Gaia Photometric Data Analysis Overviewulisse.pd.astro.it/Gaia_doc/paola.pdf · 2005. 4. 13. ·...

Gaia Photometric Data Analysis Overview

Paola MarreseSterrewacht Leiden

[email protected]

● Gaia photometric system

● Role of photometry in overall Gaia data analysis

● Photometric data analysis goals

● Tasks and links to other data processing groups

● Organisation of the PDA effort

● Examples of exploratory studies

Photometric system Role of photometry Goals Tasks/links Organisation Exploratory studies Bologna 08.04.2005 - p.1/30

Astro focal plane array

Star motion


Total field:

● Size 85× 60 cm

● 170 CCDs

● CCDs: 4500× 1966 pixels

Sky mapper:

● detects all objects to 20 mag

● rejects cosmic-ray events

Astrometric field:

● pixel size: 10× 30µm2

(44.2× 132.6 mas2)

● window area: 6× 12 pixels

Broad-band photometry:

● five colour

Spectro MBP focal plane array

Spectro sky mappers

Star motion


blue enhanced CCDsred enhanced CCDs

Designing the photometric systems

Objectives:

● Astrophysical classification and parametrisation of the observedsources

➠ Intermediate and broad band photometry

● Chromaticity correction of the astrometric measurements➠ Broad band photometry

Science case demands:

● Measurement ofL, Teff, M, age, composition for the stellar populationsin the Galaxy and its neighbours

➠ Teff, reddening for OBA stars;Teff, abundance for late giants and dwarfs

➠ luminosities for stars withσ$/$ > 10%

➠ distribution function of abundances to∼ 0.2 dex

➠ Teff to 5%; separate determination of [M/H] and [α/Fe]


Photometric system optimisation

● Find filter system that maximises separation of stars with differentastrophysical parameters in filter flux space

➠ gradients of filter fluxes wrt AP changes should be as large as possible(taking the measurement noise into account)

➠ gradient vectors should ideally form orthogonal set

φ2

φ1

φ3

rbdd rc

r

b

c

α



● Find filter system that maximises separation of stars with differentastrophysical parameters in filter flux space

➠ gradients of filter fluxes wrt AP changes should be as large as possible(taking the measurement noise into account)

➠ gradient vectors should ideally form orthogonal set

φ2

φ1

φ3

rbdd rc

r

b

c

α

Make use of sensitivity matrix:

Si =

∂φi1/∂p1 . . . ∂φi1/∂pK...

......

∂φiJ/∂p1 . . . ∂φiJ/∂pK



Calculate the posterior errors achievable with PS:

Cp = (B + STC−1φ S)−1, Cφ = diag(ε2

j )

The lengths and orthogonality of the AP gradients are contained inCp


Evaluating performance

Test photometric systems on grid ofsynthetic spectra

● Define priority targets from stellarpopulations in Halo, Bulge,Thick/Thin disk

● Assign weight to each target

● Specify precision goals for each ofTeff, AV, logg, [M/H], [ α/Fe]

➠ function of magnitude, distance

● Assign relative priorities toastrophysical parameters

For each target compute:

Qi =X

wkf (σk/σk,goal)

Overall figure of merit for PS:

Q =X

wiQi


The baseline photometric systemsC1B photometric system

200 400 600 800 1000λ (nm)

0.0

0.2

0.4

0.6

0.8

1.0

C1M photometric system

200 400 600 800 1000λ (nm)

0.0

0.2

0.4

0.6

0.8

1.0


Photometry and overall Gaia data analysis

Gaia

data processingphotometric



Gaia


Medium band photometryDiscrete object classification

Astrophysical parametrisation

variability analysis

Cross−matchingplus prompt

Broad bandphotometry



Reference frameQSOs

Global Iterative SolutionList of "well−behaved" stars

RVS dataprocessing

Gaia


Science alerts Astrometric dataprocessing

Chromaticity

Broad bandphotometry

Medium band photometryDiscrete object classification

Astrophysical parametrisation

variability analysis

Cross−matchingplus prompt


Photometric data analysis goals

Science:

● Mission-averaged fluxes and magnitudes for each object and each filter➠ Object classification➠ Astrophysical parametrisation

● Epoch photometry for each object➠ Variability database➠ Science alerts during the mission

Calibration:

● Standard fluxes

● CCD parameters

● PSF and LSF

● Photometric pass-band reconstruction


Complications

binningnumerical

Focal plane array

(along−scan direction)motion across focal plane array

electronic binning

to ground

flux

position

Data transmitted

GAIA ‘image’

pixel

sample

Window


Complications

● TDI operation across very large focal planes➠ Complex calibration task

● Windows may contain in addition to single star:➠ binary components, background sources➠ spikes from PSFs of nearby stars

● Overlapping fields of view in Astro

● Windows mostly 1-dimensional➠ Line-spread function (LSF) instead of Point-spread function➠ Mapping of surroundings of observed objects required

● Very different resolution scales Astro and Spectro➠ Specific treatment crowded regions


Scale of the effort

Star density Average 25 000, typical 150 000, worst 3× 106 stars/deg2

Number of CCDs Astro: 110 AF and 40 BBP; Spectro 32 MBP

Number of Filters BBP: 5, MBP: 14

Number of images per second per FOV

Astro AF: 3 300 20 000 400 000

Astro BBP: 1 200 7 240 144 700

Spectro MBP: 9 800 58 750 1 175 000

Total (2×Astro+Spectro): 18 800 113 230 2 264 200

Realistic FOV projections on sky and Spectro windowing limits:=⇒ maximum of∼ 1.2× 106 images/sec to be processed.


Photometric data analysis tasks

Astrophysicalinformation

MBP

BBP

for AstrometryColour info

G, GS bandVariability

Sky ‘image’




MBP

BBP



Sky ‘image’

Different colourresponse core/wings PSF

Bright stars(wings, gates)

PSF/LSFTDI, AC/AL motionMTF, Charge diffGates

CCD spectral responselarge/small scale

Filter/mirrorageing

Passband reconstruction

Flux outside window

Trend monitoringSky background

Magnitude scale

CTE effects

Calibration




MBP


Sky ‘image’

ScienceAlerts

Automaticclassification

Crowdedareas

BBP


Variablestars

Imaginganalysis

SolarSystem

Astrophysicalparametrisation

Double startreatment

Provide calibrationparameters(CCD, LSF, PSF, etc)

Provide calibratedfluxes to other partsGaia data analysis

Providestandardfluxes

Calibration



see document PWG–AB–001


G-band photometry

Links

● separating true from false images (11 successive AF CCDs)

● instantaneous ‘image’ of sky for BBP and MBP

● prime source for variability analysis

● run in combination with or on output from astrometric processing

Task details

◆ image verification; CCD calibrations

◆ development of photometric calibration model

◆ sky-background (overlapping FOVs!) and CCD zero-level

◆ calibration of spectral response variations between CCDs

◆ statistical tests on formal errors

◆ bright star treatment

◆ calibration trend monitoring software

◆ magnitude scale calibration


Broad-band photometry

Links

● supply colour information to astrometric processing

● provide (limited) astrophysical information especially in crowdedregions

● spectral response based science alerts

● detection of specific types of binaries with astrometry in BBP

Task details

◆ seeG-band tasks

◆ wavelength dependent sky-background model


Medium-band photometry

Links

● detailed photometric information for astrophysical parametrization ofsources

● maintenance clean list of GIS sources

● high-resolution information from AF and BBP will enable treatment ofcrowded areas

● spectral response based science alerts

● input for RVS data analysis (priors on stellar parameters)

● link between astrometric, spectroscopic and photometric parameters

Task details

◆ seeG-band and BBP tasks


Imaging analysis

Links

● detection of disturbing faint background sources near Gaia targets

● important for proper photometric data reduction (background treatment)

● identification of faint components of binaries and multiples

● identify possible spurious variability

Task details

◆ properly stack AF11, BBP, ASM and SSM windows and construct asky image around each Gaia source


Accumulation of data and variability

Links

● check on source variability without examining individual measurements

● variability based science alerts

● checks on the effects of accidental superpositions from other FOV


Task details

◆ accumulate parameters for each star and each successful observation ina general database

◆ input parameters for statistical tests

◆ histograms of normalized residuals

◆ see variable star working group


Passband reconstruction

Links

● essential for scientific exploitation of data

● science alerts

● automatic classification

Task details

◆ identify or create suitable calibration data for Gaia

◆ modelling and monitoring of filter transmission ageing

◆ modelling and monitoring of mirror reflectivity ageing

◆ in-flight passband calibration from differences between predicted andmeasured responses for stars of varying spectra types


Science alerts

Links

● Identify outstanding events that warrant immediate ground-basedfollow-up

Task details

◆ accumulate sky-history

◆ variability based events from comparison of new and accumulatedphotometric data

◆ spectral response based events from sources that do not fit automaticclassification schemes

◆ design robust detection filters with very low false detection probability

◆ see science alerts working group


Automatic classification

Links

● astrophysical parametrization of sources

● input (priors) for RVS/MBP data reduction and


● science alerts

● post-mission data preparation

Task details

◆ see classification working group


Double and multiple stars

Links

● double and multiple star processing

Task details

◆ identify resolved double and multiple stars in data stream and pass toappropriate reduction pipeline

➠ this pipeline has to be fully integrated into photometric processing inpractice!

◆ take into account scan orientation effects

◆ design mechanisms to detect poorly resolved multiplicity


Solar system objects

Links

● solar system objects processing

Task details

◆ develop early identification mechanism and filter out for a separatepipeline

◆ develop a posteriori recognition methods in the accumulated data(avoiding confusion in science alerts)

◆ see solar system working group


CCD calibrations

Links

● all CCDs need to calibrated and monitored in a coordinated effort

● ‘glue’ between all astrometric and photometric data processing

Task details

◆ define calibration data base structures and manipulation software

◆ pay attention at early stage to speed and efficiency

◆ interfaces for access and iterative updating of calibration parameters

◆ develop calibration monitoring and visualization tools


PSF and LSF calibration

Links

● removal of diffraction pattern effects from data

● correction for the effects of TDI operation

Task details

◆ effect of charge transfer losses

◆ micro variations scan rate

◆ localized pixel inhomogeneities

◆ study use of TDI gates

◆ details of PSF wings; differences in response between core and wings


General tasks

● identify the core and shell tasks within the photometric processing

● validation and optimisation of windowing scheme

● optimization of database interfaces for photometric data processing

● development of trend-monitoring tools for all calibration tasks➠ coordinate with astrometric and radial velocity processing➠ develop efficient interactive display tools

● implement software documentation package

● ensure proper version tracking (CVS)


Simulation needs

● simulated data for various processing stages are needed➠ telemetry (for GDAAS core processing)➠ window level data (photometric data reduction studies)➠ pixel level data (PSF modelling, window simulations)➠ intermediate photometric data products (e.g., variability studies)

● identify shortcuts for modelling parts of the data processing thatprecede intermediate or final data products

● detailed PSF models (wings)

● sky-background (overlapping FOVs, faint stars, zodiacal light)

● realistic simulations of CCD properties and TDI operation

● simulations for studying photometric processing of binary and variablestar data

Available now

◆ telemetry and window level data from GASS

◆ pixel and window level data from GIBIS

◆ CCD model under development


Organisation

Exploratory studiesIdeas for algorithmsSimulationsHigh−level pipeline designIntegration with overalldata analysis

ImplementationPreparation of reliableand efficient software forthe missionSetup of actual pipeline

Laboratory studies anddetailed modelling of CCDsTDI operationCTERadiation damageCalibration

GDAAS

Working group Data processing group


To Do

● update work-packages in PWG–AB–001➠ add packages focused on implementation

● identify who will do what

Priority tasks this year

◆ end-to-end simulation of photometric processing chain, starting fromrelatively simple AF case

◆ calibration related efforts, such as PSF, LSF, response functions

◆ develop more sophisticated sky background treatment (overlappingFOVs, crowding)

◆ bright star (gates, PSF wings), binary, and variable star photometry

◆ corresponding simulations (gates already available in GIBIS)

Please coordinate your interests with Anthony Brown:[email protected]


Crowded regions with MBP

● Performance limited by: detection, windowing, spatial resolution

● Use position information from astrometry to carry out PSF fitting

● From data analysis point of view MBP can handle regions up to∼ 400 000 stars/deg2


Result obtained by

Dafydd Evans

Images from AF11

● Proper photometric data reduction requires knowledge ofcontaminating background sources

● Windows from last AF column will be larger

● Surroundings of stars can be mapped toV ∼ 24 for∆V < 8


Result obtained by

Pasi Nurmi

Gaia Photometric Data Analysis Overviewulisse.pd.astro.it/Gaia_doc/paola.pdf · 2005. 4. 13. ·...

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