February 2013

Ground Layer Adaptive Optics (GLAO) Experiment on Mauna Kea

Doug Toomey

The Imaka ProjectThis talk is about an experiment in support of a larger project

called IMAKA

IMAKA is a project to build a wide field imager for large telescopes that has improved image quality by using a type of adaptive optics called Ground Layer Adaptive Optics (GLAO)

Adaptive optics involves the correction of atmospheric induced optical aberrations (seeing) using electronically controlled deformable mirrors

IMAKA achieves corrections over much larger fields than present instruments by only fixing atmospheric aberrations close to the ground

Imaka Science

Examples of the projects this is useful for are:

Galaxy Formation and Evolution

Finding and Studying Kuiper Belt Objects

Resolving Stellar Populations of Nearby Galaxies

Traditional Adaptive optics

Traditional adaptive optics systems are limited in field of view because as the field increases the star light travels through different paths in the upper atmosphere.

This limits corrected fields to about 1 arcminute

Ground Layer Adaptive optics

Experiments on Mauna Kea in Hawaii have shown that the turbulence is primarily found in two layers. One at or near the ground and one in the upper atmosphere.

Ground Layer Adaptive optics

By just correcting this lower layer a much larger field can be corrected and still produce a useful improvement reducing the image size from 0.5 to 1.25 arcseconds down to 0.3 to 0.4 arcseconds

The ground turbulence aberrations and the telescope dome induced aberrations are removed.

Proof

How could we prove that this technique would work on a large telescope.

CFHT funded us last year to perform an experiment on the UH 2.2 meter and the 3.6 meter CFHT telescopes, to try to verify, on-the-sky, the level of performance we can achieve.

Do we really see large correlations of the wavefronts over these large angles when we look thru the telescope?

`Imaka has the goal to reach the “free-atmosphere” seeing over large fields of

view (e.g. 10’s of arcminutes to a degree)

Tests on the UH 2.2 meter

Our foundation: Site studies with numerous optical turbulence profilers: SLODAR, LOLAS, LunarShabar, MKAM (MASS/DIMM)

Each of these studies was done “outside” - e.g. not thru one of the big telescopes.

Question: Is there something fundamentally different arising within the telescope enclosures?

We started on the UH 2.2 meter telescope since we could get more time

The Experiment

Approach:

Following Baranec (2007) - On Mt. Hopkins, in support of MMT GLAO, observe a constellation of stars with multiple wavefront sensors to measure the phase correlations and estimate the GLAO PSF over a 2’ FOV.

➡ We would use five wavefront sensors, on a constellation of stars covering 0.5 degree on UH88” (Cassegrain) and 1 deg on CFHT (prime).

Wavefront sensor

Imaging the telescope entrance pupil (the primary mirror) onto a 2d array of lenses (Lenslet array) turn the 2 meter telescope into 400 9 cm telescopes.

Measuring the star position from each sub-aperture measures the wavefront tilt in each sub aperature

Shack Hartmann wavefront sensor

mWFS experiment

✓ UH88: Prototype WFS - July `12

✓ UH88: 5 WFSs 0.5 deg - September `12

‣ CFHT: 6 WFS 1.0 deg - Dec/Jan `13

‣GL and dome seeing - direct measure of the correlation of wavefronts over one degree

Sch

ed

ule

mWFS/UH88

• Using the optics for the UH8k camera replacing the focal plane with our five WFSs

• First two runs were in September.

• Observed two different constellations

What the data looks like...

What the data looks like...

This is a combination of SHWFS spots from three WFSs. Each WFS is a different color in

the image.

When the wavefronts are correlated the spots are white

When the wavefronts are uncorrelated the spots separate into distinct colors

0.25°

0.5

°

What can we learn from this data

What the data tells us...These are the slope cross-covariance maps...

A layer at the ground moving with

the ground wind speed?

What the data tells us...

From the data we can extract a number of quantitative measures:

Simplest:

Total phase variance (seeing)

We can extract the vertical profile (where in altitude the seeing comes from the ground up to about 600 meters)

What portion of the seeing is common to all wavefront sensors ( the GLAO correctable part of the aberations)

An estimate of the image size that a GLAO system could achieve

What the data tells us...am

pli

tud

e (

nm

)

time step (50Hz)

What the data tells us...

Next steps...

Next phase is a GLAO demonstrator on the 88” proposal with NSF pending

Working our way thru an incredibly rich data set

The Experiment Team

Mark Chun (UH) PI

Olivier Lai (CFHT)

Tim Butterley (Durham University)

Doug Toomey (MKIR)

Kevin Ho and Derrick Salmon (CFHT)

Yutaka Hayano/Shin Oya (Subaru) - contributing DM/electronics for demonstrator

Simon Thibault (Lavel University) - optical design of demonstrator

Christoph Baranec (CalTech) - real-time controller from RoboAO