DPC SGS-IR – ESTEC – 24-26 January 2007 Francesca Perrotta – LFI DPC SGS2 M. On behalf of LFI...

DPC SGS-IR – ESTEC – 24-26 January 2007

Francesca Perrotta – LFI DPC SGS2 M.On behalf of LFI demo group.

Osservatorio Astronomico di Trieste,

SISSA- ISAS (Trieste),

Univ. Tor Vergata (Rome),

MPA (Garching),

Osservatorio Astronomico di Padova,

IASF (Bologna),

Univ. of Milano,

INAF Milano,

Helsinki Univ.,

Jodrell Bank Observatory,

Caltech

SGS2 OM-0 Tests Report


• Goal: make the SGS2 Pipeline commensurate with Planck scientific objectives.

• Verification plans are being followed • Scientifical performances assessed on the basis of

tests on prototypes.


• Goal: make the SGS2 Pipeline commensurate with Planck scientific objectives.

• Verification plans are being followed • Scientifical performances assessed on the basis of

tests on prototypes.

---------------------------------------------------------------------- • Integration status and improvements w.r.t. previous status (D. Maino)

• Operation planning (A. Gregorio)

• Pipeline tests results (F. Perrotta) [Reference: PL-LFI-OAT-RP–015, “Planck LFI- SGS2 End-to-end test report” ]

----------------------------------------------------------------------


Solid team of people involved in validation plan: Baccigalupi C. (SISSA), Balbi A. (Tor Vergata University, Roma) Banday A. (MPA Garching), Bersanelli M. (Milano Univ.), Bonaldi A. (OAPd), Burigana C. (IASF Bologna), Cappellini B. (Milano Univ.), Danese L. (SISSA), De Gasperis G. (Universita’ Tor Vergata, Roma) , De Zotti G. (Padova Observatory), Donzelli S. (Milano Univ.), Facchinetti S. (INAF Milano), Finelli F. (IASF Bologna), Gasparo F. (OAT), Gonzales-Nuevo J. (SISSA), Gruppuso G. (IASF Bologna), Keihanen E. (Helsinki Univ.), Kurki-Suonio H. (Helsinki Uni.) , Leach S. (SISSA), Leahy P. (Jodrell Bank Observatory), Lenardon L. (INAF Milano), Mandolesi N. (IASF Bologna), Massardi M. (SISSA), Mennella A. (Milano University), Natoli P. (Universita’ Tor Vergata, Roma), Pasian F. (OAT), Perrotta F. (OAT), Platania P. (Milano Univ.), Poutanen T. (Helsinki Univ.), Reinecke M. (MPA Garching), Rocha G. (Caltech), Sandri M. (IASF Bologna), Stivoli F. (SISSA), Stringhetti L. (IASF Bologna), Tomasi M. (INAF Milano), Villa F. (IASF Bologna), Zacchei A. (OAT)

(LFI demo group)


Solid team of people involved in validation plan: Baccigalupi C. (SISSA), Balbi A. (Tor Vergata University, Roma) Banday A. (MPA Garching), Bersanelli M. (Milano Univ.), Bonaldi A. (OAPd), Burigana C. (IASF Bologna), Cappellini B. (Milano Univ.), Danese L. (SISSA), De Gasperis G. (Universita’ Tor Vergata, Roma) , De Zotti G. (Padova Observatory), Donzelli S. (Milano Univ.), Facchinetti S. (INAF Milano), Finelli F. (IASF Bologna), Gasparo F. (OAT), Gonzales-Nuevo J. (SISSA), Gruppuso G. (IASF Bologna), Keihanen E. (Helsinki Univ.), Kurki-Suonio H. (Helsinki Uni.) , Leach S. (SISSA), Leahy P. (Jodrell Bank Observatory), Lenardon L. (INAF Milano), Mandolesi N. (IASF Bologna), Massardi M. (SISSA), Mennella A. (Milano University), Natoli P. (Universita’ Tor Vergata, Roma), Pasian F. (OAT), Perrotta F. (OAT), Platania P. (Milano Univ.), Poutanen T. (Helsinki Univ.), Reinecke M. (MPA Garching), Rocha G. (Caltech), Sandri M. (IASF Bologna), Stivoli F. (SISSA), Stringhetti L. (IASF Bologna), Tomasi M. (INAF Milano), Villa F. (IASF Bologna), Zacchei A. (OAT)

(LFI demo group)

Strict link between scientific production and data analysis


• Instrument parameters reconstruction: computes the R gain modulation factor for each detector and determine the noise parameters (knee frequency, slope of the 1/f noise component, white noise NET) for each detector, together with an estimate of the relative errors.

• Photometric Calibration: determines the calibration constant(s). Calibration is performed both on short timescales to monitor the instrument stability, and on long timescales to provide an accurate “absolute” calibration.

• Pointing and beam reconstruction: reconstructs the pointing of each detector given the Spacecraft pointing, and obtain maps of the main beam patterns for each feed-horn.

• Single channel and frequency map making: map making tools are used to produce single channel maps and final optimal combination maps.

The SGS2 LFI Om-0 - capabilities


The SGS2 LFI Om-0 - blocks

Main sub-pipelines:

1

2 4

3


Towards Phase I of End-to-end Tests

• Only temperature processing requested by Phase I definitions. However, we could make use of polarization simulated data too;

• the sky model is based on the “concordance model” CMB (no non-gaussianity);

• the dipole does not include sub-modulations due to Lissajous orbit around L2;

• the Galactic emission obtained assuming non-spatially varying index;

• non-idealities in the instrumental properties are not included: the detector model is “ideal” and does not vary with time;

• the scanning strategy (baseline Level S) is “ideal” (no gaps in the data); however, we were able to use realistic feed horn beam patterns, though the patterns are assumed constant within the bandwidth.


Test procedures - generalities

The execution of Phase I OM-0 tests performed in parallel: specific inputs are provided to be used in a single test. The four main blocks of processing have been tested through individual ProC sub-pipelines. For each test are given:

1. Detailed test objectives;2. Participants;3. Definition of simulations;4. Specs. on the input data to DPC5. Hardware and infrastructure to run the tests

6. Specs. of the tests outputs (list of parameters Xi)

7. I/O comparison: x =xs-xm and r=m/x

(Figures of merit PASS/FAIL CRITERIA)


Tests platform (hardware, libraries, formats)

• SGS2 Pipeline installed on the Beowulf system OAT. Actual LFI DPC resources: 44 CPUs with a total of 38 GB of RAM and 2.2 TB of disk space. The DPC uses the PBS queueing system. We use the following queues:

planck: 18 node x 2 processors (18 Intel Pentium III)

fast: 4 node x 2 processors (4 Opteron Dual Core).

• Individual Pipeline units are Fortran 90 and C++ modules. Also used MPI parallel codes interface. External libraries included: FITSIO and FFTW .

• Inputs files for tests are FITS files; all the Pipeline procedures compatible with the LFI TOI DPC format and with the MPA-DMC fits implementation. The use of the MPA-DMC will be simply inserted just recompiling the SGS2 pipeline with the appropriate libraries. The LFI DPC is actually ingesting the data into the database.


Input data (simulations)LFI-demo simulated 12 months (8784 rings) time streams for the two horns of the 30 GHz channel (LF 27 and LFI 28), two radiometers each. All the simulations generated on the Beowulf system, at the OAT. The TODs are in FITS format (with nside nside=2048, 1’ resolution) and include:• the 30 GHz reference sky (noiseless CMB from WMAP data; galactic

emission from synch., free-free, dust, thermal SZ). The dipole components are added during the TODS production;

• bright point sources (radio + IR) and planets; (The radio sources are constrained simulations using WMAP data, and the NVSS, SUMMS and PMN surveys. IR basically from IRAS)

• two independent realizations of white noise; 1/f noise

Optics: Main beams have been computed with GRASP9, propagating the measured pattern of the feed horns #27 and #28 through the ideal telescope. The focal plane database file has been modified, according to the values obtained during the FM RCA test campaign.

Scanning strategy: baseline


R factor

Inputs (produced at Level S in the actual LFI TOI DMC): -Signal TOI (diffuse em., tot. dipole,bps)+ wn(1)-TOI from nominal wn params; convolved with 30 GHz beam.

-Reference TOI (Tload = 4.5 K)

+wn(2)

The pipeline generates R by averaging over 1 hr of obs. sky and load signals, foreach radiometer.


R factor

NOTE: accuracy on the

reconstruction of R notfully representative of thatachievable during flight. Uncertainty in R dominated by the total 1/f noise in sky and load signals. This wasnot generated for this test.


Noise properties I

• After R determination, the pipeline creates differential data stream as V=Vsky–RVload.

A realization of 1/f residual noise TOI is added to V. The total time stream is given as input to noise_ps which produces the resulting noise power spectrum.

• From the noise power spectrum, Fitnoise_GT estimates the white noise limit, knee frequency f* and slope , as well as the relative errors.

• PS on 1 hr data, 24 hr data, and on the average of 24 hr data.

• 1 hr Spectra obtained by averaging over 24 cycles in a day.


Noise properties II

Estimated power specrum of signal + noise


Noise Power spectrum after removal of signal estimate. (Destriping is first applied; resulting map is re-observed according to pointing parameters).

Noise properties III

f* (knee frequency) Hz

(slope) w.noise

Input value 0.050 1.7 1.027 x 10 -3

Pipeline

Output

0.052 ± 0.001

(1 1.690 ±0.005

(1 (1.026 ± 0.049) x10-3 (1

f * 0.02

0.003

0.477

Rel. errors on noise params.


Beam reconstruction IProvides a parameterised model of the Planck-LFI beams and an estimate of

the focal plane geometry based on LFI data alone (initial guess of the FP

geometry is assumed based on the knowledge from instrument integration

phase). The beam response averaged over the bandwidth is approximated as:

))(),(,()(),,( 2121 RdR

The beam shape in the x-y plane is described by a bivariate Gaussian:

]2/2/exp[),,( 22

22

21

221 1

AAR

where

and sin)(cos)( 001 yyxxA

cos)(sin)( 002 yyxxA


Beam reconstruction II

Gdestribeamfit

S/C pointing FP geom.

LFI 30 GHz horns

Beam params.

I/O comparison: we computed the (r.m.s.) reconstruction sensitivity (x) for each

parameter. The error in each specific realization is in good agreement with the

quoted sensitivity.

2ln8)( 2/121 FWHM

beambeambeam =

y)ellipticit (beam / 21beambeam e

OUTPUTS:x,y (coordinates of the main beam on the focal plane); (orientation of the beam, i.e. anti-clock rotation angle of the elliptical bivariate Gaussian w.r.t. the x field of view axis);

axis) beam refer to and ( 21beambeam


Beam reconstruction III

Detect.. 100x 100y (deg) beam

(arcmin)

beam

e

e

27

3∙10 -4

1.7∙10-4

4 ∙10-4

2.3∙10-4

0.12

0.06

0.009

0.005

6∙10-4

3.5∙10-4

1.6∙10-3

9 ∙10-4

1.2∙10-3

7 ∙10-4

Same precision for detector #28


Map makingMaps for the single channels, using the whole detectors data set. Two approaches have been used:

• Madam, based on the destriping technique + infos on the noise spectrum in the form of a noise filter. The low-frequency noise component is modelled as sequence of constant offsets or 'baselines‘ determined by maximum likelihood analysis. The baseline length is an adjustable input parameter. The baselines are subtracted from the TOD, and the remaining TOD is binned into a map.

• Roma, GLS map making code. ROMA maps are “optimal” (minimum variance; built taking into account exact pixel-pixel covariance)

Simulations:

• Signal = CMB+synchrotron+dust+free-free+faint point sources+ SZ• 12 months TODs for the four LFI 30 GHz detectors. Cycloidal scanning.• Asymmetric beams. • Perfect calibration, dipole removal and R factor.• All maps are Nside 512.


Map making- MADAM resultsThree destriping methods were used:A. 1 hour baselines, standard mode, noise filter OFFB. 1 min baselines, split-mode, noise filter OFFC. 1.2 sec baselines, split-mode, noise filter ON

In standard mode all data are processed simultaneously. In split-mode, data are

processed in pieces, 2 months at a time. The optimal map-making method (1.2

sec baselines, standard mode, noise filter ON) couldn’t run on the present

Beowulf configuration.

• Noise filter parameters:

f knee = 0.05 Hz; f min = 1.15e-5 Hz; slope = -1.7. White noise level is not needed.

• Madam makes no assumptions about beam shape. Output map includes smoothing by the beam.

• The code outputs the map in the units of the TOD.

Map making- MADAM results

3

LFI 30 GHz MADAM Signal+Noise Output Map – Nside 512- 1 min baselines

(Min, Max, Rms, Mean) = (-660, 34070, 812, 416) R-J K

Madam output: 30 GHz Temperature map


Madam output: 30 GHz U and Q map

4

LFI 30 GHz

(Min, Max, Rms, Mean) = (-5093, 4402, 202, 1.8) R-J K

(Min, Max, Rms, Mean) = (-4247, 5618, 204, 0.8) R-J K

MADAM Signal+Noise Output Map – Nside 512- 1 min baselines

Madam - Residual maps (output – binned noiseless)

5

LFI 30 GHz RESIDUAL MAP – Nside 512- 1 min baselines

R-J K

Q, U RESIDUAL MAPS – Nside 512 – MADAM, 1 min baselines

R-J K

R-J K


Madam- Angular Power Spectra

Power spectra of the CMB, signal plus noise, smoothed reference, signal bin and residual (noisy output-binned noiseless map). 1 min baseline. Horizontal dashed line: expected spectrum of the white noise

Angular Power Spectra - MADAM

Polarization analysis: Q and U angular power spectra of the CMB, signal plus noise, smoothed reference, signal bin and residual (noisy output map and the binned noiseless map). 1 min baseline. The horizontal dashed lines indicate the expected spectrum of the white noise.


Madam vs. ROMA- Angular Power Spectra of Residual Maps.

Temperatureanalysis

Polarization analysis

EE and BB cross spectra

Madam vs. ROMA- Angular Power Spectra of Residual Maps.

T,Q,U = theoretical rms of white noise map

l

l

BBl

EEl

UQl

l

l

TTl

Tl CC

lC

l

2'''

&

2'' 8

1'2

4

1'2

222 , UQpBBl

EElTp

TTl CCC

1) Residual: ClXX = spectrum of the residual map

2) White noise:

3) Residual 1/f: ClXX = difference of above two spectra

Madam- 1hr baseline Residual 1/f - Madam vs. Roma


Baselines 1 houra 1 mina 1.2 secb

MADAM Map Rms Map RMS Map RMS White theoreticalc

T 34.58 32.68 32.57 32.45Q 48.81 46.18 46.02 45.83U 49.30 46.62 46.45 46.26

ROMAb

T 33.21Q 46.90U 47.38

Units areK (R-J @ 30 GHz).a – without noise filterb – with noise filterc – White noise RMS is derived from the block diagonal approximation of the pixel-pixelnoise covariance.

Madam vs. ROMA- Residual maps Rms


Open areas

• We performed the tests for the 30 GHz LFI channels, from simulated TODs up to single channel and frequency maps. Same has to be done for the other channels.

• Test calibration sub-pipeline• Realistic estimate of R (total power 1/f noise included)• The extraction of the astrophysical and cosmological informations from

these outputs (the “Level 3” of Data Processing), requiring the separation of the CMB signal from foregrounds emission, is a high-priority target. Mostly important for Polarization.

• Perform tests with serial execution with the use of ProC+DMC with DB as back end

• e2e Tests should be completed by end of May 2007• Straylight effects (Phase II ?)


Conclusions

• Verification plans are being followed;

• internal tests show that the SGS2 OM-0 LFI DPC Pipeline is actually able to reconstruct the main “Phase-I” parameters up to a quite good precision level;

• open areas clearly identified;

• schedule for main targets established;

• limitations imposed by CPU power should not be an issue;

• data processing and Scientific competences are closely linked in the actual LFI SGS2 team structure;

• team management proceeding smoothly;

• Interface HFI/LFI being implemented in the Operation Plan; effort is being produced in clarify how the SGS2 Pipeline will be operated.

DPC SGS-IR – ESTEC – 24-26 January 2007 Francesca Perrotta – LFI DPC SGS2 M. On behalf of LFI...

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Transcript of DPC SGS-IR – ESTEC – 24-26 January 2007 Francesca Perrotta – LFI DPC SGS2 M. On behalf of LFI...