1. An Off-Axis Hartmann Sensor for Measurement of Wavefront Distortion in Interferometric Detectors Aidan Brooks, Peter Veitch, Jesper Munch Department of Physics, University of Adelaide

2. Objectives Improve operation of advanced interferometers by reducing thermally induced wavefront distortion. Develop a sensor to measure the distortion and correction in the ACIGA High Optical Power Test Facility.

3. Crux of thermal problem Absorbed power causes ‘thermal lensing’ Prediction of MELODY model of Advanced LIGO Sideband power is scattered out of TEM 00 Instrument failure at approximately 2 kW Adv. LIGO cannot achieve desired sensitivity unaided Courtesy of Ryan Lawrence and David Ottaway, MIT

4. How to maintain cavity finesse? Measure distortion with wavefront sensor Employ active compensation system Sensor cannot interfere with core optics or GWI laser beam. OFF-AXIS WAVEFRONT SENSOR

5. Why use a Hartmann wavefront sensor? Interferometry Shack-Hartmann Hartmann –Easiest to align –Cheap –In principle, can measure a wavefront change of less than /1000

6. Hartmann wavefront sensor Record spot positions on CCD Wavefront changes  spot positions change Gradient of wavefront change proportional to displacement of spot. CCD

7. Off-Axis Bench Top Test Hartmann plate

8. Comparison of Hartmann sensor with interferometry demonstrated accuracy Line - Off axis fit Data – Interferometric fringe distortion Hartmann data analyzed using quasi-orthogonal functions. Lack of orthogonality results in systematic errors OPD (waves/100 at 633nm)

9. Determine wavefront distortion using optical tomography Cylinder of transparent material with internal temperature/refractive index distribution

10. Determine wavefront distortion using optical tomography Divide into annular volume elements (voxels)

11. Determine wavefront distortion using optical tomography Fitting functions are off-axis projections of voxels

12. Simulation of tomography Temperature distribution in ITM of AdLIGO-like system modelled using Hello-Vinet equation Off-axis optical path distortion (OPD) through this distribution determined OPD used as input data for a least-squares-fit to voxel projections Internal temperature distribution reconstructed On-axis OPD determined from reconstruction and compared to OPD predicted by theory

13. Simulation results Original off-axis OPDBest fit with voxel projections

14. Tomographic analysis is accurate input, reconstructed

15. Implementation of tomography Hartmann sensor used to measure OPD gradient field Gradient field used to reconstruct phase distortion (OPD) using iterative process Tomographic analysis determines temperature distribution from reconstructed OPD On-axis OPD determined from reconstructed temperature distribution

16. Initial measured precision ~ /120 Measured using ‘double snap’ – no heating 0 nm5.6 nm2.8 nm

17. Conclusion Single view, off-axis Hartmann, tomographic wavefront sensor has sufficient accuracy to measure cylindrically symmetric refractive index distributions in advanced interferometers Accuracy of ~ /1000 (simulation). Current precision ~ /120 (measured) CCD noise precision limit ~ /500 Can extend to non-cylindrically symmetric distributions – use multiple views and azimuthal voxelation

18. Interpreting Off-Axis View Distortion interferometer seesDistortion we see X Y X Y

19. Analyzing distortion using functional decomposition n(r) =  a i f i (r)  (x, y)=  a i g i (x, y)  (r)= C  a i f i (r) g i (x, y) are path integrated f i (r) LSQ fit to appropriate fns g i (x, y) Coefficients reveal on-axis distortion Most appropriate functions f i (r) are elusive z r

20. Simulated Sensitivity Test Radius (mm) Optical Path Difference ( /1000 ) Radius of curvature = 1570m