BAM/DASS: data analysis software forsub-microarcsecond astrometry device
D. Gardiol, D. Bonino, M. G.Lattanzi, A. Riva, F. Russo
INAF - Osservatorio Astronomico di Torino

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20091

Overview• Gaia Basic Angle, what is it?
• BA variations Monitoring during operations: why and how• BAM data analysis software description• Conclusions

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 2009

2

Gaia

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20093

Gaia expected performances
Hipparcos

Gaia

Magnitude limit
CompletenessBright limit
Number of objects

127.3 – 9.00120 000

Effective distancelimit
Quasars
Galaxies
Accuracy

1 kpc
None
None
1 milliarcsec

Photometry
photometry
Radialvelocity
Observing
programme

2-colour (B and V)
None
Pre-selected

20 mag
20 mag
6 mag
26 million to V = 15250 million to V = 18
1000 million to V = 2050 kpc
5 x 105
106 – 107
7 µarcsec at V = 1010-25 µarcsec at V = 15300 µarcsec at V = 20Low-res. spectra to V = 20
15 km/s to V = 16-17
Complete and unbiased

Gaia: complete, faint, accurate (from www.rssd.esa.int)

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20094

Gaia expected performances
Hipparcos

Gaia

Magnitude limit
CompletenessBright limit
Number of objects

127.3 – 9.0
0120 000

Effective distancelimit
Quasars
Galaxies
Accuracy

1 kpc
None
None
1 milliarcsec

Photometry
photometry
Radialvelocity
Observing
programme

2-colour (B and V)
None
Pre-selected

20 mag
20 mag
6 mag
26 million to V = 15250 million to V = 18
1000 million to V = 2050 kpc
5 x 105
106 – 107
7 µarcsec at V = 1010-25 µarcsec at V = 15300 µarcsec at V = 20
Low-res. spectra to V = 20
15 km/s to V = 16-17
Complete and unbiased→ Stringent requirements in Instrument performances

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20095

Gaia – Optical design

BasicAngle

LOS1

LOS2

Image credit: www.rssd.esa.int

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 2009

6Basic Angle Monitoring

BA monitoringnecessarybecause
expected BAvariations may
be too large tocope withexpected perf.

Req: accuracy of 0.5 µas rms over a period of 5 minutes
Image credit: Meijer et al., SPIE 7010

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20097

Gaia – Focal Plane

Image credit: www.rssd.esa.int

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20098

Raw data: fringe image
BAM CCD
Telescope 1
Telescope 2

Physical window onto the CCD: Size is360 x 120 pixels = 3.6 x 3.6 mm²Logical window size is 360 pixels x 60
samples (binning x 2 AC scan)
Telemetry rate: 2/3 couples of images every minute ~ 7.9e6 mission
Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 20099

Raw data: fringe imagefx

Bxx−4αα = 1µas → δLOS ≈ 3.4 ⋅10 µm
Daniele Gardiol – BAM/DASSδLOS = 2αf
δBA = δLOS 2 − δLOS1ADASS XIX – Sapporo –October 4-8, 200910

raw data

BAM/DASSRaw Data
Processingelem. data

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200911

Raw Data Processing algorithm
Four fringe location estimation algorithms (ML,LS,CC,Barycentre)-5 µm (single fringe image, Current estimated accuracy ~ 4/5 x 10
fringe model perfectly known)
 Req. accuracy challenging, but seems feasible


Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200912

BAM/DASS

raw data

the value of some parameters of the fringe modelwill not be known once in flight, and will change withtime (periodic fluctuations, drifts,…)

Raw Data
Processingelem. data

Problems:
Variability may be caused by many factors:
Charge Transfer Inefficiency due to Radiation
Damage on CCD
 Transit of parasitic stars onto the BAM CCD
 BAM device intrinsic variability (e.g. laser stability,optics,…)
 higher order aberrations variability in theTelescopes
…
Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200913

BAM/DASS

raw data
Raw Data
Processing
elem. data

Calibration
dataBAMCALibration

BAM
MODel

Need fora realistic BAM model and a algorithm to periodically determine thevalue of the parameters

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200914

BAM Model•BAM device optical design ismerged with the Gaia
telescopes optical design• Complete light-train coded(BAM+Telescopes)•enables complete
sensitivity analysis anddetermination of themost important degreesof freedom.
Image credit: Meijer et al., SPIE 7010

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200915

BAM Model / AnalyticalThe ray-tracing code is not suitable for easy and compact
description. -> analysis and translation into an analytical model

Current analytical description:

D   2πB
(xi − x0 ) fp (i, j ) = k ⋅ Airy rij  ⋅ 1 + V cos  λf  
 λf

where

 xi = R (i − i0 ) + 2 ⋅ δLOS ⋅ f
 y j = R ( j − j0 )Daniele Gardiol – BAM/DASSri =xi2 + yi2

ADASS XIX – Sapporo –October 4-8, 200916

BAM Models results - comparison
Raytracing-=AnalyticalDaniele Gardiol – BAM/DASS

Analytical / raytracing
discrepancies confined ~ 2-3%
without any param adjustement!

ADASS XIX – Sapporo –October 4-8, 200917

BAM Calibration
By calibration
we intend here the estimation of the value ofc
the parameters of the model that are frozen during thelocation estimation process. This is a crucial step to obtain
good final results.

Effect of over-/under- estimation of the image width
Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200918

BAM Calibration
in some cases (symmetric shape) the fringe locationestimation is unbiased, but the associated error increases
 in case of asymmetries and flux evaluation, estimation isbiased

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200919

BAM/DASS Core

raw data
Raw Data
Processing

Calibration
data

BAM
CALibration

BAM
MODelelem. data

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200920

Raw Data Processing algorithms
We want to compare the results from different algorithm types,
in order to chose the one that gives the best performances (alsoduring operations)
Currently we have three (four) algorithms implemented:
Maximum Likelihood (maximisation of the ML function)
 Least Squares (Minimisation of the LS function)
 Cross-correlation (Maximisation of the CC function)
 Barycentre

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200921

BAM/DASS Core

raw data
Raw Data
Processing

Calibration
data

BAM
CALibration

elem. data

RDP
Comparison

RDPC results

Daniele Gardiol – BAM/DASS

BAM
MODel

ADASS XIX – Sapporo –October 4-8, 200922

Long and Mid Term Analysis
Basic Angle variations will be found and determined
independently of BAM (on timescales > 1day) by the
astrometric solutions (AGIS, FL)
Mid and Long term analysis of the BAM measurements will allow
comparison with AGIS and FL estimates, thus enabling us toverify consistency between different systems.
Moreover, Mid and Long Term analysis can provide information
about variability on large timescales of some instrument
parameters

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200923

Basic Angle Variation Model

Sinusoidal behaviour
expected (P = 6 hours)
Thermal perturbation(M1#1 – M2#2)~ 200 µK peak to peakBA response~ 1200 µasDaniele Gardiol – BAM/DASSdBA/dT ~ 6 µas / µK
(Gardiol et al., SPIE 5497)

ADASS XIX – Sapporo –October 4-8, 200924

Monitoring of instrument performances

EXAMPLE: Monitoring the fringe period over time.

Fringe period is given by∆x p =λfB“True” value =4.95833 px



SINGLE MEASURE
 Estimated =4.95835 px
 σ=0.03237 px(6.5e-3)1080 MEASURES (~6 h) σ= 0.00098 px(2.0e-4)
Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200925

BAM/DASS Core

raw data
Raw Data
Processing

Calibration
data

BAM
CALibration

elem. data

RDP
Comparison

RDPC results

Long&Mid
T. Analysis

BAV
MODel

LMTA res.

LMTA
Comparison

BAM
MODel

LMTAC res.
AGIS/FL res

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200926

BAM/DASS

raw data
Raw Data
Processing

Calibration
data

BAM
CALibration

elem. data

RDP
Comparison

RDPC results

Long&Mid
T. Analysis

BAV
MODel

LMTA res.

LMTA
Comparison

BAM
MODel

LMTAC res.

AGIS/FL resDaniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200927

Bam/DASS Java architecture
Left: BAM Core
prototype implemented,
under testing
Right: Long/Mid Term
Analysys
under development
Top: Interfaces
Bottom: Implementations

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200928

Data Processing Center – Torino (Altec)
DPC-T Software System
Ing.
MDB
ESAC

Gaia
Binary
Files
GTS

GTS

Ext.

External Processing
Centres

WebServerGAIA
Community

DTS
Data Transfer
SubsystemRMS
Run ManagerSubsystem

DAAS
Data Access andAnalysis
Subsystem

PIS
Processing
InfrastructureSubsystem

SMAS
SystemMonitoring andAdministration
Subsystem

DSS
Data Storage
Subsystem

Data flow
Internal control flow
Internal processing control flow
DPCT operator interactions
DPCT scientist interactions

Daniele Gardiol – BAM/DASSDPCT Scientists
Workstation

ADASS XIX – Sapporo –October 4-8, 2009

DPCT Operator
Workstation

29

Conclusions• Basic Angle monitoring is crucial to reach Gaia astrometric expected
performances• Basic Angle monitoring at the required level of accuracy is challenging butfeasible• Criticality: realistic and faithful description of the fringe image(calibration). May depend on HW quality (stability over time).
• Data anaysis SW architecture defined (BAM SRS/SDD passed CDR)
• BAM core prototype modules implemented, currently under test at DPC-T• Experience acquired so far may be useful to other similar missions

Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200930

ADASS LIII (2043)
in Torino ?

Thank you!
Daniele Gardiol – BAM/DASSADASS XIX – Sapporo –October 4-8, 200931