TIPS/JIM
February 18, 2010
Agenda:
INS News (Jerry Kriss)
The "Happy Bunny": Characterizing Long-Wavelength Fringing in
WFC3/UVIS
HST Focus using Phase Retrieval on WFC3 Images
Optimization Strategies for the NIRSpec MSA Planning Tool
Next TIPS/JIM: March 18, 2010
1
Instruments Division News
02/18/2010
•
Farewell to Michael Wong, who will head back to Berkeley at the end of next week.
Thank you, Mike, for your help and expertise over the past year.
•
HST news:
o Cycle 18 proposals are due next Friday, February 26.
•
JWST News:
o A crucial milestone for JWST---tests of the first cryo-polished primary
mirror segment at the Marshall Space Flight Center X-ray Cryogenic
Facility prove that the plan of doing just 1 cryo-polishing cycle will prove
acceptable. The residual wave front errors are low enough to give good
performance down to 1 micron and shorter.
•
Planning continues for this summer’s calibration workshop, July 21-23, here at
STScI. A preliminary announcement and web site will go up shortly.
TIPS/JIM
February 18, 2010
Agenda:
INS News (Jerry Kriss)
The "Happy Bunny": Characterizing Long-Wavelength Fringing in
WFC3/UVIS
HST Focus using Phase Retrieval on WFC3 Images
Optimization Strategies for the NIRSpec MSA Planning Tool
Next TIPS/JIM: March 18, 2010
1
The “Happy Bunny:” Characterizing LongWavelength Fringing in WFC3/UVIS
Mike Wong
INS/WFC3 Visiting Scientist
2010-02-18 TIPS/JIM
1
Outline
•  What is fringing?
•  The fringe model
–  thanks: Eliot Malumuth
•  The ground test data sets
–  thanks: DCL staff, Howard Bond, Elizabeth Barker, S. Rinehart,
Bob Hill, Bryan Hilbert, Howard Bushouse, Jen Mack, Ray Lucas,
Megan Sosey, André Martel, Linda Dressel
•  Fitting data with the model
•  Correcting on-orbit data
2010-02-18 TIPS/JIM
2
What is fringing?
•  Silicon grows transparent at long wavelengths
•  Multiple internal reflections
•  Interference effects (constructive/destructive)
–  strong sensitivity to wavelength
–  strong sensitivity to detector layer thickness
•  The curse becomes the cure:
–  measure fringe patterns at multiple wavelengths
–  determine thickness of detector layer
–  use model to predict fringe patterns for any wavelength or SED
2010-02-18 TIPS/JIM
3
Filters affected by fringing
2010-02-18 TIPS/JIM
4
Monochromatic fringe flat
TV3 data
977 nm
2010-02-18 TIPS/JIM
5
Histogram
TV3 data
977 nm
2010-02-18 TIPS/JIM
6
The fringe model
•  Model described in Malumuth et al. (2003 Proc. SPIE
4854, 567-576)
–  used to correct STIS slitless spectroscopic data
•  Solves the Fresnel equations:
–  continuity of electromagnetic field components across layer
boundaries
–  multi-layer model
•  Model inputs:
–  light wavelength and incidence angle
–  layer thicknesses and roughnesses
–  layer indices of refraction (n + ik), based on composition
2010-02-18 TIPS/JIM
7
Model schematic
Table: Malumuth et al. (2003)
2010-02-18 TIPS/JIM
8
Test data
•  DCL data
–
–
–
–
2001-12-06 to 2001-12-12
detector chips tested separately, not integrated
incident light angle 0°
146-151 (monochromatic) wavelengths/chip, nominally 700–1060 nm
•  TV3 data
–
–
–
–
2008-03-28 to 2008-04-12
detectors integrated into the instrument
flight-like incidence angle of 21°
78 (2-nm FWHM) wavelengths/chip, 845–990 nm
2010-02-18 TIPS/JIM
9
Test data
•  Basic processing
–  DCL chip 2, commanded
wavelength = 760.26 nm
–  overscan/bias
–  flatfield
–  CR/hot pixels
2010-02-18 TIPS/JIM
10
Test data
2010-02-18 TIPS/JIM
11
Test data
Data for 1 pixel in Quad A
2010-02-18 TIPS/JIM
12
Test data
Data for 1 pixel in Quad A,
Bandpasses of UVIS filters affected by fringing
2010-02-18 TIPS/JIM
13
Deriving thicknesses
•  For 1 pixel, best
thickness
minimizes
residuals between
model and data at
all wavelengths
•  Problem: DCL
and TV3 data sets
give different
answer !!
2010-02-18 TIPS/JIM
14
Thickness maps
TV3 data only (other maps being developed)
Black: 13.5 µm thick, White: 17.5 µm thick
2010-02-18 TIPS/JIM
15
Reconciling TV3/DCL data sets
•
•
•
•
•
Order errors? No.
Basic processing, or normalization methods? No.
Errors in DCL and TV3 incident angles? No.
Anti-reflective coating index of refraction? No.
Wavelength error in DCL data?
–
–
–
–
Malumuth: DCL wavelengths could be off by 2–3 nm (But, no.)
comprehensive test of wavelength error provided surprising result...
actual wavelengths shorter than commanded wavelengths by about 20 nm
scale factor of 0.972 ± 0.003 gives best result
2010-02-18 TIPS/JIM
16
Optimal λ determination
•  For this frame, commanded λ = 997.35 nm
(black point)
•  Calculate whole-chip
residuals between:
–  this DCL data frame at
0° incidence
–  0° model with TV3derived parameters
•  Minimum residual yields
chip-averaged optimal
wavelength, in this case
969.4 nm (red point)
•  Procedure repeated for
each frame to get full
spectrum of optimal vs.
commanded wavelengths
2010-02-18 TIPS/JIM
17
Optimal λ spectrum
•  Strong systematic
relationship between
commanded and optimum
wavelengths
•  Best parameterization:
–  constant scale factor at
all wavelengths
–  higher-order fits not
justified
•  scatter in data
•  lack of physical
explanation for
wavelength errors
2010-02-18 TIPS/JIM
18
Constant scale factor...
•  Order errors cycle
periodically through mean
scale factor "α", so more
confidence in this
parameterization
•  Fun note:
If λopt / λcmd = α , then:
λopt / λcmd = ncmd / nopt
•  So finding a constant scale
factor is like finding an
error in the index of
refraction for the DCL
experiments...
2010-02-18 TIPS/JIM
19
(or n error)
•  Data could be
construed as indicating
an experimental index
of refraction of
1.029 ± 0.003
•  This is close to the
index of refraction of
aerogel of 1.024–1.026
(Poelz & Riethmüller,
1982, Nuc. Instr.
Meth. Phys. Res. 195,
491-503)
2010-02-18 TIPS/JIM
20
On-orbit test data
On-orbit test data
•  Cycle 17 calibration data to be collected in 2 (for sure) or all filters
affected by fringing
•  Photometry in Omega Cen
•  Data will allow comparison of models
•  On-orbit test data is best way to verify fringe corrections extrapolated
beyond ground test data range
•  Another correction approach: create fringe models based on restricted
wavelength ranges of test data (Kalirai)
–  may compensate for uncertainty in silicon index of refraction as a function of
wavelength
2010-02-18 TIPS/JIM
22
TIPS/JIM
February 18, 2010
Agenda:
INS News (Jerry Kriss)
The "Happy Bunny": Characterizing Long-Wavelength Fringing in
WFC3/UVIS
HST Focus using Phase Retrieval on WFC3 Images
Optimization Strategies for the NIRSpec MSA Planning Tool
Next TIPS/JIM: March 18, 2010
1
HST Focus Monitoring
&
Phase Retrieval on WFC3
Sami-Matias Niemi (niemi@stsci.edu)
together with
Matt Lallo, George Hartig, Colin Cox
and
John Krist (JPL) & Richard Hook (ESO)
TIPS/JIM meeting, Feb. 18 2010
Outline
How to measure focus?
HST Focus monitoring results
Phase Retrieval
Process of trying to recover the wavefront
error for a given PSF.
Iteratively fitting an observed PSF and
expressing it in terms of a Zernike Polynom.
Nonlinear, similar to deconvolution.
Was used to measure aberrations in HST
mirrors (Burrows 1991; Fienup 1993).
Modeling a PSF
Courtesy: J. Fienup
Mirror Maps
Krist J.E., Burrows C.J., 1995, Applied Optics, 34, 22
Observed vs. Model PSF
Krist J.E., Burrows C.J., 1995, Applied Optics, 34, 22
Zernike Polynomials?
Are a set of orthogonal polynomials that
arise in the expansion of a wavefront
function for optical systems with circular
pupils!
Piston
Tilt (x & y)
Astigmatisms
Focus (0, 2)
Clovers (-/+3,3)
Comas (-/+1, 3)
Higher
order
terms
Implementation of WFC3
Requirements:
Camera pixel size & focal length
Pupil Image with offset mirror maps
Charge Diffusion Kernels (Hartig)
Geometric Distortion Coeffs. (Cox, Platais...)
Modify the existing IDL software
Fix higher order Zernike polynomials
Focus monitoring Data
Proposal 11877:
WFC3 and ACS in parallel
2 WFC3 UVIS and 5 ACS WFC exposures
per orbit (currently, but shall change)
Object NGC 188-73 (open cluster)
Executes once a month
ACS: F502N, WFC3: F410M (currently)
ibcy10bkq_flt
Pupil
Image
HorzCross
Data
VertCross
Model
HorzCross
Residuals
VertCross
Focus Measurements
Focus Stars of ibcy09usq Chip 1
2000
Star 5
Star 3
Star 6
1500
1000
Star 2
500
Star 1
Star 4
0
0
0.0
1000
0.3
0.6
2000
0.9
1.2
1.5
1.8
log10 (Counts)
3000
2.1
4000
2.4
2.7
3.0
Focus Measurements
8
Focus Measurement (No breathing correction)
ACS chip 1
WFC3 chip 1
ACS chip 2
WFC3 chip 2
Mean + standard err
6
Defocus [SM µm]
4
2
0
−2
−4
01:26:23
01:33:35
01:40:48
01:47:59
08 Jan 2010
01:55:11
02:02:24
02:09:35
Focus Measurements
Focus Measurement
10
ACS chip 1
WFC3 chip 1
ACS chip 2
WFC3 chip 2
Mean + standard err
8
Defocus [SM µm]
6
4
2
0
−2
−4
01:26:23
01:33:35
01:40:48
01:47:59
08 Jan 2010
01:55:11
02:02:24
02:09:35
HST Focus Trends
Days since HST Deployment
Accumulated OTA shrinkage [SM µm]
150
0
1000
2000
3000
4000
5000
6000
7000
Double Exponent Fit
No breathing correction
100
50
0
24
Apr
1990
15
Dec
1991
06
Aug
1993
29
Mar
1995
18
Nov
1996
11
Jul
1998
02
Mar
2000
23
Oct
2001
15
Jun
2003
04
Feb
2005
27
Sep
2006
19
May
2008
09
Jan
2010
01
Sep
2011
HST Focus Trends
Focus Trend Since Dec 2002 Mirror Move
Mirror Movement
No Breathing correction
No Breathing correction (WFC3)
Linear Regression
Exponent Fit
Exponent Fit Cont.
5
0
5000
5500
6000
2.97µm
5.34µm
4.16µm
-5
3.6µm
Accumulated Defocus [SM µm]
10
6500
Days since HST deployment
7000
HST Focus Trends
Focus Trend Since Dec 2002 Mirror Move
Mirror Movement
Breathing corrected
Breathing corrected (WFC3)
Linear Regression
Exponent Fit
Exponent Fit Cont.
5
5000
5500
6000
2.97µm
5.34µm
-5
4.16µm
0
3.6µm
Accumulated defocus in SM microns
10
6500
Days since HST deployment
7000
HST Focus Trends
Focus Trend Since Dec 2004 Mirror Move
Mirror Movement
Breathing corrected
Breathing corrected (WFC3)
Linear Regression
Exponent Fit
Exponent Fit Cont.
5500
6000
2.97µm
-5
5.34µm
0
4.16µm
Accumulated defocus in SM microns
5
6500
Days since HST deployment
7000
HST Focus Trends
Focus Trend Since Dec 2002 Mirror Move
Mirror Movement
Breathing corrected
Breathing corrected (WFC3)
Linear Regression
Exponent Fit
10
5
5000
5500
6000
Days since HST deployment
2.97µm
5.34µm
-5
4.16µm
0
3.6µm
Accumulated Defocus [SM µm]
15
6500
7000
Conclusions
WFC3 UVIS phase retrieval works and is
being used for focus monitoring.
Some changes to the current program to
better sample each orbit with WFC3.
Predicted Zero-crossing dates:
April 2010 (data since 2002)
Dec 2010 - Feb 2011 (using all focus data)
WFC3 perhaps -0.5 micron compared to ACS
Thank You!
TIPS/JIM
February 18, 2010
Agenda:
INS News (Jerry Kriss)
The "Happy Bunny": Characterizing Long-Wavelength Fringing in
WFC3/UVIS
HST Focus using Phase Retrieval on WFC3 Images
Optimization Strategies for the NIRSpec MSA Planning Tool
Next TIPS/JIM: March 18, 2010
1
Optimization Strategies for the
NIRSpec MSA Planning Tool
The image cannot be displayed. Your
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James Muzerolle
Special thanks to NIRSpec teamlet members and
APT developers:
Diane Karakla
Tracy Beck
Jason Tumlinson
Jeff Valenti
Tom Donaldson
Rob Douglas
Karla Peterson
Quick NIRSpec overview
•
•
•
•
3 spectroscopic modes: MOS, fixed slit, IFU
3 resolutions: R ~ 100 (prism), 1000 and 2700 (gratings)
effective wavelength range 0.6 – 5 microns
FOV ~ 3.6’ x 3.4’
Microshutter Array (MSA)
4 x 365 x 171 shutters,
individually addressable
shutter pitch = 0.26” x 0.51”,
(actual FOV = 0.2” x 0.45”)
activated with magnet sweep
prism spectral layout
R=2700 spectral layout
MSA planning tool prototype
(APT v17.0.3)
Preliminary optimization study
•  IDL code to simulate planning tool analysis of target
placement within MSA shutters
•  heuristic iterative scheme to optimize the number of
targets per MSA configuration from an input
“candidate” target sample
–  grid of MSA center pointings and position angles
–  optimized solution = grid point with largest number of targets
–  loop for multiple configurations
•  test cases to evaluate various parameters:
–
–
–
–
–
input sample size/spatial distribution
number of “sky” shutters
including known failed shutters
dithers
target priorities
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Default test case:
•  UDF-derived input candidate target catalog (1009 objects)
•  3x3 center pointing grid, 20.1” x 36.2” offsets
•  3-shutter slitlet
•  ideal MSA
•  1 configuration per target set (no cross-slitlet dithers)
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Default test case with failed shutters
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Default test case with failed shutters,
2-shutter slitlet
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Default test case with failed shutters,
1-shutter dither (0.26”) in dispersion direction
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Default test case with failed shutters,
detector gap dither (18”)
prism spectral layout
R=2700 spectral layout
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Optimization results
# cand
Targ Set 1
Targ 1/2
Config 1/2
Fails?
Test case
1009
102
407
5
n
1 center
1009
102
534
6
n
3x3 center grid, 3-shutter slitlets
1009
80
508
8
y
1009
118
505
5
y
2-shutter slitlets
1009
76
545
9
y
shutter dither (0.26”)
1009
65
510
11
y
gap dither (17.9”)
1000
64
519
11
y
concentrated source distribution
25
9
16
2
y
sparse sample, 3 orients
1009 (99, 100)
71 (24, 11)
528 (88, 76)
8
y
target priorities
Recommendations
•  Tool should incorporate iterative scheme for optimizing the number
of targets in a configuration using a grid of center pointings and/or
position angles.
•  Account for “acceptance zone” where flux losses are minimized.
•  Failed shutters must be tracked and updated. No targets in failed
closed. Generate warnings for targets in rows with failed opens.
•  Include an option for dithers requiring separate configurations (e.g.,
detector gap coverage), for an arbitrary number of dithers.
•  Target priorities, with an arbitrary number of layers, should be a
key part of the optimization scheme.
•  Include a diagnostic plot summarizing characteristics of all targets
in a given configuration, such as relative shutter position, priority,
dither status, user-defined properties (magnitude, redshift, etc).
To do
•  optical distortion across the FOV must be included, with the ability
to update the distortion solution as needed
•  better treatment of prism spectra (can fit more than one in the same
shutter row without overlap)
•  target acquisition: visualization and selection of reference stars,
avoiding failed closed shutters
•  explore more observing scenarios