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Tomographic Reconstruction for Single Conjugate Adaptive Optics

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Time-dependent Problems in Imaging and Parameter Identification
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Abstract

Single Conjugate Adaptive Optic systems use the light of one bright guide star and a deformable mirror to correct for the loss of image quality of earthbound astronomical telescopes caused by turbulences in the atmosphere. The system achieves best correction in guide star direction. The imaging quality of the scientific object, which is usually separated from the guide star, can further be improved if the turbulence distribution is known. We propose to use wavefront sensor measurements from the past to recover the turbulence in the atmosphere. Mathematically, a limited angle tomography problem has to be solved. We present a model for the related tomography equations and discuss solvability and uniqueness of the solutions. Based on our analysis we develop an algorithm for the inversion and obtain a first numerical reconstruction.

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References

  1. D.R. Andersen, S.S. Eikenberry, M. Fletcher, B.L. William Gardhuose, J.-P. Veran, D. Gavel, R. Clare, R.G.L. Jolissaint, R. Julian, W. Rambold, The MOAO system of the IRMOS near-infrared Multi-Object Spectrograph for TMT, in Proceedings of the SPIE, vol. 6269 (2006)

    Google Scholar 

  2. G. Auzinger, New reconstruction approaches in adaptive optics for extremely large telescopes. PhD thesis, Johannes Kepler University Linz, 2017

    Google Scholar 

  3. M. Davison, The ill-conditioned nature of the limited angle tomography problem. SIAM J. Appl. Math. 43, 428–448 (1983)

    Article  MathSciNet  Google Scholar 

  4. V. Dhillion, Adaptive optics. http://www.vikdhillon.staff.shef.ac.uk/teaching/phy217/telescopes/phy217/_tel/_adaptive.html

  5. E. Diolaiti, A. Baruffolo, M. Bellazzini, V. Biliotti, G. Bregoli, C. Butler, P. Ciliegi, J.-M. Conan, G. Cosentino, S. D’Odorico, B. Delabre, H. Foppiani, T. Fusco, N. Hubin, M. Lombini, E. Marchetti, S. Meimon, C. Petit, C. Robert, P. Rossettini, L. Schreiber, R. Tomelleri, MAORY: a multi-conjugate adaptive optics relay for the E-ELT. Messenger 140, 28–29 (2010)

    Google Scholar 

  6. B. Ellerbroek, C. Vogel, Inverse problems in astronomical adaptive optics. Inverse Probl. 25, 063001 (2009)

    Article  MathSciNet  Google Scholar 

  7. B. Ellerbroek, L. Gilles, C. Vogel, A computationally efficient wavefront reconstructor for simulation or multi-conjugate adaptive optics on giant telescopes. Proc. SPIE 4839 (2002)

    Google Scholar 

  8. T. Fusco, J.-M. Conan, G. Rousset, L. Mugnier, V. Michau, Optimal wave-front reconstruction strategies for multi conjugate adaptive optics. J. Opt. Soc. Am. A 18, 2527–2538 (2001)

    Article  Google Scholar 

  9. L. Gilles, B. Ellerbroek, Split atmospheric tomography using laser and natural guide stars. J. Opt. Soc. Am. 25, 2427–2435 (2008)

    Article  Google Scholar 

  10. L. Gilles, B. Ellerbroek, C. Vogel, Layer-oriented multigrid wavefront reconstruction algorithms for multi-conjugate adaptive optics. Proc. SPIE 4839 (2002). https://doi.org/10.1117/12.459347

  11. L. Gilles, B. Ellerbroek, C. Vogel, Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics. Appl. Opt. 42, 5233–5250 (2003)

    Article  Google Scholar 

  12. L. Gilles, B. Ellerbroek, C. Vogel, A comparison of multigrid V-cycle versus Fourier domain preconditioning for laser guide star atmospheric tomography, in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, Washington, 2007)

    Google Scholar 

  13. G.H. Golub, C.F. Van Loan, Matrix Computations (The Johns Hopkins University Press, Baltimore, 2013)

    MATH  Google Scholar 

  14. F. Hammer, F. Sayède, E. Gendron, T. Fusco, D. Burgarella, V. Cayatte, J.-M. Conan, F. Courbin, H. Flores, I. Guinouard, et al., The FALCON concept: multi-object spectroscopy combined with MCAO in near-IR, in Scientific Drivers for ESO Future VLT/VLTI Instrumentation ESO Astrophysics Symposia (2002), pp. 139–148

    Google Scholar 

  15. T. Helin, M. Yudytskiy, Wavelet methods in multi-conjugate adaptive optics. Inverse Probl. 29, 085003 (2013)

    Article  MathSciNet  Google Scholar 

  16. R.A. Horn, C.R. Johnson, Topics in Matrix Analysis (Cambridge University Press, Cambridge, 1991)

    Book  Google Scholar 

  17. F. Natterer, The Mathematics of Computerized Tomography (Wiley, New York, 1986)

    Book  Google Scholar 

  18. A. Neubauer, R. Ramlau, A singular-value-type decomposition for the atmospheric tomography operator. SIAM J. Appl. Math. 77, 838–853 (2017)

    Article  MathSciNet  Google Scholar 

  19. M. Pöttinger, R. Ramlau, G. Auzinger, A new temporal control approach for SCAO systems. Inverse Probl. 36, 015002 (2019)

    Article  MathSciNet  Google Scholar 

  20. M. Puech, H. Flores, M. Lehnert, B. Neichel, T. Fusco, P. Rosati, J.-G. Cuby, G. Rousset, Coupling MOAO with integral field spectroscopy: specifications for the VLT and the E-ELT. Mon. Not. R. Astron. Soc. 390, 1089–1104 (2008)

    Article  Google Scholar 

  21. S. Raffetseder, R. Ramlau, M. Yudytskiy, Optimal mirror deformation for multi conjugate adaptive optics systems. Inverse Probl. 32, 025009 (2016)

    Article  MathSciNet  Google Scholar 

  22. R. Ramlau, M. Rosensteiner, An efficient solution to the atmospheric turbulence tomography problem using Kaczmarz iteration. Inverse Probl. 28, 095004 (2012)

    Article  MathSciNet  Google Scholar 

  23. R. Ramlau, A. Obereder, M. Rosensteiner, D. Saxenhuber, Efficient iterative tip/tilt reconstruction for atmospheric tomography. Inverse Probl. Sci. Eng. 22, 1345–1366 (2014)

    Article  MathSciNet  Google Scholar 

  24. F. Rigaut, B. Ellerbroek, R. Flicker, Principles, limitations and performance of multiconjugate adaptive optics. Proc. SPIE 4007, 1022–1031 (2000)

    Article  Google Scholar 

  25. C. Robert, J.-M. Conan, D. Gratadour, L. Schreiber, T. Fusco, Tomographic wavefront error using multi-LGS constellation sensed with Shack-Hartmann wavefront sensors. J. Opt. Soc. Am. A 27, A201–A215 (2010)

    Article  Google Scholar 

  26. F. Roddier, Adaptive Optics in Astronomy (Cambridge University Press, Cambridge, 1999)

    Book  Google Scholar 

  27. M.C. Roggemann, B. Welsh, Imaging Through Turbulence. Laser and Optical Science and Technology Series (CRC Press, New York, 1996)

    Google Scholar 

  28. M. Rosensteiner, Wavefront reconstruction for extremely large telescopes via CuRe with domain decomposition. J. Opt. Soc. Am. A 29, 2328–2336 (2012)

    Article  Google Scholar 

  29. M. Rosensteiner, R. Ramlau, The Kaczmarz algorithm for multi-conjugate adaptive optics with laser guide stars. J. Opt. Soc. Am. A 30, 1680–1686 (2013)

    Article  Google Scholar 

  30. D. Saxenhuber, R. Ramlau, A gradient-based method for atmospheric tomography. Inverse Probl. Imaging 10, 781–805 (2016)

    Article  MathSciNet  Google Scholar 

  31. M. Tallon, I. Tallon-Bosc, C. Béchet, F. Momey, M. Fradin, E. Thiébaut, Fractal iterative method for fast atmospheric tomography on extremely large telescopes, in Proc. SPIE 7736, Adaptive Optics Systems II (2010), pp. 77360X–77360X–10

    Google Scholar 

  32. E. Thiébaut, M. Tallon, Fast minimum variance wavefront reconstruction for extremely large telescopes. J. Opt. Soc. Am. A 27, 1046–1059 (2010)

    Article  Google Scholar 

  33. Q. Yang, C. Vogel, B. Ellerbroek, Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography. Appl. Opt. 45, 5281–5293 (2006)

    Article  Google Scholar 

  34. M. Yudytskiy, T. Helin, R. Ramlau, Finite element-wavelet hybrid algorithm for atmospheric tomography. J. Opt. Soc. Am. A 31, 550–560 (2014)

    Article  Google Scholar 

  35. M. Zhariy, A. Neubauer, M. Rosensteiner, R. Ramlau, Cumulative wavefront reconstructor for the Shack-Hartman sensor. Inverse Probl. Imaging 5, 893–913 (2011)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The work of the authors was partially supported by the Austrian Science Fund (FWF), project F 6805-N36: SFB Tomography Across the Scales and by the Austrian Ministry of Research (Hochschulraumstrukturmittel) in the project Observation oriented Astrophysics in the ELT era. Both authors would like to thank Roland Wagner and Markus Pöttinger for fruitful discussions.

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Correspondence to Ronny Ramlau .

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Niebsch, J., Ramlau, R. (2021). Tomographic Reconstruction for Single Conjugate Adaptive Optics. In: Kaltenbacher, B., Schuster, T., Wald, A. (eds) Time-dependent Problems in Imaging and Parameter Identification. Springer, Cham. https://doi.org/10.1007/978-3-030-57784-1_11

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