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Fast E2E simulation tools and calibration strategies for EAGLE-MOAO on the E-ELT. Manal Chebbo, Alastair Basden , Richard Myers, Nazim Bharmal , Tim Morris, Thierry Fusco, Jean-Francois Sauvage.

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slide1

Fast E2E simulation tools and calibration strategies for EAGLE-MOAO on the E-ELT

Manal Chebbo, Alastair Basden, Richard Myers, NazimBharmal, Tim Morris, Thierry Fusco, Jean-Francois Sauvage

Manal Chebbo AO4ELT3 30 May 2013

dasp vs e2e s durham ao simulation platform vs e2e sparse lam onera
DASP VS E2E-SDurham Ao Simulation Platform VS E2E- Sparse (LAM / ONERA)
  • Conventional MVM dense
  • Sparse methods utilized.
  • Atmosphere to Slopes slow but accurate model.
  • Typically needs to run for several hours to simulate 10 – 100 s of operational time, but with high fidelity…
  • Sparse methods only.
  • Atmosphere to Slopes fast but approximated model.
  • Speed comparable to analytical codes, but capabilities of E2E codes, for ex: Optical tolerance studies…

Chebbo et al 2011

AO4ELT2

Basden et al 2007

Manal Chebbo AO4ELT3 30 May 2013

synopsis
Synopsis
  • Sparse E2E Simulator
  • DASP Simulator
  • Conclusion and Perspective

Manal Chebbo AO4ELT3 30 May 2013

synopsis1
Synopsis
  • Sparse E2E Simulator
  • DASP Simulator
  • Conclusion and Perspective

Manal Chebbo AO4ELT3 30 May 2013

slide5

Sparse E2E Simulator

  • AO in blocks

Configuration system

Turbulent generator

WFS model

Tomographicreconstructor

DM model

Manal Chebbo AO4ELT3 30 May 2013

slide6

Sparse E2E Simulator

  •  Description of the different modules
  • Configuration System

Manal Chebbo AO4ELT3 30 May 2013

slide7

Sparse E2E Simulator

  •  Description of the different modules
  • Turbulence generator
  • Generate layers in the form of pixilated phase screen
  • Simulation and computation of white noise FT
  • Inverse FT → real part
  • d/r0
  • Wind speed, direction for the considered layer

Manal Chebbo AO4ELT3 30 May 2013

slide8

Sparse E2E Simulator

  • Description of the different modules
  • Wave Front SensorSparse-Model
  • RealisticsparseGeometry Model of Shack-Hartman WFS
  • Illuminated and partlyilluminatedsubapertures are managed
  • RCO/RCO_d FORMAT :

(Representation Complete and Ordered)

Ds = {rco}

Ds.r = 2* Ns2

Ds.c = N2

Ds.n = 4* nb_pix* Ns2

Ds.ix = ptr_new([0,make_array(D.r, /long)])

Ds.jx = ptr_new(lonarr(D.n + bandwidth))

Ds.xn = ptr_new(make_array(D.n+ bandwidth, /float))

400 subapertures / 308 are fully or partlyilluminated in the pupil

Manal Chebbo AO4ELT3 30 May 2013

slide9

Sparse E2E Simulator

  • Description of the different modules
  • SparseWave Front Reconstruction
  • Sparse noise covariance matrix Cn
  • Noise are not correlated
  • noise is uniform
  • Turbulence covariance matrix

Manal Chebbo AO4ELT3 30 May 2013

slide10

Sparse E2E Simulator

  • Description of the different modules
  • Deformable Mirror sparse-Model
  • DM with sparse influence functions
  • Ifs profile ~ double Gaussian
  • IF = 0 beyondNacinf
  • Fs→ RCO→ [ N2 , Nact-valid]

64*64 actuators , Nacinf= 4 Nacinf= 6

  • 30% of mechanical coupling for minimizing the fitting error.

Manal Chebbo AO4ELT3 30 May 2013

slide11

Sparse E2E Simulator

  • Challenges of AO with Tomography
  • Tip, Tilt and Defocus Indetermination
  • Goal: Generate realistic WFS measurement’s with filtered out TTF
  • We modify the slopes to remove any tip tilt or defocus

Manal Chebbo AO4ELT3 30 May 2013

S

TTF

slide12

Sparse E2E Simulator

  • Challenges of AO with Tomography
  • Tip, Tilt and Defocus Indetermination
  • We search the transformation matrix M to an orthogonal space whichexludes TTF
  • 2 methods present :
  • Setting mean slopes to zero.
  • M contain all the modes generated by the AO system.

Manal Chebbo AO4ELT3 30 May 2013

slide13

Sparse E2E Simulator

  • Challenges of AO with Tomography
  • Tip, Tilt and Defocus Indetermination

Subtraction of averageslopes

Method-1

  • TT is reduced to 7%
  • Defocus is not filtered

Manal Chebbo AO4ELT3 30 May 2013

slide14

Challenges of AO with Tomography

  • Tip, Tilt and Defocus Indetermination
  • M contains the WFS answer to all the modes generated by the system

Method - 2

Karhunen–Loève

TTF are filtered out

Manal Chebbo AO4ELT3 30 May 2013

synopsis2
Synopsis
  • Sparse E2E Simulator
  • DASP Simulator
  • Conclusion and Perspective

Manal Chebbo AO4ELT3 30 May 2013

dasp vs e2e s
DASP VS E2E-S
  • Conventional MVM dense
  • Sparse methods utilized.
  • Atmosphere to Slopes slow but accurate model.
  • No, Simple only TT
  • Sparse methods only.
  • Atmosphere to Slopes fast but approximated model
  • TTF filtered out.

Chebbo et al 2011

AO4ELT2

Basden et al 2007

Manal Chebbo AO4ELT3 30 May 2013

slide17

DASP

  • Durham AO Simulation Platform
  • Python and C
  • MPI, shared memory, and multi-threaded
  • Suitable for ELT-scale problems
  • Cross checked with other codes: Octopus (42 m), YAO (4.2 m), Fourier (ONERA) (42 m)...

Manal Chebbo AO4ELT3 30 May 2013

slide18

DASP

  • EAGLE E2E DASP-simulations
  • Simulation Parameter:
  • 42 m, central obscuration = 6 m
  • R0 = 13.5 cm @ 500 nm.
  • L0= 30 m
  • SH With 84*84
  • LGS closed loop GLAO with M4 and the same with open loop correction on the MOAO DM
  • 40 s of telescope time (10000 iterations)
  • No NGS , 6 LGS in a regular hexagon

Manal Chebbo AO4ELT3 30 May 2013

slide19

DASP

  • EAGLE E2E DASP-simulations

H-band Ensquared energy in 75mas over the field of view. 6 LGS at 7.3arcmin diameter

6 LGS, 7.3 arcminute diameter

Strehl Map

Manal Chebbo AO4ELT3 30 May 2013

actuators required

DASP

  • EAGLE E2E DASP-simulations
Actuators required
  • By making use of global M4 GLAO correction
    • Can reduce requirements for MOAO DMs
    • MOAO can be relaxed somewhat without dramatically affecting AO performance.
      • To ones that can be bought today!

Manal Chebbo AO4ELT3 30 May 2013

alignment tolerance

DASP

  • EAGLE E2E DASP-simulations
Alignment tolerance

Rotational tolerance

  • Steep fall with rotation
  • 0.2 degrees
    • ~1/8thsubap at edges
  • Lateral misalignment reduces performance
    • Up to 1/8th of a sub-aperture has small effect

Manal Chebbo AO4ELT3 30 May 2013

slide22

Conclusion:

  • Current Project is to produce a new validated rapid E2E simulation which combines the speed advantages of analytic codes with the ease performing engineering tolerance analysis, for example: Rotational and misalignment
  • Future Work:
  • Cross check the codes
  • New user interface for E2E-S code
  • Aim to produce a new form of systems engineering for ELT scale AO problems.

Manal Chebbo AO4ELT3 30 May 2013

slide23

Thank You

Manal Chebbo AO4ELT3 30 May 2013

23

comparison with other codes
Comparison with other codes

Manal Chebbo AO4ELT3 30 May 2013

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