the count rateDetermining the count rate

“Classical” approach: aperture photometry

counts in fixed aperturecorrect local background

advantage of CCDs:Aperture chosen after data are obtained.Which aperture radius?

too smalltoo small: loose signaltoo large: backgroundWhere is optimum?


Local backgroundLocal background

Signal above local background

exact background essentialvariable background

high background (IR)

histogram analysis

signal above backgroundpixel value

frequ

ency

average



Sampling counts with weighting functiongeneral case, includes plain sum in aperturearbitrary positioning of “soft” aperture enables treatment of extended sources

Weighting is equivalent to convolutioncalculated only at position r

Photon counts at position r from signal Sin what follows, see Eduard Thommes (PhD thesis Heidelberg 1996)



Signal S= point spread function (PSF) = Gaussian2

022

0( )r r

S r p e σ

−−

=

20

220( ) w

r r

W r W e σ

−−

=

(seeing)

Weighting function = Gaussian at r0

( ) ( ) ( )i

i i ir R

S r W r r S r dr<

= −∫

position

sign

al

p0

σ



Total counts from object above background2

2 220 0

0

2 2r

totS p e rdr pσπ π σ∞ −

= =∫

2 2

2 22

0

2 2

0 0

20

2 2

02

2

w

w

r r

w

S rW de r

p W

p e σσπ

σ σπσ σ

∞ − −

=

=+

∫

Result of weighting



Result of weighting ≡ total number of photons

normalisation

202totS S pπσ= ⇒ 02 pπ=

2

0W σ 2 2

02 2 21 1w

w w

Wσ σ ασ σ σ

⇒ = + = ++

Extended objectstotal counts are under-estimated this way

correction factor necessary to obtain Stot

count ratios (i.e. colour) remain valid



Optimum width of weighting function

maximum S/N = signal / noise

Measured signal in aperture of radius R

2

2

0

(1 )2

(2 )

,

(

1

)R

R

tot

S rdrW

RS S

r

e

S r

ασ

π

ασ

− +

=

⎛ ⎞ ⎛ ⎞= − =⎜ ⎟ ⎜ ⎟⎜ ⎟ ⎝ ⎠⎝ ⎠

∫



Photon noise =

theoretical uncertainty of photometry

2 2 2 2

0 0

2 ( ) ( ) 2 ( ) ( )R R

N b W r rdr S r W r rdrπ ρ π= + +∫ ∫

~N

b = photons / pixel in background

ρ = read-out noise



( )

( )( )

2

2

2

2

222 2 2 2

2(1 2 )

2

12 ( ) 1

2

11

1 2

R

R

tot

N b e

S e

ασ

ασ

απ ρ σ

α

αα

−

− +

⎛ ⎞+= + − +⎜ ⎟⎜ ⎟

⎝ ⎠⎛ ⎞+

−⎜ ⎟⎜ ⎟+ ⎝ ⎠

( ) ( )2 22 2 2 1 1

lim 2 ( )2 1 2totR

N b Sα α

π ρ σα α→∞

+ += + +

+



Signal-to-noise ratio

, ,R RS Nα ασ σ

⎛ ⎞ ⎛ ⎞= ⎜ ⎟ ⎜ ⎟⎝ ⎠ ⎝ ⎠

S/N

2

2

2

2

(1 )2

22

1

( , )(1 )1

t

R

t

R

oSe

eb

R

ασ

ασ

σπαα σ

α

− +

−

⎛ ⎞−⎜ ⎟⎜ ⎟

⎝ ⎠= =+

−

S/N S/N

Limit of weak signal (b >> p0 , ρ small):

R/ σ

10

65

4

3

2

1.6 1.31.11.0

0.5

plainsum

large aperture

/weight PSFσ σ


Optimum S/NOptimum S/N--ratioratio

Unweighted sum (α → 0):2

22

0

1lim(

R

totS eRb

σ

α σ π

−

→

−=S/N)

Ropt = 1.58σ = 0.67 FWHM

Weighted sum (R → ∞): σw = σwidth of weighting function = seeing



Convolution changes resolution

2 . /2 2opt S

weff

Nσ σσσ= + =

seeingresult weighting function

Multi-wavelength study of extended sourcessame effective resolution for all images

achieved by carefully choosing σw

centre of weighting function positioned in world co-ordinates to fraction of pixels


Photometry of extended objectsPhotometry of extended objects

positions of weighting functions

sky background apertures



Sources of errorimage alignment

important for multi-waveband studies— radio / optical

< 0.1”— depending on seeing and required accuracy

error in PSFvariable from image to image

Now ready to do actual photometry


Classical photometryClassical photometry

Measurementscount rate in filter system at various airmasses

program objects and standard stars

Data analysisextinction correction

flux outside earth’s atmosphere

transformation to standard systemslight differences in filter / detector response


Magnitude Magnitude systemsystem

Pogson scale5 mag difference = factor 100 in flux

Relative scale to standard object (Vega)

1 2 1 22.5log( / )m m F F− = −

2000 4000 6000 8000 10000

λ [Ångstrom]

2 x 107

4 x 107

6 x 107

8 x 107

f λ [1

0−18 W

/ m

2 / n

m]

Problem

Observed quantities on surface of earth

Flux from star outside earth‘s atmosphere


Extinction in earth’s atmosphereExtinction in earth’s atmosphere

Plane parallel atmospherezenith distance z < 60°

dF F dsλ λ λα= −

00

0 0

ln( / )s

s

dF ds F F dsF

F e dsF

λ

λλ λ λ λ

λ

τλλ λ

λ

α α

τ α−

= − ⇒ = −

= =

∫

∫mit

Fλ0

Fλ

sy

z

optical depth[αλ]=cm2/cm3 = cm-1


ExtinctionExtinction

Transition to magnitude system

0

0

2.5log( )2.5log( )

m m em m e

λτλ λ

λ λ λτ

−− = −

= −

0

sec secy

ds dy z dz yλ λτ α= = ∫ gives

Fλ0

Fλ

sy

z

0 secm m k zλ λ λ′= +

2 3

sec 0.0018167(sec 1)

0.002875(sec 1) 0.0008083(sec 1)app app

app

X z z

z z

= − −

− − − −

Introduction of airmass X

airmass

mag

nitu

de

1


ExtinctionExtinction

= f (atmospheric conditions, zenith distance)

extinction = f (object colour)extinction due to molecules ∝ λ−4

extinction due to aerosols ∝ λ−1 or ∝ λ0

bandwidth effect

include colour term in extinction correction

( )km m k c Xλλ λλ = − + ′′′

ipalindex


Transformation to standard Transformation to standard systemsystem

Transformation to standard system

response of system different from standardshift in effective wavelength of measurement

Dependent on object continuum

problems with non-stellar objects

wavelength

appa

rent

am

gnitu

de Continuum shape of objectλstandard

λ instrument


Transformation to standard Transformation to standard systemsystem

Approximation by Taylor expansion in λobs

200 ( )obs obs

obs

mM m Oλλ λ λ λ

λ⎛ ⎞Δ

= + Δ + Δ⎜ ⎟Δ⎝ ⎠

0M m Cλ λ λ λβ γ= + +

constants for instrument

colour indexnear λobs

slope = colour

magnitudes corrected for extinction


Standard systemsStandard systems

Spectrum of Vegaaccuracy ~1.5%

Hayes (1985): IAU Symp.111

Conversion factors 0mag

AB-magnitude (B. Oke)AB = −2.5 log (fν) - 48.59

[fν] = erg/cm2/s/Hz

1 Jy = 10-23 erg/cm2/s/Hz

Flux conversion fνdν=fλdλ

fλ [phot/m2/s/nm] =

15.09 fν [μ Jy] / λ [nm]

U 1900 JyB 4640 JyV 3670 JyR 2840 JyI 2250 JyJ 1650 JyH 1070 JyK 673 Jy


Synthetic photometrySynthetic photometry

Parameters of overall systematmosphere, telescope, filter, detector

Calculate count rates for standard starsObserved count rate provides correctionModel applied to program objects

calculate flux [ Jy] from observed count ratesapplicable not only to starssupports non-standard filter systems

Synthetic Photometry

telescope

atmosphere

filter

detector

spectrum f

program object

expected count rate

measured count rate

correction factor

measured count rate

flux of program

object

Regression with

airmass

spectral shape

standard star

adjust for measuring procedure

input measurement calculated


Synthetic photometrySynthetic photometry

Fit correction factor as a function of e.g. airmassCheck photometric quality of the nightCorrection factor should be on the order of unity

check validity of model

airmassco

rrec

tion

fact

or


ApplicationApplication:: PhotometricPhotometric redshiftsredshifts

Multi-colour observationsseparation stars / galaxiesclassification (Ch. Wolf PhD thesis HD 1999)

spectral types of starsgalaxy type and redshift for galaxiesquasistellar objects (redshifts)

ApplicationsHubble Deep Field (HDF)CADIS (Calar Alto Deep Imaging Survey) etc.


Separation Separation starsstars / / galaxiesgalaxies

Principle:object area =

FWHMX * FWHMY

area = const. for linear detector

PlotArea = f (intensity)

Problemmultiple stars


Object inventory (3 filters)Object inventory (3 filters)

-1

0

1

2

3

0 1 2 3B-R

R-I

Galaxies 16h

Stars 16h

QSOs 16h

QSOs 9h

3.3

3.73

2.80

2.41

2.26

3.36

QSOs 3h


MultiMulti--color filter setcolor filter set

0

20

40

60

80

100

trans

mis

sion

[%]

300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400 1,500

wave length [nm]

CADIS filter set: 3 broad and 13 mediumband filters

Objects measured in each filter (flux, position, shape etc.)


Parameter-space

λ−space

Colour space

T

g

[M/H]

SED

zE

Sb

B

B

Sb

E

614-IB-

614

B-R

R-I

Pickels library

Allard’s M

Classification principleClassification principleChristian Wolf

(PhD thesis 1999)


selection of discriminating colours

Spektren-bibliothek

filter curves

spectrallibrary

Schätzer/Klassifikator

parameters and class of objects

object listwith

colour dataestimatorclassificator

colourlibrary

Classification principleClassification principle


Classification principleClassification principle

q1

q2

qc2

c1


0

20

40

60

80

100

trans

mis

sion

[%]

300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400 1,500

wavelength[nm]

Classification resultClassification result

galaxy at z = 1.2


Spectroscopic VerificationSpectroscopic Verification

Actual class Spectroscopic

Color class Stars Galaxies QSOs

Stars 55 1

Galaxies 153 2

QSOs 2 20

Phot

omet

ric

~103 objects/field to R ~ 23m


0.0

0.5

1.0

z(spectroscopic)

z(ph

otom

etri

c)

0.0 0.5 1.0 0.0 0.5 1.0z(simulated)

ComparisonComparison: : galaxiesgalaxies


0 2 4z(simulated)

0

4

z(spectroscopic)

z(ph

otom

etri

c)

0 2 4

2

ComparisonComparison: : QSOsQSOs

2.41

3.72

1.57

2.27

2.26

1.13

2.80

0.471.43 3.36

CADIS 16h-Field

3 Seyferts

plus7 Quasars

1 Mpc

@ z~1

containing


Abell Abell 902 902 studystudy

N

0

80

0.0 0.5 1.0 1.5

0 .185specz =

0 .189photoz =30

00.16 0.22

N

z( ) 0 .0 0 5

pho to specz zσ − =

z


Literature generalLiterature general

R. Berry, J. Burnell (2005):Astronomical Image Processing (Willmann-Bell)

A.A. Henden, R.H. Kaitchuck (1982):Astronomical Photometry (van Nostrand Reinhold)

P. Léna (1998):Observational Astrophysics (Springer Verlag)

N. Carleton (ed., 1974):Methods of Experimental Physics, Astrophysics part A: Optical and infrared (Academic Press)


Literature detectorsLiterature detectors

Mackay, C.D. (1986): Ann.Rev. A&A 24, 255

McLean, I.S. (1989):

Electronic and Computer- Aided AstronomyPhilip, Janes, Upgren (ed.) (1995):

IAU Symp. 167: Array Technology & ApplicationsGraser, Meisenheimer & Röser (1993)

Landolt-Börnstein New Series VI/3a, 17

SPIE proceedings


Literature own workLiterature own work

Röser (1981): Photographic polarization survey with a Savart plate A & A 103, 374

Röser & Meisenheimer (1991): The synchrotron light from the jet of 3C 273 A & A 252, 458

Wolf, C., K. Meisenheimer and H.-J. Röser(2001). "Object classification in astronomicalmulti-color surveys." A & A 365, 660

imaging and photometry - california institute of...

Documents