Wavefront Sensing - Heriot-Watt...
Transcript of Wavefront Sensing - Heriot-Watt...
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Wavefront Sensing Wavefront Sensing @ Heriot@ Heriot--WattWatt
What we are doing and why!What we are doing and why!
Heather CampbellHeather Campbell
Durham Workshop 14Durham Workshop 14thth December 2005December 2005
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Talk OutlineTalk Outline
Brief description of the GPD wavefront Brief description of the GPD wavefront sensorsensorThe Small Angle ExpansionThe Small Angle Expansion–– Why? What? How?Why? What? How?–– IssuesIssues–– Preliminary Results (Beijing)Preliminary Results (Beijing)–– Current workCurrent workWhere do we go from here?Where do we go from here?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
PD with Diffractive OpticsPD with Diffractive Optics
OrderIMP®
B 0
A +1
C -1A B C
Source Image
Figure 1: Shows the design of thecurrent wavefront sensor.
Quadratically distorted Quadratically distorted defocus grating.defocus grating.
Images of different Images of different object layers are object layers are recorded on the same recorded on the same focal plane focal plane [1].[1].
The plane separation The plane separation and image locations are and image locations are determined by the determined by the properties of the grating.properties of the grating.
Note: IMP® is a DERA (now QinetiQ) trademark
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
GPD ~ How we get error signalsGPD ~ How we get error signals
Diffraction Grating Diffraction Grating –– applies diversity to the input applies diversity to the input wavefront.wavefront.Intensity images in the Intensity images in the ±±1 orders contain the 1 orders contain the wavefront convolved with the diversity function.wavefront convolved with the diversity function.We use the difference between these intensity We use the difference between these intensity images to form the error signal d(r). images to form the error signal d(r). When the input wavefront is unaberrated the When the input wavefront is unaberrated the ±±1 1 images are identical and d(r) is zero.images are identical and d(r) is zero.
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Small Angle Expansion ~ Why?Small Angle Expansion ~ Why?We need an algorithm to retrieve the phase of We need an algorithm to retrieve the phase of the input wavefront the input wavefront –– preferably this will be an preferably this will be an analytic solution.analytic solution.
We want an algorithm that works for any We want an algorithm that works for any allowable diversity function (unlike the Greenallowable diversity function (unlike the Green’’s s function or Nugent algorithm.)function or Nugent algorithm.)
We want the algorithm to be robust, capable of We want the algorithm to be robust, capable of dealing with scintillated and discontinuous dealing with scintillated and discontinuous wavefronts.wavefronts.
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
The Error SignalThe Error Signal
Formed by the difference between the intensity Formed by the difference between the intensity images in the images in the ±±1 diffraction orders.1 diffraction orders.
Full details of the error equation and how we Full details of the error equation and how we derived it can be found in Optics Letters derived it can be found in Optics Letters 2929(23): p. 2707(23): p. 2707--2709 (2004) [2]2709 (2004) [2]
The small angle approximation has been used The small angle approximation has been used to linearise this equation and allow us to solve to linearise this equation and allow us to solve for the phase of the unknown wavefront.for the phase of the unknown wavefront.
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Small Angle Expansion ~ What?Small Angle Expansion ~ What?
We will use this familiar mathematical trick to We will use this familiar mathematical trick to derive a solution for the retrieved phase.derive a solution for the retrieved phase.
The derivation itself is not difficult, here I will The derivation itself is not difficult, here I will restrict this talk to a brief summary of the most restrict this talk to a brief summary of the most important parts.important parts.
And now for a little bit of mathsAnd now for a little bit of maths……..
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
A little bit of mathsA little bit of maths……
Let a wavefront be given by:Let a wavefront be given by:
( )( )0( ) expr A i rψ ϕ=
The Small Angle Approximation [SAA]:The Small Angle Approximation [SAA]:
When ( ) 1rϕ ≈
( )( ) ( ) ( )2exp 1i r s i sϕ ϕ ϕ≈ − +
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
A little bit of mathsA little bit of maths……Consider the wavefront as being made up of a Consider the wavefront as being made up of a real and an imaginary part:real and an imaginary part:
( ) ( ) ( )r h r ia rψ = +
Then under the SAA:Then under the SAA:
( ) ( )2 40( ) 1 ( )h r I r O rϕ ϕ⎡ ⎤= − +⎣ ⎦
( ) ( ) ( )30 ( )a r I r O rϕ ϕ⎡ ⎤= −⎣ ⎦
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
A little bit of mathsA little bit of maths……
Ignoring higher order terms, and Ignoring higher order terms, and assuming no/moderate scintillation:assuming no/moderate scintillation:
0( )h r I≈
( ) ( )0a r I rϕ⎡ ⎤≈ ⎣ ⎦
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
A little bit of mathsA little bit of maths……The error signal is the result of the convolution of The error signal is the result of the convolution of the input wavefront with the blur function {the FT of the input wavefront with the blur function {the FT of the diversity filter function}.the diversity filter function}.
We can show (and will soon publish):We can show (and will soon publish):
( ) ( ) ( )4 ( )
ird r d T eh r
ξξ ξ ξ −= Φ∫Error Signal
Real part of theinput wavefront
FT Wavefront phase
FT Phase Transfer Function
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Solving for the phase:Solving for the phase:
( )( )( )
( )Where ( )4 ( )
h
h
DT
d rDh r
ξξξ
ξ
Φ =
⎡ ⎤= ℑ⎢ ⎥
⎣ ⎦
Data Conditioning
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
What does this mean?What does this mean?
We can reconstruct the phase using an error We can reconstruct the phase using an error signal that we measure, and a Phase Transfer signal that we measure, and a Phase Transfer Function (PTF)Function (PTF)
The PTF is defined by the diversity function that The PTF is defined by the diversity function that we choosewe choose
We can choose/design a PTF to suit specific We can choose/design a PTF to suit specific applications!applications!
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Properties of the SAEProperties of the SAE
We know that the error signal is the result of We know that the error signal is the result of the convolution of the wavefront phase with the convolution of the wavefront phase with the PTF/blur functionthe PTF/blur function
What does this look like and what does What does this look like and what does this tell us about the SAE?this tell us about the SAE?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
The Convolution ProcessThe Convolution Process
wavefront
blur function
⊗
What happens here?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
IssuesIssues
3. What happens if the data is noisy?3. What happens if the data is noisy?
2. What happens at the boundary?2. What happens at the boundary?
1. What exactly do we mean by 1. What exactly do we mean by ““smallsmall”” angle?angle?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
““SmallSmall”” AnglesAngles
The PV of the wavefront error is not the problem!The PV of the wavefront error is not the problem!
The PV step and slope The PV step and slope over the area of the blur over the area of the blur functionfunction is the issue, and should obey SAE.is the issue, and should obey SAE.
However, we will still encounter problems at the However, we will still encounter problems at the edges!edges!
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
High slope example High slope example -- 11
Constant
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
High slope example High slope example -- 22
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
IssuesIssues
3. What happens if the data is noisy?3. What happens if the data is noisy?
2. What happens at the boundary?2. What happens at the boundary?
1. What exactly do we mean by 1. What exactly do we mean by ““smallsmall”” angle?angle?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Hard Edge Example Hard Edge Example --11
The shape isn’tbad but there are large amplitude
errors
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Hard Edge Example Hard Edge Example --22
SAME PROBLEM!
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Hard Edge SimulationsHard Edge Simulations
In all the simulations conducted using a hard In all the simulations conducted using a hard edge pupil the general retrieved shape was edge pupil the general retrieved shape was good, but there were large amplitude errors.good, but there were large amplitude errors.
This could be indicative of a boundary value This could be indicative of a boundary value problemproblem……..
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Using a Soft Edged PupilUsing a Soft Edged Pupil
In the hard edge simulations we observed In the hard edge simulations we observed amplitude errors which may indicate a amplitude errors which may indicate a boundary problemboundary problem
When the blur function reaches the edge, When the blur function reaches the edge, what happens if it sees a gradual slope, what happens if it sees a gradual slope, instead of a sudden drop?instead of a sudden drop?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Soft Edge Pupil SimulationsSoft Edge Pupil Simulations
Here we see the same
example, but this
time the fit is much better!
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
IssuesIssues
3. What happens if the data is noisy?3. What happens if the data is noisy?
2. What happens at the boundary?2. What happens at the boundary?
1. What exactly do we mean by 1. What exactly do we mean by ““smallsmall”” angle?angle?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Regularisation IssuesRegularisation Issues
Earlier we saw that the wavefront phase can Earlier we saw that the wavefront phase can be retrieved using the following equation:be retrieved using the following equation:
( )( )( )
( )Where ( )4 ( )
h
h
DT
d rDh r
ξξξ
ξ
Φ =
⎡ ⎤= ℑ⎢ ⎥
⎣ ⎦
What happens when the data is noisy?
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Noisy DataNoisy Data……..
( ) ( )( )( )
h hD NTξ ξξ
ξ+
Φ =
Classic regularisation problem!Classic regularisation problem!
→ → →∞As ( ) 0, ( ) 0 but ( ) !!!h hT D Nξ ξ ξ
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Properties of the PTFProperties of the PTF
Regions where the Phase Transfer
Function goes to zero cause regularisation
problems!
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Preliminary Results (Beijing)Preliminary Results (Beijing)The Error Signal
20 40 60 80
20
40
60
80 -2
0
2
x 104
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Preliminary ResultsPreliminary Results
• The direction of asymmetry in the SAE solution accords betterwith the asymmetry of the error signal.
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Simulated (noiseless) ResultsSimulated (noiseless) Results
• The shape and orientation of the phase profile are correct, butthere is as yet an unexplained scaling error contained in the SAE
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
Other IssuesOther Issues
Boundary Problems:Boundary Problems:Can we get a better result by reconstructing the Can we get a better result by reconstructing the imaginary part of the wavefront instead?imaginary part of the wavefront instead?
Data ConditioningData ConditioningWhat is the best function to use?What is the best function to use?
0( )( ) , ( )
4 ( )hd rD h r Ih r
ξ⎡ ⎤
= ℑ ≈⎢ ⎥⎣ ⎦
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Heather Heather -- Durham Workshop Durham Workshop -- 14.12.0514.12.05
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our website!our website!For theFor the latestlatest resultsresults and news from the Heriotand news from the Heriot--
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