Post on 23-Dec-2015
transcript
PSF estimation and parametric modelling from scientific data
Laura SchreiberIstituto Nazionale di Astrofisica – Osservatorio Astronomico di Bologna
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 2
Context
Adaptive Optics has become a key technology for all the main existing telescopes (VLT, Keck, Gemini, Subaru, LBT..) and is considered a kind of enabling technology for future giant telescopes (E-ELT, TMT, GMT).
AO systems increase the energy concentration of the Point Spread Function (PSF), but the PSF itself is also characterized by complex shape and spatial variation.
the exceptional advancement in AO technology and observational capability has not been followed by a comparable advancement in the development of data analysis methods.
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 3
Science with AO
Main science targets: Crowded stellar fields resolved stellar populations in GCs and
Galaxies (MCAO) Close binary systems improved angular resolution / dynamical
mass estimation (SCAO) Exoplanets (XAO, SCAO) Our Galaxy’s central black hole Mass estimation through
stars proper motions measurements (SCAO, MCAO) Distant galaxies morphology, spectroscopy (MCAO, MOAO)
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 4
Imaging techniques
Astrometry: precise measurements of the positions and movements of objects (parallax and proper motion)– Dynamical masses of brown dwarfs [Dupuy et al 2009]– Our Galaxy’s supermassive black hole [Ghez et al 2005]– Formation and evolution of young star clusters [Stolte et al 2008] …
Photometry: is the process of obtaining accurate numerical values for the brightness of objects (aperture phot./ PSF fitting). – Time variability of individual sources – Flux ratios or luminosity functions of multiple systems [Harayama et
al. 2008]– Color Magnitude Diagrams of resolved stars (GC age, stellar
population, stellar evolution, SFH) […]
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 5
How do the AO data look like?
Single Conjugate AO Highly structured PSF, small FoV
Galactic center, PUEO@ CFHT, K band
13 a
rcse
c
Courtesy of F. Rigaut
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 6
How do the AO data look like?
Single Conjugate AO Highly structured and variable PSF
M15 Core, @ Keck, K band Courtesy of L. Origlia
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 7
How do the AO data look like?
Single Conjugate AO Highly structured and variable PSF
21 a
rcse
c
1 pixel = 0.021 arcsecExposure Time = 6 s
M92, FLAO @ LBT, Pisces, J band GS
AO science demostration run
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 8
How do the AO data look like?
Multi Conjugate AO Improved PSF uniformity across a larger FoV
ωCen, MAD @ VLT, K band
1 ar
cmin
[Bono et Al 2009]
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 9
How do the AO data look like?Grabbed from F. Rigaut presentation at AO4ELT3, Florence 2013
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 10
AO results and limitations
SCAO small corrected FoV, PSF spatial variation– Crowded-field AO astrometry appears to be limited by the inaccurate
modeling of the Point Spread Function (PSF) [Shoedel 2010]– astrometry of faint sources is biased by residuals due to the incorrect
subtraction of the PSF of brighter stars [Fritz 2009]– photometric accuracy is limited by the SNR and by the knowledge
of the PSF [Shoedel 2010]– detection of elongated sources
– Many ‘exotic’ solutions have been found to reduce data…
Astrometric and photometric measurements with AO systems are mainly limited by errors in the PSF modeling and fitting.
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 11
AO results and limitations
SCAO small corrected FoV, PSF spatial variation– Galactic center (NACO): Image is first Wiener-filter-deconvolved
using a suitable PSF (GS psf) . Local variations in PSF kernels and ringing is taken care with locally extracted PSF fitting. [Schoedel 2010]
– M92 GC (FLAO): Modiefied Romafot software. PSFfitting with variable moffat (no parameters fixed). [Bono 2013 Ao4ELT3]
– NGC6440 GC (NACO): PSFfitting with starfinder using an analitical model composed by 3 gaussian components. [Origlia 2008]
– Usage of calibration images [Steinbring et al. (2002)] – Usage of calibration HST fields – Galaxy Survey (NACO): Estimate local PSF around guide star image
and model the PSF in the field as the convolution of the GS PSF and a blurring kernel. [Diolaiti 2000, Cresci 2006]
guide staroff-axis PSF blurring kernel(e.g. Gaussian)
=
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 12
AO results and limitations
MCAO To improve the PSF uniformity across the FoV– Suitable to study dense stellar field, galaxy morphology– MAD: Many papers have been pubblished [Melnick SPIE 2012 for a
review]– GeMs: First papers are coming out– Already available sofware have been used
Terzan5, MAD @ VLT, K band
The presence of two red clumps implies the presens of two different stellar populations. [Ferraro et Al, Nature, 2009]
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 13
SF: Exercise of variable PSF
FWHM ≈ 3.4 pxSR ≈ 0.01 ÷ 0.37Magnitude range ≈ 10 magHigh SNR
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 14
SF: Exercise of variable PSF
PSF fitting photometry using the true PSF model
Photometric error in the fainter magnitude bin ≈ 0.11
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 15
SF: Exercise of variable PSF
∆𝑚𝑎𝑔≅ 0.172521∆𝑚𝑎𝑔≅ 0.18
When the PSF varies across the FoV, the photometric error depends mainly on the goodness of the PSF model adoped
PSF fitting photometry using the guide star
1
0
-1
-2
-3
-4
-5
Photometric error in the fainter magnitude bin ≈ 0.7
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 16
SF: Exercise of variable PSF
PSF fitting photometry using the local PSF
Photometric error in the fainter magnitude bin ≈ 0.26 Photometric error in the fainter magnitude bin ≈ 0.14
To be compated with the error when perfect PSF is used ≈ 0.11
Photometric error in the fainter magnitude bin ≈ 0.11
3 X 3 subdomains9 X 9 subdomainsMore subdomains
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 17
PSF estimation I
PSF reconstruction: – the long exposure PSF within the isoplanatic angle from the reference
source can be expressed in terms of second-order statistics of the phase of the residual wavefront that can be computed from the AO loop data (i.e. WFS measurements, DM commands…) [Veran 1997]
– by knowing the Cn2 profile, it is possible to ‘generalize’ the method and model the PFS degradation in the FoV. It is therefore possible to compute (a posteriori) the PSF in any α direction within the FoV [Fusco 2000]
– Pros: No need of isolated bright stars for modeling the PSF, no extra observation time, available cronology of PSF variation in time
– Critical aspects: determination of the system’s static aberrations and of the optical turbulence paramenters; complexity (MCAO?)
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 18
PSF estimation II
PSF estimation from data:– Analytical PSF (constant or variable)– Numerical PSF (constant over the entire frame or in subdomains)– Hybrid PSF (analytical model + numerical residual map)– Product of the Blind deconvolution
Implemented in image analysis softwares:– DAOPHOT (analytical/hybrid/smoothly variable) [Stetson 1987]– Romafot (Purely analytic) [Buonanno 1983]– DoPHOT (Analytical) [Schecter 1993]– PSFex (analytical, linear combination of basis vectors) [Bertin 2010]– STARFINDER (numerical/analytical/hybrid, possible hacking) [Diolaiti
2000]– Dolphot (HSTPhot), …
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 19
Starfinder
Code for identification and analysis of point-like sources– Designed and developed (1997-2000) for images with structured
PSF but uniform across field of view – Numerical PSF– Written in IDL easy to hack– Graphical User Interface– Available on the Web
Target: to extend the usage of Starfinder to AO images with complex and spatially variable PSFs – Numerical local PSF by dividing the image in subdomains (MCAO)– Analitical model of the PSF and of its parameters vatiation
across the Fov by a multi-component parametric model (Gaussian, Moffat, Lorentzian) + map of residuals using information about AO (GS position, seeing, .. NGS SCAO)
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 20
PSF analytical model
3 Broad Gaussian/ Moffat halo
1 Narrow Moffat core2 External torus
3
1
2
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 21
SF variable PSF: analytical model
PSF fitting photometry using the estimated PSF model: method
Choose the PSF stars (bright, distributed in the FoV)
Choose of components for PSF modeling (first iteration one)
Fit of parameters variation with respect to the GS distance
Residual map = stars – model
STARFINDER
Photometry and stars positions
A priori knowledge of the rotation angle
Stack, combine and normalize residuals
PS
F r
efin
ing
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 22
SF variable PSF: analytical model
PSF fitting photometry using the estimated PSF model: results
Photometric error in the fainter magnitude bin ≈ 0.13
To be compated with the error when perfect PSF is used ≈ 0.11
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 23
SF variable PSF: analytical model
PSF fitting photometry using the estimated PSF model: real data
M15, FLAO @ LBT, Pisces, J band
1 - PSF stars selection: possibly bright and isolated
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 24
SF variable PSF: analytical model
2 – Definition of the analytical model: 2D Moffat 3 – Estimation of the Moffat parameters variation across the FoV
Product: PSF model + residual
Moffat majior axis variation model Moffat minor axis variation model
Flux variation model
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 25
SF variable PSF: analytical modelImage Synthetic Image model
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 26
SF variable PSF: Local PSF
PSF extraction from MAORY + MICADO simulated crowded stellar fields in distant ellipticals (Virgo cluster) [Schreiber 2013]– Map of Maory Phase A PSF – Different crowding conditions– Different regions of the FoV
Maory FoV
Micado FoV
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 27
SF variable PSF: Local PSS
The scope of the work was to explore the [effect of the] photometric error [on stellar metallicity distribution] as a function of the crowding and of the PSF variation across the FoV– Different crowding, central (best SR)
PSF telescope re-pointing– Same crowding, different PSFs (best and
worst SR) subdomains
Micado FoV
Comparable photometric error, but different zero points (fractions of magnitude) among different subdomains
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 28
Results
Simulated image: 2 moffat component– easy to model– promising photometric accuracy
Local PSF estimation: ideal for MCAO– Numeric robust– Tested on highly crowded simulated images (with typical MAORY
PSF variation) no effects on photometric accuracy– Possible drawback: different zero points
Ideal model for SCAO PSF: hybrid (analytical + residual)– Less analytical components implies more robustness (fit algorithms
easely converge on a small number of pixels)– The case of M15 the estimated residuals look indistinguishable
within 1σ assuming a constant residual map seems to be approprated
FP7-OPTICON PSF reconstruction meeting, Marseille 29-30 January 14 29
Future work
Implement in Starfinder a tool able to model the PSF Add more complex model of PSF parameters variation across the
FoV (maybe polynomials) application to MCAO images Small variation of the PSF parameters during the fitting of the field
stars; residual map look-up table Test it on real data and map the photometric error varying SNR
and PSF variation magnitude Put it on the web
‘My dream is to receive the data and the associated PSF for the data reduction’
[an astronomer using AO data]