wavefront sensing for adaptive optics

48
Wavefront sensing for adaptive optics MARCOS VAN DAM & RICHARD CLARE W.M. Keck Observatory

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Page 1: Wavefront sensing for adaptive optics

Wavefront sensing for adaptive

optics

MARCOS VAN DAM & RICHARD CLARE

W.M. Keck Observatory

Page 2: Wavefront sensing for adaptive optics

Wilson Mizner : "If you steal from one author it's

plagiarism; if you steal from many it's research."

Thanks to: Richard Lane, Lisa Poyneer, Gary Chanan,

Jerry Nelson

Acknowledgments

Page 3: Wavefront sensing for adaptive optics

Wavefront sensing

Shack-Hartmann

Pyramid

Curvature

Phase retrievalGerchberg-Saxton algorithm

Phase diversity

Outline

Page 4: Wavefront sensing for adaptive optics

Properties of a wave-front sensor

Localization: the measurements should relate to aregion of the aperture.

Linearization: want a linear relationship between thewave-front and the intensity measurements.

Broadband: the sensor should operate over a widerange of wavelengths.

=> Geometric Optics regime

BUT: Very suboptimal (see talk by GUYON on Friday)

Page 5: Wavefront sensing for adaptive optics

Effect of the wave-front slope

A slope in the wave-front causes an incoming photon

to be displaced by

There is a linear relationship between the mean slope

of the wavefront and the displacement of an image

Wavelength-independent

xzWx =

x

z

W(x)

Page 6: Wavefront sensing for adaptive optics

Shack-Hartmann

The aperture is subdivided using a lenslet array.

Spots are formed underneath each lenslet.

The displacement of the spot is proportional to the

wave-front slope.

Page 7: Wavefront sensing for adaptive optics

Shack-Hartmann spots

45-degree astigmatism

Page 8: Wavefront sensing for adaptive optics

Typical vision science WFS

Lenslets CCD

Many pixels per subaperture

Page 9: Wavefront sensing for adaptive optics

Typical Astronomy WFS

lensletsrelay lens

CCD

200 μ

2 mm

3.15 reduction

21 pixels

3x3 pixels/subap

Former Keck AO WFS sensor

Page 10: Wavefront sensing for adaptive optics

The performance of the Shack-Hartmann sensordepends on how well the displacement of the spot isestimated.

The displacement is usually estimated using thecentroid (center-of-mass) estimator.

This is the optimal estimator for the case where thespot is Gaussian distributed and the noise is Poisson.

=),(

),(

yxI

yxIxsx

Centroiding

=),(

),(

yxI

yxIysy

Page 11: Wavefront sensing for adaptive optics

G-tilt vs Z-tilt

The centroid gives the mean slope of the wavefront

(G-tilt).

However, we usually want the least-mean-squares

slope (Z-tilt).

Page 12: Wavefront sensing for adaptive optics

Due to read noise and dark current, all pixels arenoisy.

Pixels far from the center of the subaperture aremultiplied by a large number:

The more pixels you have, the noisier the centroidestimate!

= ),( yxIxsx

Centroiding noise

},3,2,1,0,1,2,3,{ LL=x

Page 13: Wavefront sensing for adaptive optics

The noise can be reduced by windowing the centroid:

Weighted centroid

Page 14: Wavefront sensing for adaptive optics

Can use a square window, a circular window:

Or better still, a tapered window, w(x,y)

Weighted centroid

= ),(),( yxIyxxwsx

= ),(),( yxIyxywsy

Page 15: Wavefront sensing for adaptive optics

Find the displacement of the image that gives themaximum correlation:

Use FFT or quadratic interpolation to find thesubpixel maximum correlation

Correlation (matched filtering)

)),(),(max(arg),( yxIyxwss xx =

=

Page 16: Wavefront sensing for adaptive optics

Noise is independent of number of pixels

Much better noise performance for many pixels

Estimate is independent of uniform backgrounderrors

Estimate is relatively insensitive to assumed image.

Correlation (matched filtering)

Page 17: Wavefront sensing for adaptive optics

In astronomy, wavefront slope measurements are

often made using a quad cell (2x2 pixels)

Quad cells are faster to read and to compute the

centroid and less sensitive to noise

Quad cells

4321

4321

IIII

IIIIs

x

+++

+=

4321

4321

IIII

IIIIsy

+++

+=

Page 18: Wavefront sensing for adaptive optics

These centroid is only linear with displacement over a

small region (small dynamic range)

Centroid is proportional to spot size

Quad cells

Displacement

Centroid

Centroid vs. displacement for different spot sizes

Page 19: Wavefront sensing for adaptive optics

When the photon flux is very low, noise in the

denominator increases the centroid error

Centroid error can be reduced by using the average

value of the denominator

Denominator-free centroiding

][ 4321

4321

IIIIE

IIIIs

x

+++

+=

][ 4321

4321

IIIIE

IIIIsy

+++

+=

Page 20: Wavefront sensing for adaptive optics

Shack-Hartmann subapertures see a line not a

spot

Laser guide elongation

Page 21: Wavefront sensing for adaptive optics

LGS elongation at Keck

Laser projected from right

Page 22: Wavefront sensing for adaptive optics

A possible solution for LGS elongation

Radial format CCD

Arrange pixels to be at

same angle as spots

Currently testing this

design for TMT

laser

Page 23: Wavefront sensing for adaptive optics

Pyramid wave-front sensor

Focal plane

Images of the aperture

(conjugate aperture plane)

Aperture plane

Pyramid (glass prism)

Lens to image the aperture

Page 24: Wavefront sensing for adaptive optics

Similar to the Shack-Hartmann using quad cells: it

measures the average slope over a subaperture.

The subdivision occurs at the image plane, not the

pupil plane.

Local slope determines which image receives the light

Pyramid wave-front sensor

Page 25: Wavefront sensing for adaptive optics

When the aberrations are large, the pyramid sensor is

very non-linear.

Pyramid wave-front sensor non-linearity

4 pupil images x- and y-slopes estimates.

Large focus aberration

Page 26: Wavefront sensing for adaptive optics

Modulation of pyramid sensor

Without modulation:

Linear over spot width

With modulation:

Linear over modulation width

Page 27: Wavefront sensing for adaptive optics

+

Pyramid + lens = 2x2 lenslet array

Pyramid

Relay lens

lenslets

Page 28: Wavefront sensing for adaptive optics

Duality between Shack-Hartmann and pyramid

Shack-Hartmann Pyramid

Low resolution

images of the object

Object

Low resolution

images of the aperture

Aperture

ApertureHigh resolution

image of the

object

Page 29: Wavefront sensing for adaptive optics

Duality between Shack-Hartmann and pyramid

Shack-Hartmann Pyramid

Page 30: Wavefront sensing for adaptive optics

Duality between Shack-Hartmann and pyramid

Shack-Hartmann

Aperture Focal Plane

Pyramid

Pixels in Shack-Hartmann = lenslets in PyramidLenslets in pyramid = pixels in Shack-Hartmann

Page 31: Wavefront sensing for adaptive optics

Multi-sided prisms

Pyramid uses 4-sided glass prism at focal plane

to generate 4 aperture images

Can use any N-sided prism to produce N aperture

images

Limit as N tends to Infinity gives the “cone” sensor

Cone

Relay lens

Aperture image

Aperture

Page 32: Wavefront sensing for adaptive optics

Wave-front at aperture

Aperture

Image 1

z

-z

Image 2

Curvature sensing

Page 33: Wavefront sensing for adaptive optics

Localization comes from the shorteffective propagation distance,

Linear relationship between thecurvature in the aperture and thenormalized intensity difference:

Broadband light helps reducediffraction effects.

Curvature sensing

Aperture

Defocused

image I1

Defocused

image I2

l

f l

lffz

)(=

Page 34: Wavefront sensing for adaptive optics

Curvature sensing

WIWIz

I= .

2

I

IWzWz

II

II+=

+.

2

12

12

Where I is the intensity, W is the wave-front

and z is the direction of propagation, we obtain

a linear, first-order approximation,

Using the irradiance transport equation,

which is a Poisson equation with Neumann

boundary conditions.

Page 35: Wavefront sensing for adaptive optics

Solution at the boundary

)()(

)()(

21

21

xx

xx

zWRxHzWRxH

zWRxHzWRxH

II

II

++

+=

+

I1

I2

I1- I2

If the intensity is constant at the aperture,

Page 36: Wavefront sensing for adaptive optics

Solution inside the boundary

)(21

21yyxx WWz

II

II+=

+

There is a linear relationship between the signal and

the curvature

The sensor is more sensitive for large effective

propagation distances

Curvature

Page 37: Wavefront sensing for adaptive optics

Curvature sensing

As the propagation distance, z, increases,

Sensitivity increases.

Spatial resolution decreases.

Diffraction effects increase.

The relationship between the signal, (I1- I2)/(I1+ I2)

and the curvature, Wxx + Wyy, becomes non-linear

)(21

21yyxx WWz

II

II+=

+

Subaru AO system will use two different propagation distancesA large distance for high sensitivityA short distance for high spatial resolution

Page 38: Wavefront sensing for adaptive optics

Curvature sensing

Practical implementation uses a variable curvature

mirror (to obtain images below and above the

aperture) and a single detector.

Page 39: Wavefront sensing for adaptive optics

Curvature sensor subapertures

Measure intensity in each subaperture with an

avalanche photo-diode (APD)

Detect individual photons – no read noise

Page 40: Wavefront sensing for adaptive optics

Wavefront sensing from defocused images

There are more accurate, non-linear, algorithms to

reconstruct the wavefront using defocused images

with many pixels

Defocused images True and reconstructed wavefronts

Page 41: Wavefront sensing for adaptive optics

Suppose we have an image and knowledge about the

pupil.

Can we find the phase, , that resulted in this image?

Phase retrieval

Page 42: Wavefront sensing for adaptive optics

Image is insensitive to:

Addition of a constant to (x).Piston does not affect the image

Addition of a multiple of 2 to any point on (x)Phase wrapping

Replacing (x) by - (-x) if amplitude is symmetricale.g., positive and negative defocused images look identical

Called the phase ambiguity problem

Phase retrieval

Page 43: Wavefront sensing for adaptive optics

Gerchberg-Saxton algorithm

Page 44: Wavefront sensing for adaptive optics

Phase retrieval suffers from phase ambiguity, slow

convergence, algorithm stagnation and sensitivity to

noise

These problems can be overcome by taking two or more

images with a phase difference between them

In AO, introduce defocus by moving a calibration source.

Phase diversity

Page 45: Wavefront sensing for adaptive optics

Phase diversity

+2 mm

-2 mm

-4 mm

Defocus

Page 46: Wavefront sensing for adaptive optics

Phase diversity

Poked actuators Minus poke phase Plus poke phase Difference

Page 47: Wavefront sensing for adaptive optics

Phase diversity

Theoretical diffraction-limited image Measured image

Page 48: Wavefront sensing for adaptive optics

Mahalo!