FLAO#1 commissioning report

LBT-ADOPT

TECHNICAL REPORT

Doc.No : 485f032

Version : a

Date : 05/12/2011

INAF – Osservatorio Astrofisico di Arcetri

Largo E. Fermi, 5 - 50133 Firenze - ITALY http://www.arcetri.astro.it/adopt

FLAO#1 commissioning report

F. Quirós-Pacheco, R. Briguglio, E. Pinna, A. Puglisi,

A. Riccardi, and S. Esposito

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Date : 05/12/2011 LBT-ADOPT TECHNICAL REPORT

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Largo E. Fermi, 5 - 50133 Firenze - ITALY http://www.arcetri.astro.it/adopt/

ABSTRACT

This document presents the results of the commissioning campaign of the First Light Adaptive Optics system

(FLAO#1) installed on the right side of the LBT telescope, and using the InfraRed Test Camera (IRTC). The

commission took place in the period February 2010, October 2011 and has been divided in 11th

commissioning

runs. The total time spent in the commissioning is 158 of which 46 nights. The total deployed manpower is about

3.5 FTE. The amount of time and FTE are consistent with the estimate given in the original commissioning plan.

The two main results of the commissioning activity are (a) the verification that the system on sky performance

matches the expected performance, (b) the demonstration that the system can be operated in an automated way with

an acceptable reduction in performance.

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Modification Record

Version Date Authors Section/Paragraph

affected

Reason/Remarks

1 05/12/2011

F. Quirós-Pacheco,

R. Briguglio, E. Pinna,

A. Puglisi, A. Riccardi,

and S. Esposito.

All First release of the document

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Abbreviations, acronyms and symbols

Symbol Description

AGW Acquisition, Guiding and Wavefront sensing unit

AO Adaptive Optics

AOS Adaptive Optics Sub-system

ASM Adaptive Secondary Mirror

ATT Arcetri Test Tower

BCU Basic Computational Unit

CCD Charge Coupled Device

CL Closed Loop

DIMM Differential Image Motion Monitor

DL Diffraction Limited

DM Deformable mirror

FLAO First Light Adaptive Optics system

FoV Field of View

FW Filter Wheel

FWHM Full Width at Half Max

GUI Graphical User Interface

IM Interaction Matrix

IR InfraRed

IRTC InfraRed Test Camera

KL Karhunen-Loeve

LBT Large Binocular Telescope

LBT672a First Adaptive secondary unit of LBT telescope

LUT Look Up Table

MCS Mount Control System

OL Open Loop

PSD Power Spectral Density

PSF Point Spread Function

PtV Peak to Valley

RMS Root Mean Square

ROI Region Of Interest

RON Read Out Noise

RRH Retro-Reflector Holder

SNR Signal to Noise Ratio

SR Strehl ratio

SW Software

TCS Telescope Control Software

TCS-PSF Telescope Control Software – Point Spread Function module

TO Telescope Operator

TT Tip-Tilt

W On axis Wavefront sensing unit

WFS WaveFront Sensor

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Contents

1 Overview of the commissioning campaign 7

2 System alignment and calibration 8

2.1 ASM calibration with interferometer .................................................................................................................... 8

2.2 Mirror modes and control modes characterization................................................................................................ 9

2.2.1 Mirror modes measurements ....................................................................................................................... 9

2.2.2 Fitted KL modes characteristics ................................................................................................................ 12

2.3 Optical alignment ................................................................................................................................................ 13

2.3.1 W unit with instrument rotator axis ........................................................................................................... 13

2.3.2 FLAO with retro-reflector ......................................................................................................................... 15

2.3.3 Pupil registration ....................................................................................................................................... 16

2.3.4 Pupil mask acquisition .............................................................................................................................. 18

2.4 Measurement of system interaction matrices with retro-reflector ...................................................................... 18

2.4.1 Fast push-pull technique ............................................................................................................................ 19

2.4.2 Mode amplitude optimization ................................................................................................................... 19

2.4.3 Coping with telescope vibrations .............................................................................................................. 20

2.4.4 Implementation details .............................................................................................................................. 20

3 Seeing-limited mode: on-sky performance 22

3.1 Flattening command calibration ......................................................................................................................... 22

3.1.1 Flattening results ....................................................................................................................................... 22

3.1.2 Shape repeatability .................................................................................................................................... 23

3.1.3 Aging of flattening calibrations ................................................................................................................. 23

3.2 Astigmatism and elevation .................................................................................................................................. 25

3.3 Zernike mode application ................................................................................................................................... 25

3.4 PSFs seeing-limited verification ......................................................................................................................... 26

4 Estimation of observing conditions and performance metrics 27

4.1 Estimation of the guide star magnitude .............................................................................................................. 27

4.2 Estimation of the seeing value ............................................................................................................................ 27

4.2.1 Seeing estimation from the DIMM ........................................................................................................... 27

4.2.2 Seeing estimation from real-time AO data ................................................................................................ 28

4.2.3 Seeing estimation from turbulence PSF .................................................................................................... 31

4.3 Characterization of telescope vibrations ............................................................................................................. 32

4.3.1 Open-loop vibrations ................................................................................................................................. 32

4.3.2 Closed-loop (residual) vibrations .............................................................................................................. 33

4.4 Readout noise (RON) characterization ............................................................................................................... 37

4.5 Estimation of the Strehl Ratio ............................................................................................................................. 39

5 Adaptive-optics mode: on-sky performance 40

5.1 Closed-loop preparation: sequence of operations ............................................................................................... 40

5.1.1 Preset phase ............................................................................................................................................... 40

5.1.2 Acquire reference phase ............................................................................................................................ 41

5.1.3 Start phase: gain optimization procedure .................................................................................................. 42

5.2 Active settings .................................................................................................................................................... 43

5.2.1 Active pupil centering ............................................................................................................................... 43

5.2.2 Automatic CCD background correction .................................................................................................... 43

5.3 Day time performance verification ..................................................................................................................... 44

5.4 On-sky commissioning results ............................................................................................................................ 44

5.4.1 Performance at the bright end: high-contrast imaging .............................................................................. 46

5.4.2 Effect of residual vibrations ...................................................................................................................... 47

5.4.3 Performance at the faint end ...................................................................................................................... 48

5.5 Verification of FLAO operational requirements ................................................................................................. 49

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5.5.1 System offsets in closed loop .................................................................................................................... 49

5.5.2 System offset in open loop ........................................................................................................................ 49

5.5.3 Static modes offloading to TCS ................................................................................................................ 49

5.5.4 System operation at low and high elevations ............................................................................................ 50

6 Conclusions 51

Acknowledgments 51

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1 Overview of the commissioning campaign

The main goals of the commissioning campaign of the First Light Adaptive Optics (FLAO) system for the LBT

telescope were the following:

1) To measure the performance of the FLAO#1 in terms of SR versus reference star magnitudes verifying that

the system reaches its specifications [10].

2) To demonstrate the system operability provided by the FLAO#1 control SW and to verify that the system can

be operated in an automated way with an acceptable reduction in performance.

The total number of days in the commissioning activities was 158 of which 37 were dedicated to system installation

and functional checks. The installation of the first adaptive secondary mirror (LBT672a) and of the first W unit

(AGW#2) happened in February-March 2010. The total commissioning time is equivalent to 3.5 FTE. The original plan

[4] reported 123 days of commissioning including 36 clear nights. The estimated manpower was 3.5 FTE well matching

the length of the total activity on site. Additionally, the total clear nights were 25, about 2/3 of the total originally

foreseen. The on-sky commissioning campaign of FLAO#1 started in May 2010 after the system installation and first

system calibration at the telescope.

Table 1 summarizes the time spent on each run of the commissioning campaign. We report in Figure 1 a Gantt chart

from the original commissioning plan document as a reference. In summary, the two above mentioned goals have been

achieved, as detailed in the next sections, in a period of time consistent with the original plan [4].

Run # (day/night) Start date End date Days total Persons Person-days total

system tel. inst. & first test 09-Feb-10 17-Mar-10 37 7 259

1st daytime run 10-May-10 26-May-10 17 5 85

1st night time run 27-May-10 03-Jun-10 8 9 72

2nd daytime run 06-Jun-10 12-Jun-10 7 4 28

2nd night time run 19-Jun-10 25-Jun-10 7 7 49

3rd daytime run 18-Sep-10 28-Sep-10 11 7 77

4th run (day/night) 13-Oct-10 28-Oct-10 16 (7) 4 64

5th run (day/night) 14-Nov-10 28-Nov-10 15 (7) 5 75

6th run (day only) 12-jan-11 22-Jan-11 11 4 44

7th run (day/night) 01-Jun-11 21-Jun-11 21 (12) 4 84

8th run ( day/night) 08-Oct-11 15-Oct-11 8 (5) 3 24

Table 1. Number of days/nights in each run of the FLAO#1 commissioning campaign. The numbers in parenthesis

account for the night of observing in a mixed run.

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Figure 1 The Gantt chart of the commissioning activities for FLAO#1 taken for the original commissioning plan.

2 System alignment and calibration

2.1 ASM calibration with interferometer

The 4D interferometer was installed inside a thermally insulated box, mounted on the Bent Right Gregorian Back focal

station. The procedure for the optical alignment took approximately 2 hours to be completed: the first step required to

operate close to the interferometer focus, on the telescope platform, in order to align the beam with the RRH axis (see

Figure 2) and to align the reflected one. The alignment procedure implemented at Arcetri Test Tower (ATT) was easily

accomplished inside LBTO dome with basically no changes. The sequence of operations is the following:

1. Remove the interferometer lenses (collimated beam) and switch on the laser.

2. Move M3 to center the laser spot on the back of the RR barrel (see Figure 2, left).

3. Place a screen at the focal plane with a hole in the focal point and move M2 hexapod until the image of the

hole (relayed from the M2-shell+RR-optics) is on the hole (rough auto-collimation). This step is made by

eye. The hole has a diameter of about 1.5cm.

4. Mount the converging interferometer lens and look for the return beam. Move M2 to over impose the return

with the source spot.

5. Fine align with M2 hexapod using the interferometer and move M2 hexapod to compensate for alignment

coma with PSF GUI.

We collected two sets of hexapod positions for the optical alignment, corresponding to the runs held in June and

September 2010 (§ Table 2). Also, as the RRH was generally mounted at the beginning of the activity (morning) and

dismounted before the beginning of the night time, for both runs we collected a number of daily positions. The spread

defines the cube which the RRH is installed within, to be compared with the hexapod movement range over its 6

coordinates.

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2.2 Mirror modes and control modes characterization

We will describe in this section the on-site characterization of the mirror modes and the computation of the KL modes

used for AO control. The acquisition setup utilizes the 4D interferometer installed on the right-back bent-Gregorian

focal station of the LBT telescope (§ 2.1). Two measurement campaigns were done: the first one in May 2010 and the

second in September 2010 after the maintenance of the LBT672a unit was completed.

The set of mirror modes are in general arranged in a matrix form called Optical Interaction Matrix. This matrix is

crucial to calibrate the flattening command for seeing-limited operations (§ 3.1), and to fit the KL modes used as control

basis for adaptive-optics correction (§ 2.2.2).

2.2.1 Mirror modes measurements

We will briefly describe the procedure followed to measure the mirror modes. As a first step, the ASM disturbance

buffer is loaded with a sequence of mirror modes commands, in which each mode is applied p times, with positive and

negative amplitude, alternatively. As soon as a single mode has been commanded, a 4D frame is captured thanks to the

synchronizing signal sent by the SwitchBCU to the trigger port of the 4D interferometer.

A total of 641 mirror modes (672 actuators – 31 defective ones) were measured. The measurements sets acquired at

LBTO are summarized in Table 3. To achieve a good SNR at the telescope, the number p of measurements had to be

increased from p=3 (as in the ATT) to p=51 (see next sections for a discussion on noise). On the other hand, the

Hexapod positions and semi-dispersion recorded during June 2010

X (mm) Y (mm) Z (mm) Rx (") Ry (") W (")

1.386 3.405 3.746 -573.714 232.687 0

0.04 0.07 0.17 9.5 16.3 0

Hexapod positions and semi-dispersion recorded during September 2010

X (mm) Y (mm) Z (mm) Rx (") Ry (") W (")

0.665 3.128 3.557 -579.72 105.68 0

0.01 0.05 0.13 4.0 2.5 0

Table 2. Sets of hexapod positions for the optical alignment with the interferometer, corresponding to the runs held

in June and September 2010.

Figure 2. (Left) The target placed below the retro-reflector to speed up the alignment procedure. (Right)

View of the secondary mirror reflected by the tertiary.

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collection of such large datasets was very time demanding. For instance, the time required to collect the mirror modes

with p=3 is 15 minutes, whereas with p=51 takes approximately 6 hours. This is because each frame is processed at 1.2

Hz. So far, there are two cases requiring the 51 iterations sampling: when the first few modes (0 to 9) are collected to

build up the Optical Interaction Matrix and for the modal basis identification needed for the KL computation. Figure

3(Left) shows some examples of mirror modes measurements from the last acquired set.

Figure 3. Modes associated with the LBT672a unit. (Left) Example of mirror modes. (Right) Example of fitted KL

modes produced by the ASM.

2.2.1.1 Noise in mirror modes measurements

The major source of noise detected in the dome environment was due to telescope vibrations, affecting mainly TT with

amplitudes as large as hundreds of nm RMS. For comparison, during optical acceptance test at the ATT, we coped

mainly with convection, while the TT standard deviation was tens of nm.

To evaluate the contribution of vibrations in mirror modes measurements, we collected a large number of 4D frames

without modes being applied and processed them with the same algorithm used for reducing mirror modes

measurements. The number of frames to be averaged was changed within the range p=[3,51] in order to evaluate the

best working point of the system.

Figure 4 presents a summary of the noise analysis results. First of all, note that the TT residuals are the dominant

disturbance at the telescope site. An acceptable SNR is achieved by averaging at least 25 frames, for which the residual

WFE (after TT removal) is below 2 nm RMS. For comparison, using the same processing at the ATT resulted in a

residual WFE of 0.5 nm RMS.

The contribution of astigmatism has also being taken into account. We identified about 10 nm RMS of differential

astigmatism in images couples taken at 25 Hz. The astigmatism residuals are effectively compensated through frames

averaging, as discussed above. It is mostly critical in the sampling of high-order modes for which the commanded

modal amplitude is typically very low (as low as 20 nm RMS) because of both the large forces required and the high

Date # of datasets # of modes Measurements per

mode (p)

May 16/17 2 641 3

May 23 2 641 3

September 21 1 641 3

September 22 2 641 51 (0-9); 3 (10-640)

September 28 1 641 51

Table 3. Measurements sets of mirror modes acquired at LBTO.

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fringes density they produced. As a consequence, the astigmatism residual pattern reduces seriously the SNR of the

measurements of high-order modes. We should note that astigmatism variations were not detected during optical tests at

the ATT.

Finally, we should note that convection noise (i.e. slowly evolving turbulence) was not detected above the threshold

of 5 nm RMS in the dome. This disturbance source was actually stronger at the ATT (from 10 to 30 nm RMS of WFE

injected by convection).

2.2.1.2 Measurement repeatability

In the previous section we analyzed the noise sources injected by the dome environment affecting the measurement of

the mirror modes. In this section we will analyze the measurement uncertainty given by the reproducibility of the same

mirror command, when it is executed several times.

The strategy for this test is as follows:

1. We select two mirror modes measurement sets, sampled with the same configuration (3 acquisitions/mode)

a few minutes apart;

2. Each mode measurement is normalized to the commanded modal amplitude;

3. For any mode, the difference between corresponding images of both sets is calculated;

4. Low-order Zernikes (alignment aberrations, astigmatism and trefoil) are calculated and then subtracted;

5. The RMS of the resulting differential pattern gives an estimate of the command non-repeatability.

The plot in Figure 5 shows the residual WFE after 1) removing only alignment aberrations (i.e. only TT removed),

and 2) TT, astigmatism and trefoil residuals have been removed. We will now address some points:

• Modes ranging from 100 to 300 show a larger dispersion of the repeatability error: this was verified on

several datasets, at different epochs, both at the ATT and at LBTO. We should advance that the same

behavior has been observed on unit LBT672b, during its optical acceptance test. Such effect is given by a

tiny modal oscillation (<1%) whose damping time is longer than 10 ms, so that it is sampled with a 25Hz

acquisition. This was observed also in the modal step response test.

• The contribution of astigmatism variations is similar for the whole dataset, and is comparable to the values

given in the previous section.

Figure 4. (Left) Residual WFE (nm RMS) after averaging N empty 4D frames (i.e. no modes applied) and

removing TT residuals (in black), and removing TT+astigmatism+trefoil residuals (in red). (Right) TT and

astigmatism residuals (nm RMS) versus the number of averaged frames N.

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• The astigmatism removal for mode numbers larger than 250-300 is very necessary to ensure an error on the

modal identification lower than 10 nm RMS (WF).

• Modes from #100 to #300 are the least affected by the astigmatism variations. The reason for this still need

to be understood. This effect was not observed at the ATT because of a very low astigmatism disturbance.

The repeatability of mirror modes measurements sampled with the 51 frames averaging was not possible, because a

single modal basis was collected.

2.2.2 Fitted KL modes characteristics

The FLAO control loop is based on a modal compensation approach using fitted KL modes. We have used the mirror

modes sets described in the previous sections to fit the theoretical KL modes defined on the LBT pupil. A detailed

description of the computation can be found in [11]. We have computed a total of 595 modes fitted by the working 641

actuators, although we have used a maximum of 500 of these in actual closed-loop operations.

It is important to emphasize that the quality of the KL fitting strongly depends on the quality of the set of mirror

modes used. In particular, we should mention that KL modes computed using mirror modes collected in May 2010 (see

Table 3) had to be subjected to additional post-processing in order to eliminate spurious cross-coupling effects due to

the poor SNR of the mirror modes measurements. This additional treatment was no longer necessary for the ultimate

KL modal basis computed from the last mirror modes set acquired in September 2010.

Figure 6 shows the cross-product matrix between the theoretical and the last set of fitted KL modes. Note that modes

higher than ≈ 300 present additional contributions of higher theoretical KLs. Some examples of KL modes are shown in

Figure 3(Right).

Figure 5. Non-repeatability analysis: residual WFE (in percent of the applied amplitude) between two mirror

modes measurement sets after TT removal (black rhombs), and after TT, astigmatism and trefoil removal (red

rhombs).

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2.3 Optical alignment

2.3.1 W unit with instrument rotator axis

After the separate transportation to the LBTO of the W board and the AGW frame, the W unit had to be re-installed and

realigned on it. The strategy for this alignment is divided in 2 main steps:

1. align an auxiliary mirror to the AGW rotation axis

2. align the W board axis to the auxiliary mirror using auto-collimation

2.3.1.1 Auxiliary mirror installation and alignment

The mirror is hosted on a micrometric tip-tilt mount. This mount is screwed on an aluminum bar that we installed on the

AGW structure. The goal is to align the mirror so that its reflecting surface is normal to AGW rotation axis. We perform

a preliminary alignment shining a laser beam (installed on a tripod lying on the room floor) on the mirror. Then we

rotated the entire AGW frame on the cart bearings simulating the field de-rotation. The wobble of the reflected laser

beam identifies the misalignment in between the mirror surface and the AGW rotation axis. We minimized the wobble

acting in the tip-tilt mount reaching an accuracy of few arc-minutes. A more accurate alignment has been performed

then by A. Rakich using the laser tracker reaching an accuracy of 10” per axis.

2.3.1.2 W board alignment to the auxiliary mirror axis

Once the auxiliary mirror is properly aligned we need to mount the IRTC flange on the AGW frame in order to have the

IRTC dichroic in the working position (see Figure 7). To do that we dismounted the clocking columns from the AGW

cart and we installed the flange using the clean room crane. Of course the cart cannot hold in position the AGW frame

while the IRTC flange is installed, so we maintained in active position the crane attached to the rocket launcher

structure during all the time we had the IRTC flange attached to the AGW frame. Now we installed a laser source on the

W board. The laser is hosted in a L1 spare mount. The laser beam is shined toward the IRTC dichroic and then reflected

on the auxiliary mirror (see Figure 8). As last step we installed a webcam in the auxiliary unit in order to easily detect

the misalignment of the out-coming and incoming beam. At this point the setup represented in Figure 7 was ready. We

tilted the W board in order to achieve the auto-collimation conditions (see Figure 9) with a final accuracy of about 1

arcmin. This guarantees that the laser source reflected by the IRTC dichroic is parallel to the auxiliary mirror axis with

the same accuracy and so to the AGW rotation axis. Now the laboratory alignment phase is completed and the W unit

is ready to be installed at the bent Gregorian focal station.

Figure 6. Cross-product matrix between theoretical and fitted KL modes.

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Figure 7. Scheme of the optical setup for the auto-collimation procedure of the W board. This procedure allows aligning

the W unit to the AGW frame rotation axis.

Figure 8. (Left) The alignment setup. The auxiliary mirror is in foreground on its tip-tilt mount hosted on a dedicated

bar. On the W unit board, L1 is substituted with the alignment laser installed on a L1 spare mount. (Right) a detailed

view of the setup. In the IRTC window reflection we can see the laser shining through the telecentric lens and the beam

splitter cube. On the left side of the cube we installed a webcam in order to verify the superposition of the out-coming

and incoming spots on the laser mount.

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Figure 9. Two frames from the webcam installed for the auto-collimation procedure. The webcam is imaging the mount

where is hosted the laser source. (Left) The out-coming and incoming beams are separated by few millimeters showing

a residual error in the alignment. (Right) The tip-tilt of the W board is corrected and the two beams are superposed.

2.3.2 FLAO with retro-reflector

2.3.2.1 Main alignment

The first step in the alignment of the FLAO system with its calibration unit, i.e. the Retro-Reflector (RR), is to allow the

light propagation through the full optical train. The calibration light source is an optical system providing an F/14.4

light beam, usually fed by a white light lamp. During this first phase, we temporarily installed a He-Ne laser source in

the AGW frame feeding the internal laser source in order to have more light intensity. This allowed us to identify by

eye the light spot at the different foci of the optical system. The beam generated by the calibration light source is

reflected by a beam splitter cube towards the IRTC dichroic and then to the ASM.

The first critical point was the alignment of M2 and M3 in order to feed the RR that has an entrance hole of about 2mm

only. Verified that, in the present configuration, no light was propagated back to the W-unit; part of the team went to

the 9th floor of the telescope building with a camera, a tripod and a tele lens of 300mm. With few seconds of open

shutter the laser spot reimaged by the ASM was visible on the RR mechanical mount in the picture taken with the

camera. Using the available tip-tilt range of the hexapod we succeed in feeding the RR entrance hole with the laser

light. At this point, the light was back propagated to the bent Gregorian focal station and we visually identified the spot

in the AGW frame. We changed back the laser source with the white light lamp and we were able to find the spot on

the IRTC wide field.

2.3.2.2 Fine alignment

The focal plane image on the IRTC presented an evident coma that we mostly corrected moving the hexapod using a

combination of translation and tilt (is a manual “movement on a sphere” that requires a 1” of tilt for 10µm of translation

in the opposite axis). Moving the W-unit stages we found the spot reflected by the IRTC dichroic on the WFS and we

had sufficient light on the pupil images in order to acquire a first interaction matrix and close a low order adaptive

optics loop (10 modes) in order to improve the optical quality of the spot. Thanks to the closed loop, we acquired a new

and better flat position for the ASM that allowed us to have light all over the pupil images. The PWFS had to be

operated with high modulation amplitude (tens of λ/D) in order to avoid signal saturation under these operating

conditions. Finally, another interaction matrix with higher modes (up to 200) was acquired, and a new and improved flat

position for the ASM could be calibrated after closing the loop.

2.3.2.3 Pupil wobble minimization

We performed a first estimation of the pupil wobble during field de-rotation measuring the image positions on the

CCD39 of the 4 LEDs that are located on the external border of the ASM. Having now improved the correction of the

wavefront, we were able to have a reliable and accurate (0.1pix) estimation of the real pupil image positions on the

CCD39. These are the conditions required by the fine alignment of the system. The most demanding requirement on the

alignment is the residual pupil wobble during the field de-rotation. Due to the residual misalignment between the W-

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unit optical, the instrument rotator, and the incoming light optical axis, the field de-rotation introduces a wobble of the

pupil images. This wobble can be corrected using the camera lens translator, so the wobble amplitude has to be within

the translator range that is about 4 pixels peak to valley for each pupil plane axis. We measured the pupil jitter during a

full de-rotator revolution keeping active the pupil re-rotator implemented on the W unit. The residual misalignment of

the pupil re-rotator with respect to the board axis plays a relevant role in the pupil wobble, so we have that the wobble

depends on the chosen clocking between the instrument de-rotator and the pupil re-rotator. This is because a different

clocking combines differently the residual misalignments of the involved optical axes. Due to the ASM actuator

symmetry at 120°, combined with the 90° geometry of the WFS subapertures, there are 6 equivalent angles for each

desired actuators/subapertures arrangement. We measured the pupil wobble for all the 6 positions and we chose the one

that minimized the pupil displacement.

As stated before, the clocking optimization depends on the desired arrangements between actuator-subapertures so,

in principle, a different optimized clocking exists for each different CCD39 binning. The numerical simulation

demonstrated that the optimal angle for binning 1x1, 3x3 and 4x4 is the same, only binning 2x2 requires a different

clocking position. So we repeated the six measurements using binning 2x2 and we chose again the one minimizing the

pupil wobble. Once we identified the optimal clocking, we verified at all 4 binning modes that the residual pupil

wobbles was in the camera lens translator range. That means that the performed system alignment was meeting all the

specifications. If the pupil wobble for one or more binning was found out of the specifications, the optical alignment

would have required some adjustment such as the optimization of the W board tip an tilt with respect to its stages.

Figure 10. The best arrangement of actuators/subapertures in the case of binning 1×1. The cross identifies the center of

a sub-aperture while the circles represents the ASM actuator positions. The green circles correspond to the actuators

that have a good sampling (Fried geometry) on the WFS, while the red ones are those that have a bad sampling (about

0.5pixel of shift with respect to the Fried geometry).

2.3.3 Pupil registration

Once the pupil clocking has been optimized (§ 2.3.2.3), a fine registration of the actuator vs. sub-aperture grid is

required. This alignment consists in the fine rotation and translation of the pupil image with respect to the CCD WFS

pixel grid. As a prerequisite for this fine alignment, the pupil magnification had to be verified. Indeed, the actuator

pattern that will be applied for the pupil registration can only generate the expected (high contrast) signal pattern if the

pupil magnification is the correct one.

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2.3.3.1 Magnification

Before proceeding to the magnification adjustment, we verified that the center-to-center distance between the pupil

images was 36.0±0.1 pixels as obtained during the W internal alignment. After this check we proceeded to measure the

pupil magnification applying specific patterns to the ASM. These patterns are formed by pairs of actuators

pushed/pulled at the maximum stroke so that the corresponding signals can be easily identified on the WFS. Since the

physical distance between the actuators on the mirror is known, the magnification can be estimated by measuring the

distance in subapertures between the corresponding signal patterns. Averaging the measurements on 4 different actuator

pairs, the magnification resulted in the desired one (911mm imaged on 30x24µm=720µm gives a magnification of 7.9

10-4

) at the level of 2% of error.

2.3.3.2 Rotation

Another specified ASM pattern is dedicated to the rotation detection. Two radial rows of actuators (see Figure 11 on the

left) have been pushed one against the other in order to identify three rows of sub-apertures with opposite signal sign.

The three actuator rows will produce three uniform signal rows when the rotation of the actuators pattern is the correct

with respect to the sub-aperture grid. This rotation is easily adjusted using the pupil re-rotator and maximizing the

signal contrast and uniformity along the sub-apertures rows.

2.3.3.3 Shift

The same pattern used for the rotation adjustment can be used for the vertical shift. A shift of the four pupil images on

the CCD39 frame can be easily applied using the camera lens translator. Shifting in the direction perpendicular to the

two rows, the signal contrast will vary from a maximum to zero. The maximization of the signal contrast corresponds to

the desired matching. The adjustment of the shift in the horizontal direction requires a new actuator pattern built using

the same actuators, but now grouped in pairs as represented in Figure 11(Right). Once again, the desired shift is reached

when the maximum of the contrast is found. When the best shift was identified, we iterated all the operations starting

from the rotation because, after the shift correction, the rotation had to be checked again. Once the desired matching

was reached, the position of the pupil centers was measured and recorded. This position was set as the reference for the

pupil position correction operated by the camera lens translator.

Figure 11. The same representation shown in Figure 10 with the identification of the actuators patterns used for the

pupil registration. (Left) The blue and red regions identify the actuator rows that have been used for the rotation and

vertical shift adjustments. These rows have been chosen because of their arrangement respect to the sub-aperture grid.

(Right) The blue and red regions identify the couple of actuators that have been used for the horizontal shift

adjustments.

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2.3.4 Pupil mask acquisition

After reaching the desired positioning of the pupil images on the CCD39 plane, we proceeded to the final acquisition of

the pupil maps, the ones that will be used for the system calibration required for on-sky operations. The pupil maps are

defined by the indexes of the CCD39 pixels associated with each subaperture (one pixel on each of the 4 pupil images

of the PWFS). The centers of the pupil images, and so of the masks, are determined by the operations previously

described and by the fact that the map inter-distance must be an integer number of pixels that at binning 1×1 is equal to

36. Moreover, because to each subaperture corresponds a pixel in each pupil image, the shape of the 4 maps is

necessarily the same. The map must include only the subapertures that receive a sufficient amount of light. The

subaperture selection is done with an algorithm that checks which subapertures are the most sensitive to wavefront

changes, out of an initial subaperture list which contains the illuminated pupils with an overestimated diameter, in order

to be sure of including all subapertures at the pupil border. The first step in the algorithm is to define a round sub-

aperture mask based on the current pupil centers. To do this, the output of the pupil measurement routine can be used to

define the mask, using the center information and increasing the diameter by about 3 pixels.

A stream of N frames and slopes is recorded. The number of frames N is typically at least 1000 in order to have a

significant average. For each subaperture, the following values are computed:

• Subaperture intensity (Intsa): Total intensity of the four pixels composing the subaperture, averaged over the

integration time.

• Subaperture signal standard deviation (σSx, σSy): standard deviation of the two slopes (separately X and Y) over

the integration time.

• Merit function: max{σSx / Intsa2 ; σSy / Intsa

2}

Once the merit function has been calculated for each subaperture, a threshold is applied and only the sub-apertures

with a merit value lower than the threshold are selected. Typically, this is done interactively with a procedure that

displays the resulting pupil shape and number of selected subapertures.

At the end of the procedure we recorded the final pupil mask. The pupil mask acquisition procedure is repeated for

each binning value. After this operation, the W-unit was ready for the system’s interaction matrix acquisition.

2.4 Measurement of system interaction matrices with retro-reflector

The interaction matrix (IM) between the pyramid WFS and the ASM was acquired for each different system

configuration (i.e. combination of each binning mode and TT modulation radius) listed in Table 4. KL modes are

applied one at a time using the fast push-pull technique and the corresponding WFS signals are acquired and then

processed to obtain the desired modal interaction matrix. The modal reconstruction matrix required to close the AO

loop is simply computed as the generalized inverse of the IM. In order to calibrate an IM at the LBT telescope with an

adequate SNR some improvements to the IM acquisition procedure were implemented and will be discussed below. A

diffraction-limited illumination source has been used for all IM calibrations.

Ref. star

mag (R)

Bin

Mode

Sampling

[#subaps]

Num. of valid

subaps.

Max num. of

modes

Pyr. Modulation

[±λλλλ/D]

<10 1 30×30 678 400 (500) 3 (2)

10-14 2 15×15 177 153 3

14-15 3 10×10 72 66 6

>15 4 7×7 48 36 6

Table 4. Summary of the different configurations used under different observing conditions, each one requiring the

calibration of a particular interaction matrix.

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2.4.1 Fast push-pull technique

A typical push-pull sequence is shown in Figure 12. Each KL mode is applied first with a positive amplitude (+A) and

after a few loop iterations with a negative one (-A). The first WFS measurement of each application is usually discarded

to allow for the mirror settling time. The remaining WFS measurements are averaged and combined to produce the jth

column of the interaction matrix containing the WFS signal vector S(·) associated with the jth

KL mode )( jm as:

(1) A

AmSAmSjIM

jj

2

)()()(

−−+=

In order to calibrate an IM with a good SNR, the amplitude A applied to each KL mode needs to be optimized

(§2.4.2). Also, the time elapsed between positive and negative applications should be kept as short as possible in order

to freeze and subtract the local turbulence present inside the dome. For this reason, a typical IM acquisition is

performed at loop frequencies of 400Hz or more (maximum frequency limited by the flux coming from the calibration

source). The whole sequence actuating all the modes is usually repeated several times (4+) in order to further improve

the SNR of the IM measurement.

Figure 12. Example of a typical push-pull sequence applied during the calibration of an interaction matrix.

2.4.2 Mode amplitude optimization

The amplitude (A) applied to each mode during the IM measurement must be fine-tuned not only to provide a good

SNR, but also to calibrate the WFS response in the small wavefront aberration regime, about the zero point. A general

target of 0.2-0.3 (in signal units RMS) has been used as a criterion. The final amplitude vector is computed iteratively:

1. Measure an IM using an initial amplitude vector (A inversely proportional to the radial order of the mode).

2. Measure the signal RMS for each mode, and multiply each element of the amplitude vector by the quantity

RMStarget / RMSmeasured

3. Repeat from step 1), until RMSmeasured becomes equal to RMSmeasured (within a threshold). This computation

usually requires a couple of iterations due to the non-linearity of the pyramid WFS.

An additional upper limit to the amplitude (A) comes from the ASM maximum force restrictions (<0.6N) translating

into a maximum amplitude of a few nanometers for high-order modes (300+). This often limits the calibration

amplitudes to values lower than the ideal ones for these modes. An example of an optimized amplitude vector for the

calibration of an IM with binning mode #1, and a modulation of ±3λ/D is shown in Figure 13.

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Figure 13. Set of optimized modal amplitudes for the calibration of an IM (binning mode #1, ±3λ/D).

2.4.3 Coping with telescope vibrations

The presence of telescope vibrations during the IM acquisition had several undesirable effects. In particular, spurious

low-order modes (mainly TT) produced by these vibrations were mixed up with all the modes being calibrated. We

found that the fast push-pull technique by itself could not remove all the spurious residuals; hence two additional

improvements were put in practice, as described below.

Off-line tip/tilt removal. This is a post-processing technique applied to the acquired WFS signals. A small two-

modes reconstructor is computed using only the TT modes of the acquired IM. This reconstructor is used to estimate

and remove TT signals from all the other modes. It is important to note that sometimes the TT vibrations may lead to

the saturation of the WFS signals for a given mode. In this case, it is not possible to properly recover the slopes for that

particular mode with this technique.

IM calibration in CL mode. The IM can be acquired while the system is in closed loop, using in general a very low

gain (<0.1). Of course, a reconstructor needs to be available, which is not the case when measuring the IM for the first

time in a given optical configuration. Thus a bootstrap sequence was followed:

1. Measure an IM with only the first few KL modes (~10) in open loop, averaging as many push-pulls as

possible for each mode. Thanks to the fast IM acquisition implementation (§ 2.4.4), about 100

measurements for each mode can be averaged in a few minutes.

2. Use the reconstructor obtained in step 1) to keep the loop closed while measuring the full IM. Telescope

vibrations will be compensated for by the closed loop, leaving only small TT residuals that can be removed

off-line from the WFS signals, as described above.

Calibrating an IM in CL mode requires less averaging and the full IM can be done in a manageable time.

2.4.4 Implementation details

The implementation of the fast push-pull technique makes use of the disturbance injection feature of the ASM. This

disturbance is a user-defined command vector that is summed to the output of the AO reconstructor. The disturbance is

loaded into an internal circular buffer capable of holding a history of 4000 command vectors. For the purpose of IM

calibrations, the disturbance contains the sequence of push-pull commands (Figure 12). In order to have the disturbance

feature on, the AO system needs to be kept in CL mode either with the controller gain set to zero, or set to a small value

for a true closed-loop IM calibration (§ 2.4.3).

The WFS signals are generated too fast to be downloaded in real-time. Instead, they are saved into a buffer on the

ASM onboard memory, and downloaded at the end of the IM acquisition. This buffer is capable of holding up to 20000

vectors of WFS signals. Allowing for some overhead when starting and stopping the IM measurement, the 4000-long

disturbance can be repeated four times before the slopes buffer is full. A full IM (600+ modes) can be acquired in a few

minutes. Communication overhead makes up for 50% of this time.

Finally, WFS signals processing (i.e. averaging, normalization, and TT removal) is performed offline to compute the

columns of the IM as stated in eq. (1).

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Figure 14. Example of WFS signals acquired for the calibration of the corresponding interaction matrices.

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3 Seeing-limited mode: on-sky performance

In seeing limited mode the adaptive M2 mirror should behave like a standard rigid mirror. This configuration is

obtained by setting the shell with the required pre-calibrated flattening position command (§ 3.1) and keeping it against

the gravity direction variation and wind disturbance. The internal metrology is used to keep this command effectively

applied relying on the pseudo-integrator of the actuator control forces for rejecting the quasi-static error given by

gravity and wind pressure variation (0-5Hz bandwidth, see pseudo-integrator in [14]). The command is kept by the

internal metrology with respect to the reference body. In order to account for gravitational flexure of the reference body

itself, a LUT versus elevation for low order Zernike modes is applied as an additive term to the position command and

refreshed every 20 seconds. The LUT is currently used to apply astigmatism term (§ 3.2).

3.1 Flattening command calibration

3.1.1 Flattening results

Flattening commands have been calibrated with the 4D interferometer in May, July and in September, providing a

starting point for the operations with the WFS unit. During the other commissioning runs (October, November and

January), additional flattening commands were no longer required, since the mirror optical figure was, at the beginning

of the activities, within the capturing range of the pyramid sensor.

The flattening procedure is exhaustively described in the LBT672a Optical Acceptance Test report [2]; here we will

just remember that, once the mirror modes have been collected (§ 2.2.1), they provide an Optical Interaction Matrix for

the mirror, whose pseudo-inverse is a projection operator from the space of optical shapes to that of the mirror modes.

Therefore, a given optical shape S might be decomposed as a linear combination f of mirror modes: the flattening

command for S is –f.

The main source of noise in the procedure is the change of S throughout the process. This is mainly due to thermal

drifts and oscillations, occurring at a time scales of approximately 100s, which is the duration of the procedure (i.e. the

time elapsed between the capturing of the shape S and the application of the command -f). Indeed, the resulting thermal

bend excites low amplitude (tens of nanometers) power and trefoil deformations φ, so that the final command -f will be

systematically slightly out of target. Such effect was observed and described also during optical tests inside the Test

Tower, both for unit LBT672a and LBT672b.

In Figure 15 four interferograms are shown, taken during July and September runs. The typical mirror figure error

after the flattening procedure ranges from 30 to 50 nm RMS (WFE) within both runs. These values of the flattening

results are very comparable with those calibrated in ATT during the optical acceptance test. A tiny contribution is given

by astigmatism and trefoil residuals, as low as 3 to 5 nm RMS.

Figure 15. Samples of the mirror WFE after the flattening procedure. (Left) Commissioning run June 2010. (Right)

Commissioning run September 2010.

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3.1.2 Shape repeatability

The calibration of a flattening command is obtained through the optical feedback provided by the interferometer. We

investigated the mirror figure error when the flattened shape is blindly applied later on, i.e. without any optical

feedback. This operation is the standard routine executed by the AO Supervisor software when the ASM is asked to set

to its working position, starting from the “rest” status, i.e. shell attached to the reference body.

In Figure 16 the result of this test is shown: the dots indicate the mirror WFE at the end of the procedure, after

removing the alignment aberrations (black dots) and also removing astigmatism and trefoil (red dots). The remarkable

point here is the spread of the datasets, rather than its mean value, that is approximately 3x larger than the best

flattening result: this is due to the procedure in itself, that cuts the modal command above a given mode threshold, in

order to reduce the required maximum forces, and preserve the forces budget for AO operations. The standard deviation

of both series is, respectively, 19 nm and 2 nm: such values define the repeatability level of the WFE when a given

shape (previously calibrated as optically flat) is loaded.

Figure 16. WFE of the ASM after applying a flattened shape previously calibrated. The same shape is loaded 9 times, in

a time lag of 20 minutes. (Black dots) alignment aberrations are removed. (Red dots) astigmatism and trefoil are

removed.

3.1.3 Aging of flattening calibrations

Within the scope of the seeing-limited operations performances, we evaluated the “aging” effect of the system

calibrations. A general degradation of the optical figure is indeed expected when a flattened shape is loaded far from the

calibration time. In the previous section we analyzed the system repeatability in applying the same shape several times

at the same epoch; now, we will investigate the system repeatability in a much wider time scale and on a larger data

sample. As the reference for the calibrations comparison we have taken the optical flat calibrated with the WFS.

Two different approaches have been explored:

1) The comparison between the last loaded shape and the next flattened one, and

2) The comparison between any flattened shape with respect to the mean of the whole sample.

3.1.3.1 Comparison between loaded shape and subsequent flattened ones

The strategy for this analysis is as follows:

1. Collect a number of flattening commands, calibrated with the WFS unit in close loop. These data consist in

actuators positions corresponding to the optical flat.

2. Collect the actuators position before the flattening procedure with the WFS: such shape is saved automatically

when the mirror is set to its working status.

3. For any pair of starting shape-flattened shape, compute the difference ∆S and remove alignment aberrations

and astigmatism plus trefoil.

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4. The starting shape is the mirror shape that would have been used for seeing-limited observations, hence the

RMS of ∆S virtually estimates the deviation from the optical flat for that observing run.

The result is shown in the cumulative curves in Figure 17: the 50% of the collected shapes depart from the optical

flat by less than 100 nm RMS (WFE); while, removing astigmatism and trefoils, the same count rises to 98%. The

specification for this value (from optical acceptance test plan and specification [12]) is 200 nm RMS WFE.

The robustness of this analysis is however limited by a statistical bias induced by the procedure in itself. During a

calibration run, flattening commands are frequently acquired and set as default shape for the system: hence, the shape

loaded at the system start-up is typically, during a calibration run, a recently calibrated one, so that the difference with

respect to an optical flat is generally small.

Figure 17. Cumulative plot of the WFE difference between the mirror shape before and after the flattening procedure

with the WFS.

3.1.3.2 Result of shape comparison with respect to the mean flattened shape

A different approach, that takes into account just the actuators positions corresponding to the optical flat, is as follows:

1. Collect a number of optical flats, calibrated with the WFS unit in closed loop.

2. Compute their mean value P0.

3. Compute for all of them, the deviation from the mean value P0. Any of the resulting vectors indicate the error

of the capacitive sensor calibrations, provided that P0 is a robust indicator of the system position at the optical

flat.

4. For any ∆P calculate the surface RMS, after removing alignment aberration and additionally astigmatism and

trefoil.

The result is shown in Figure 18, where black and red dots indicate respectively ∆P RMS after removing alignment

aberrations and astigmatism plus trefoil. Data are plotted as a time history to verify whether a “seasonal” trend was

noticeable (not observed). The three points groups are representative for the three calibration runs (September, October,

November): data are very similar comparing the three epochs, both in mean values and dispersion, both when

astigmatism is removed and when is not. The contribution of astigmatism is compatible with the hysteresis value at 90°

elevation after an elevation slew (hysteresis has been measured within the range 200-500 nm RMS surface).

The compensation for astigmatism gives a final RMS as low as 60-70 nm (surface) on average, in strong correlation

with the result of the previous paragraph.

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Figure 18. Difference between a set of mirror shapes (corresponding to the optical flat, calibrated with the WFS) and the

set average. A span of 60 days since the system installation is plotted, covering 3 commissioning runs (September,

October, and November). Data are in surface error (m RMS).

3.2 Astigmatism and elevation

Night-time and daytime observations showed the introduction of astigmatic deformation by the adaptive secondary

mirror when elevation is changed from 90deg. This was confirmed with measurements taken with the interferometer,

the FLAO WFS and active optics WFS.

A preliminary LUT was calibrated contemporary with the first on sky, seeing limited observations (March 2010),

with the goal of compensating for this effect.

The astigmatism deformation was characterized during the daytime with the retro-reflecting optics on, feeding the

FLAO WFS (W) unit. The mirror is kept optically flat as long as the optical loop is closed with W during the slewing,

while the tip-tilt and focus in the gap between shell and reference body are continuously compensated by the hexapod.

Because the mirror is kept flat by the optical feedback, the possible deformation of reference body with respect to

elevation is seen as gap variation in the capacitive sensor and read by the telemetry. The contribution of astigmatism

due to off-axis aberrations was simulated with Zeemax and it is estimated to be negligible.

Two sets of measurements have been collected: the first on 23 Oct 2010 between 90deg and 26deg elevation, the

latter on 19 Jan 2011 between 90deg and 30deg elevation.

The WFE of astigmatism variation is about 10µm RMS (~50µm PtV WFE) changing the elevation between 90deg

and 26deg. Also, the astigmatism shows an evident hysteresis loop with a maximum width of 4-5µm WFE RMS

between the back and forth paths in the same range of elevation. Because of hysteresis loop, a single-valued LUT of

astigmatism versus elevation can reduce the astigmatism error from 10µm to no less than 2-2.5µm WFE RMS (i.e. half

the loop width) and is therefore partially effective.

In addition, a day-by-day reproducibility error of about 1µm WFE RMS astigmatism at zenith is also visible, to be

added to the LUT residual.

3.3 Zernike mode application

The adaptive mirror is able to apply a linear combination of first 22 Zernike modes. The Zernike modes follow the

definition stated for the PSF subsystem of the TCS. For safety reasons the Zernike piston term (first mode) is always

forced to zero.

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Figure 19. Red and black plots represent two samplings of Z6 astigmatism versus elevation. The green line represents

the fitting of the Z6 astigmatism with a 2nd order polynomial to be used for the LUT. A maximum astigmatism

deviation from the LUT of the hysteresis loop is about 2.5um WFE RMS.

The set of commands defining the Zernike optical shapes have been calibrated using the same process that is used

for defining KL modes and described in Sec. 2.2.2.

The Zernike modes can be applied to the mirror using the “Zernike Application” fields in the “Shape Control” tab of

the AdsSec Control GUI (limited from Z2 to Z9) or through the SetZernikes command of AOS (see Sec.14.14 in [6]).

The same Zernike definition of commands is used to define the offloading to be requested to TCS of accumulated

low-order terms in the gap between the last flattening command and the shell position read from capacitive sensors (see

sec. 5.5.3).

3.4 PSFs seeing-limited verification

The seeing limited performances have been directly verified looking for artifacts on the PSF shape taken from the

Guider, especially on the PSF wings. The performances have been estimated after telescope collimation.

The night of 22 March 2010, which had a good seeing (0.5arcsec FWHM on the guider), has been selected to be

more sensitive to possible artifacts introduced by the mirror. The PSF image and the two orthogonal profiles are shown

in Figure 20, showing good PSF symmetry and no artifacts on the wings.

Figure 20 Seeing limited image on 22 march 2010. (Left) PSF taken with the guider. (Right) x and y PSF profiles.

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4 Estimation of observing conditions and performance metrics

The maximum performance that can be attained with an AO system is limited by several factors, the most important

being the total received flux from the GS, the atmospheric turbulence conditions (i.e. the seeing value, and the wind

speed), the separation between the object of interest and the GS, the read-out noise (RON) of the WFS detector, and the

telescope vibrations. We will present in this section the procedures followed to estimate the observing conditions. These

estimates are crucial to understand the limitations of the performance obtained in AO mode of operation (§ 5). The

performance will be in general evaluated in terms of the SR measured on the imaging camera. We will briefly outline in

Sec. 4.5 the algorithm followed to estimate this quantity.

4.1 Estimation of the guide star magnitude

The pyramid WFS is sensitive to a broadband encompassing R and I bands. On the lower bound, the passband is limited

by the dichroic installed on the filter wheel #1, which sends all the light above 600nm to the WFS. On the upper bound,

the quantum efficiency curve of the WFS detector a deep-depletion CCD39 limits the passband to ~950nm.

Therefore, the luminosity of the reference star in this band, 600−950nm, drives the AO correction capabilities.

For the purpose of comparing the performance of the FLAO system obtained with different reference stars, we will

use the concept of an “equivalent” star magnitude in R band computed as:

(2)

⋅⋅

⋅−= ph

ssys

R ne

chM

0

10log5.2λτ

where nph stands for the number of photons per squared-meter per second [ph m-2

s-1

]. This quantity can be easily

estimated from the acquired WFS CCD39 frames. The constants in Eq. (2) are: h, the Planck constant; c, the light

velocity; e0 = 1.76·10-8

W m-2

µm-1

, the zero-magnitude brightness in the Johnson R band; sλ = 750nm, WFS central

wavelength; and sysτ , the overall optical transmission (Telescope + WFS board + CCD39) in the spectral band

600−950nm, computed as in [10].

4.2 Estimation of the seeing value

The seeing value is defined as the angular size (FHWM) of the long-exposure PSF produced by Kolmogorov turbulence

(i.e. infinite outer scale). The seeing value can be computed as:

(3) )(

98.0)(0 λ

λλ

rs = ,

where r0(λ) is the Fried parameter at wavelength λ. By convention, the seeing value is always quoted at a wavelength of

λ=500nm. We counted on three methods to estimate the seeing value, each one of them with its own advantages and

limitations, as described below.

4.2.1 Seeing estimation from the DIMM

In order to have an independent estimate of the seeing value during a given observation, LBTO installed a Differential

Image Motion Monitor (DIMM) on top of the telescope mount. Unfortunately, the DIMM was not routinely available

during the FLAO commissioning due to the fact that it loses often the pointing thus requiring continuous re-

initializations by the Telescope Operator (TO). For this reason, DIMM measurements were available only on ~30% of

all datasets acquired in 2010.

In addition, logging in the LBTO telemetry stream of all pertinent DIMM data (time tag of measurement, exposure

time, and elevation angle of DIMM star) was not implemented until mid-2011. Hence, DIMM measurements could not

be corrected for air mass differences nor time-correlated with performance metrics with the required precision (roughly

one DIMM measurement available every 2-3 minutes). Although the error due to the air-mass difference may be

acceptable (<9%) for observations done at elevations higher than 70 degrees, the time tag uncertainty proved to be more

important for performance correlation analysis.

Figure 21 shows the histogram of all DIMM measurements available in 2010 for datasets acquired at elevations

>70°. The median seeing from this analysis results in 1.10 arcsec with an RMS of 0.34 arcsec.

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Figure 21. Histogram of DIMM seeing values for the whole 2010 commissioning campaign. A total of 195 datasets

(acquired at a telescope elevation > 70°) taken into account.

4.2.2 Seeing estimation from real-time AO data

This seeing estimation method is based on the reconstruction of OL modes (i.e. modal decomposition of the turbulence)

from applied mirror commands and residual WFS signals obtained in closed loop [8]. Then, the Fried parameter (r0) can

be estimated from the OL modal variance distribution. Once r0 is known, the seeing value can be retrieved from eq. (3).

4.2.2.1 Open-loop modal reconstruction

Assuming a two-frame delay in the loop due to the exposure and read-out times, the OL modal vector can be

reconstructed as:

(4) )2()()( −+= nnn correstur aaa ,

where )(ntura stands for the OL (turbulence) modal vector at iteration n; )(nresa stands for the residual modal vector, and

)(ncora stands for the modal correction vector applied by the DM. These modal vectors can be computed as:

(5) )()( nnres sRa =

(6) )()( †2 nn CMcor cPa =

where )(ns is the slopes vector, )(nc the position commands vector, R the modal reconstructor, and CM 2P the modes-to-

commands matrix.

AO real-time data cannot be downloaded at full speed. There is a variable decimation factor that depends on the

selected sampling frequency. Table 5 summarizes the way decimated data is combined in order to properly take into

account the two-frame delay between the residual and the correction modes [see eq. (4)].

The case when fs > 800Hz deserves further explanation. First of all, let us consider that the actual positions vector

(i.e. the positions actually reached by the actuators) at iteration n is )1()( −≈ nn cp . Multiplying both sides by the matrix

†2CMP leads to the following relationship: )1()( −≈ nn corpos aa . On the other hand, when one every three frames is saved (i.e.

decimation factor 2), it should be clear that )3()1( −=− np corcor aa , where p is the decimated data index. Therefore, the

vector )2( −ncora can be estimated as the linear interpolation between )3()1( −=− np corcor aa and )1()( −≈ np corpos aa .

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Decimation

factor

Notes Sampling

frequency range

Open-loop modal vector

( p ≡ decimated data index )

0 No decimation fs < 400Hz )2()()( −+= ppp correstur aaa

1 One frame saved every two 400 < fs < 800Hz )1()()( −+= ppp correstur aaa

2 One frame saved every three fs > 800Hz [ ])()1(5.0)()( pppp poscorrestur aaaa +−+=

Table 5. Reconstruction of open-loop modes from acquired AO real-time data.

4.2.2.2 Fitting r0 from OL modal variance distribution

The Fried parameter r0 can be estimated from the fitting of the time-variance distribution of the reconstructed OL

modes by the theoretical modal variance distribution. Let us consider the well-known Zernike decomposition of

turbulence in these computations. The theoretical Von-Karman variance of the jth

Zernike coefficient is given by [18]:

(7) ( )3/5

0

02 ,,

×=

r

DLmnfz jjj

where ( )0,, Lmnf jj is a scalar that depends on the outer scale L0, the radial order nj, and the azimuthal frequency mj of

the jth

Zernike, with L0 having an impact mostly on the variance of the first radial orders. In order to avoid the effect of

L0 (and also telescope vibrations), the first three radial orders were not considered in the fitting of r0. Also, to avoid the

effects of aliasing, we have neither considered the last two radial orders.

Figure 22 shows some fitting results for two particular cases. The experimental and the best-fit variance

distributions are shown as well as the corresponding r0 and seeing values obtained. Despite the good fitting achieved in

both cases, we should note that the seeing estimation for the case of binning #3 and 66 controlled modes is actually

under-estimated as discussed below.

Figure 22. Example of r0 fitting from reconstructed OL modes. (Crosses) Estimated OL modal variances; (Red

line) Theoretical modal variance distribution. (Left) Case of bin#1, 400 controlled modes. (Right) Case of bin#3,

66 controlled modes.

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4.2.2.3 Pyramid WFS sensitivity issues

We should bring some attention to the fact that for a pyramid WFS, )(nresa will be in general underestimated for the

following reasons. Recall that the pyramid sensitivity depends on the size of the PSF atop the pyramid vertex. All our

modal reconstructors were computed from modal interaction matrices calibrated with a diffraction-limited source. On

the other hand, in closed-loop conditions the size of the PSF on the pyramid will be in general wider; the actual size

depending on the seeing and on the level of AO correction attained at the WFS wavelengths. The mismatch between the

PSF size during calibration and closed-loop operation is responsible for the underestimation of the residual modal

vector )(nresa , which in general leads to an underestimation of the seeing value.

We are developing an improvement of this method in which the residual modal vector is iteratively estimated as

)()( nnres sΛRa = , where ΛΛΛΛ is a diagonal matrix containing a set of “modal sensitivity compensation coefficients”. A look-

up table for these compensation coefficients as a function of different seeing values and for each set of relevant system

configuration parameters (i.e. binning mode, number of controlled modes, etc.) could be calibrated for instance with the

aid of numerical simulations. The seeing value estimated at the first iteration with ΛΛΛΛ=Id can then be used as the entry

value for the look-up table, and refined iteratively until convergence is reached.

It is important to keep in mind that all seeing estimates from AO data presented in this document are subject to

underestimation. In particular, we have found from our data analysis that the estimation error is non-negligible for

datasets taken with star magnitudes MR >13.

4.2.2.4 Correlation with DIMM measurements

Figure 23 shows the correlation between the DIMM measurements and the seeing values estimated from AO real-time

data. First of all, note that there is a systematic underestimation of seeing values estimated from AO data, as expected,

when no pyramid sensitivity compensation is taken into account. Also, it becomes clear from this plot that the seeing

estimations from AO data are not reliable at all when the system is operating in binning mode #4.

A 2nd

-order polynomial fit to data is also show in the Figure 23 with coefficients [-0.45, 1.38, -0.30]. The fitting was

done taking into account only data with bin#1 and bin#2 (MR <13). As expected, the (AO-data) seeing underestimation

error becomes more important under strong turbulence conditions.

Figure 23. Correlation between seeing measurements from DIMM and seeing values estimated from AO real-time data.

All 280 datasets for which DIMM measurements were available are considered in this plot. Different binning modes are

distinguished with symbols. (Red dashed-line) 2nd

-order polynomial fit to data.

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4.2.3 Seeing estimation from turbulence PSF

An estimate of the seeing value could also be deduced from an OL long-exposure PSF acquired with the IRTC.

According to the von-Karman turbulence theory, The FWHM of the long-exposure turbulence PSF, )(λFWHM , is

related to the Fried parameter and the outer scale by [16]:

(8) 356.0

0

0 )(183.21)()(

−≈

L

rsFWHM

λλλ .

Figure 24 shows this relationship for different values of L0. For instance, note that a FWHM of 0.5 arcsec corresponds

to a seeing value of 0.75 or 0.95 if the outer scale value considered is 20 or 100m respectively. Besides the uncertainty

on the outer scale value, we should note that there is an additional PSF smearing caused by telescope vibrations that

adds to the FWHM estimation uncertainty.

Figure 25 shows an example of an OL PSF and its radial average used to estimate the FWHM. Note that the PSF is

more elongated in the vertical direction most likely due to presence of telescope vibrations.

Figure 24. Theoretical FWHM of the turbulence long-exposure PSF in H band versus the corresponding seeing value (at

500nm) for different values of the outer scale L0.

Figure 25. Seeing estimation example from an OL PSF (20100526_053329). (Left) OL PSF in H band. (Right) Radial

average used to estimate the FHWM. The estimated FWHM is 0.44 arcsec which corresponds to a seeing value of 0.74

arcsec assuming an outer scale of 50m.

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4.3 Characterization of telescope vibrations

Large telescopes suffer from structure vibrations that can reduce the AO performance. In the case of the LBT telescope,

the swing arm supporting the ASM has resonance frequencies from 15 to 30Hz [9]. Wind shaking and telescope

tracking can excite these resonances. Additional vibrations were identified during the commissioning runs coming from

the cooling fans in the “treehouses”, and the M1 cooling system. As we will show below, all of these vibrations affect

mainly the tip/tilt modes.

We have characterized the telescope vibrations in open- and closed-loop conditions. Open-loop vibrations will be

discussed in section 4.3.1, whereas the characterization of the closed-loop residual vibrations will be presented in

section 4.3.2. The vibrations characterization is based on the analysis of the temporal PSDs of the pertinent variables

(e.g. time series of modal coefficients) with a peak detection tool developed for this purpose.

4.3.1 Open-loop vibrations

Open-loop vibrations can be estimated from the power spectra of the OL modal vector [eq. (4)]. Indeed, this modal

vector gives an estimate of the disturbance signal comprising both the turbulence and the telescope vibrations. We have

identified the strongest TT vibration occurring at a frequency of 13.4±0.1Hz. As an example, Figure 26 shows the

spectra of the TT OL coefficients for a particular dataset. The TT vibration at ~13Hz is clearly seen.

We have characterized the power of this TT vibration based on the analysis of our reconstructed OL data. Once

again, no pyramid sensitivity compensation has been taken into account in the OL reconstruction [eq. (4)]. Therefore, in

order to minimize the impact of this effect, we have only selected datasets with a high-order level of correction for this

analysis (system parameters: bin#1, controlled modes ≥ 400, and fs ≥ 400Hz).

Figure 27 shows the power histogram of the 13.4±0.1Hz TT vibration. A total of 282 datasets were considered. Note

that this vibration occurred on 49% of the datasets analyzed. The median value of the vibration’s power in open-loop is

26.6 mas RMS. This particular vibration has been further studied using accelerometers data in order to correlate the

optical effects to their mechanical sources [1].

Figure 26. Example of OL spectra reconstructed from CL data (Dataset 20100531_042254). The strong

telescope vibration centered at ~13Hz is clearly seen.

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4.3.2 Closed-loop (residual) vibrations

When the FLAO system is operated in closed loop, telescope vibrations are partially compensated for; the degree of

compensation depending on the characteristics of the Rejection Transfer Function (RTF) at the vibration frequencies in

question. In this section we will present the characterization of the residual vibrations when the FLAO system is

operated in the high-flux regime. As we will discuss below, this analysis could not be performed in the low-flux regime.

First of all, taking advantage of the large number of controlled modes (typically 400) used in the high-flux regime,

we have performed a detailed analysis of the residual vibrations on all the modes (§ 4.3.2.1). As already mentioned

above, tip and tilt are the modes mainly affected by telescope vibrations. The power characterization of the residual TT

vibrations in the high-flux regime will be presented in Section 4.3.2.2. The analysis on how the SR loss is related to the

power on the TT vibrations will be presented in section 5.4.2.

4.3.2.1 Characterization of residual vibrations in all the controlled modes

We have identified the principal vibrations from the analysis of the power spectra of the residual modal vector [eq. (5)].

The frequency fvib, the bandwidth ∆fvib, and the power Pvib of the vibrations have been characterized for all the modes.

Clearly, these powers would represent the residuals of the vibrations after AO correction. It is important to keep in mind

that, since in general modal residuals are underestimated, the power on the vibrations will be also under-estimated.

However, in the particular case of TT modes, it is possible to characterize more accurately the residual power of the

vibrations from the analysis of the centroid power spectra of the PSF images acquired with the IRTC (§ 4.3.2.2). As an

example, Figure 28 shows the residual vibrations identified on tip and focus for a particular dataset.

For the purpose of characterizing the vibrations affecting each one of the controlled modes, we have selected a total

of 296 datasets with the following system parameters: bin#1, controlled modes ≥ 400, and fs ≥ 800Hz, corresponding to

MR < 10.5 and SRH > 0.1 under various seeing conditions. We have computed a vibration frequency histogram for each

mode (using a bin size of 0.25Hz). Only vibrations with a relative power of Pvib,rel > 5% (relative to the total residual

power on the corresponding mode) have been taken into account in the histograms. As an example, Figure 29 presents

the frequency histograms of the vibrations affecting TT modes. The percentage of occurrences is computed with respect

to the total of 296 selected datasets.

Figure 27. Power histogram (mas rms) of the 13.4±0.1Hz vibration present on TT modes estimated from the

OL modal vector. The percentage of occurrences is computed with respect to the total of 282 selected datasets.

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Figure 30 presents a summary of the vibration analysis for all the modes. Note that vibrations with frequencies

higher than 10Hz affect only the first 5 modes: TT (modes#0 and #1), focus (mode#3), and astigmatisms (modes#2 and

#4). However, as shown in Figure 30(right), only vibrations on TT modes exhibit larger amplitudes. Note that modes 3

to ~60 also exhibit low-frequency vibrations (<10Hz), but their occurrences and amplitudes are relatively low.

Vibrations on modes higher than ~60 may exist but with occurrences of less than 10%, so they are not shown in Figure

30. In conclusion, residual telescope vibrations have an impact mainly on TT modes.

Figure 29. Vibration frequency histogram for tip and tilt modes. Only vibrations with a relative power of Pvib,rel

> 5% have been taken into account. The percentage of occurrences is computed with respect to the total of 296

selected datasets (bin#1, controlled modes ≥ 400, and fs ≥ 800Hz). The characteristics of the principal TT

vibrations are summarized in Table 6.

Figure 28. Vibrations characterization example. (Left) mode 0 - tip; (Right) mode 3 - focus. The vibration

frequencies, bandwidths and associated powers are identified from the analysis of the residual modal spectra.

Observing conditions: MR=7.7, s=0.82”. System parameters: bin#1, 400 modes, 1kHz, ±3λ/D; Performance:

SRH=53%.

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The characteristics of the principal vibrations on TT modes are summarized in Table 6. Note that the most important

vibration (both in terms of occurrence and relative power) is the one at 13.4Hz. This vibration is usually accompanied

by a sister vibration at 13.2Hz. In fact, our peak detection algorithm sometimes considers both close peaks as part of a

single wider vibration (e.g. see left plot of Figure 28).

Mode Median Frequency (Hz)

(fvib)

Bandwidth (Hz)

(∆∆∆∆fvib)

Median Relative Power (%)

(Pvib,rel)

Occurrence (%)

0

(tip)

13.2 0.25 12.1 24

13.4 0.33 31.1 74

14.4 0.25 7.4 36

15.6 0.25 7.8 27

22.8 0.17 9.1 44

29.8 0.17 7.1 13

1

(tilt)

13.2 0.25 11.1 15

13.4 0.33 26.9 72

14.4 0.25 13.9 56

15.6 0.33 10.0 29

24.6 0.17 9.2 21

29.8 0.17 10.3 35

Table 6. Characteristics of the main vibrations on TT modes. The power Pvib,rel is relative to the residual power on

the corresponding mode. The percentage of occurrences is computed with respect to the total of 296 selected

datasets (bin#1, controlled modes ≥ 400, and fs ≥ 800Hz).

Figure 30. Characterization of vibrations present in residual modes (Occurrence > 10%). (Left) Median

vibration frequencies. (Right) Median power on vibrations (nm wf rms). No pyramid sensitivity compensation

taken into account (i.e. power under-estimated). The percentage of occurrences is computed with respect to the

total of 296 selected datasets (bin#1, controlled modes ≥ 400, and fs ≥ 800Hz).

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4.3.2.2 Power of vibrations on TT modes

Let us center our attention in this section on the characterization of the vibrations’ residual power on TT modes. As it

was discussed above, this estimation is affected by the pyramid sensitivity issues when using the residual modes.

Alternatively, using the PSF images acquired with the IRTC, it is possible to estimate more accurately the residual

power from the analysis of the PSF centroid power spectra. On the other hand, this estimation can only be done when

the IRTC is operated at framerates 60 < fIRTC < 66 Hz (considering a maximum vibration frequency of 30Hz) in order to

prevent aliasing effects.

Figure 31 puts in evidence the underestimation problem in a particular dataset. The cumulated PSDs of TT modes in

arscsec RMS estimated from both the residual modes and the IRTC images are compared. The x- and y- axes are not

coincident since the IRTC orientation depends on the telescope’s rotator position. As expected, the frequencies of the

peaks coincide but the residual TT power RMS values are underestimated when using the residual modes (by a factor

~2 in this particular dataset).

As discussed in section 4.2.2.3, the pyramid sensitivity depends on the size of the PSF atop the pyramid vertex,

which depends on the level of AO correction attained at the WFS wavelengths. When the AO correction is done with

similar system parameters (in our present study: binning mode #1, controlled modes ≥ 400 modes, and fs ≥ 800Hz) the

pyramid sensitivity (and therefore the power underestimation) changes with the seeing. Figure 32 shows how the TT

power underestimation for the vibration at 13.4Hz varies with the seeing value. Note that, as expected, the

underestimation is higher for worse seeing values. To avoid the sensitivity-dependent power estimation from residual

modes, we will characterize below the power on vibrations using the IRTC data.

Figure 33 presents the power histogram (mas RMS) of some of the principal TT vibrations. We have restricted our

sample to those datasets where fIRTC ≥ 60 Hz in order to characterize the TT vibrations up to fvib = 30Hz. Hence, a total

of 183 datasets were taken into account (system parameters: bin#1, ≥400 modes, fs ≥ 990Hz) corresponding to MR < 9.6

and SRH > 0.12 under various seeing conditions. Note that the strongest vibration (fvib = 13.4Hz) has a median RMS

value of 6.3 mas RMS. The median RMS values for the other vibrations are also indicated in Figure 33.

Figure 31. Comparison of residual TT cumulated PSDs: (Left) estimated from TT residual modes; (Right)

estimated from PSF jitter. System configuration (dataset 20100622_032730): bin#1, 400 modes, fs = 1kHz,

±3λ/D; Observing conditions: MR=7.7, s=0.67”; Performance: SRH=65%; IRTC parameters: H-band filter,

10 mas/pixel, 5ms exposure time, fIRTC = 66Hz, 1000 frames.

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It is important to emphasize that the residual powers shown in Figure 33 were estimated under high-flux conditions

(MR < 9.6) and fast sampling rates (fs ≥ 990Hz). Hence, vibration frequencies lie well below the AO correction

bandwidth (usually ~0.1fs) leading to a higher vibration attenuation. For fainter reference stars slower sampling rates are

typically required. Hence, it is expected that the residual power on TT vibrations will increase. Unfortunately, we

cannot perform this analysis for these cases with the collected IRTC data due to the fact that IRTC sampling rates are

typically fIRTC << 30 Hz under these conditions.

4.4 Readout noise (RON) characterization

The RON value for each dataset was estimated from the acquired CCD39 frames. A ROI defined at the four corners of

the CCD frames with practically no diffracted light from the pupil images was selected for the RON estimation. Table 7

summarizes the median RON values measured during the commissioning nights for each typical readout speed used in

each binning mode. Figure 34 shows the histogram of the RON values for the particular cases of binning mode #1 and

#2.

The RON values assumed to compute the baseline and goal performances [10] are also listed in Table 7 for

comparison. Note that actual median RON values measured at the telescope for binning mode #1 and the “fast” binning

mode #2 are better than the goal one. On the other hand, for the “slow” binning mode #2 and for binning modes #3 and

#4, the actual median RON values are between goal and baseline ones.

Regarding binning mode #2, we must say that only the 800 kpixel/s readout speed was automatically set with this

binning mode, giving a median RON value of 6.4 e- RMS in all datasets. A more sophisticated look-up table is

envisaged for the FLAO#2 system in which the readout speed can be switched to 380 kpixel/s when operating at

sampling frequencies fs<625Hz in order to take advantage of a lower median RON of 4.2 e- RMS.

Figure 32. Residual TT power rms on the vibration at 13.4Hz estimated from TT residual modes versus the

equivalent estimation using the PSF images. System parameters: bin#1, ≥400 modes, fs ≥ 800Hz, and fIRTC > 33 Hz.

A total of 228 datasets were considered in this analysis (corresponding to MR < 10.4 and SRH > 0.1).

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Binning mode Readout speed

(kpixel/s)

Max. freq

(Hz)

Median RON

(e- RMS)

Baseline/Goal RON

(e- RMS)

1 2500 1000 10.5 14.0 / 11.5

2 800 1000 6.4 8.5 / 7.0

2 380 625 4.2 5.1 / 4.0

3 380 1000 4.5 5.0 / 3.5

4 335 1000 4.6 5.0 / 3.5

Table 7. Median RON values of the WFS detector (CCD39) during the commissioning nights for each typical readout

speed used in each configuration. For comparison, baseline and goal RON values are also shown.

Figure 33. Power histogram (mas rms) on main residual vibrations present on TT modes estimated from PSF

images. System parameters: bin#1, ≥400 modes, fs ≥ 990Hz, and fIRTC ≥ 60Hz corresponding to MR < 9.6 and SRH >

0.12 under various seeing conditions. The percentage of occurrences is computed with respect to the total of 183

selected datasets.

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4.5 Estimation of the Strehl Ratio

The Strehl Ratio value reached by the AO corrected image is the main parameter we used to assess the system

performances during the commissioning. The SR is defined as the ratio between the PSFM (measured PSF) peak and the

one of the PSFDL (pure diffraction limited PSF): SR = PM/PDL. We will briefly describe here the procedure we used to

estimate this value from the image acquired on the camera. The procedure consists in two fundamental parts: generate

the PSFDL as reference, and evaluate the total star flux in PSFM.

As a first step, the monochromatic synthetic diffraction-limited image is generated as reference. This PSF is created

computing the Fourier transform of the pupil map. The map takes into account the telescope central obstruction and

neglects the footprint of the swing-arms. The PSF is produced taking into account the central working wavelength

(usually H band) and the measured PSFM sampling (usually 10mas/pix). In order to properly reproduce the sampling of

the PSFM, the synthetic one is initially generated with an oversampling of a factor 10 with respect to the one of the

PSFM. In order to correctly reproduce the real sampling, we need to have an estimation of the PSFM centering with sub-

pixel accuracy. This information is obtained fitting a Gaussian surface on PSFM. Now we can properly resample down

the synthetic PSF to reproduce the same sampling and sub-pixel centering obtained in the measured image. At this

point, we obtain the PSFDL.

The SR calculation is based on the comparison of the peaks of the PSFs, so we need to properly rescale the two

images: the PSFDL is generated with PDL = 1, while PM depends on the star flux collected during the camera integration.

This quantity is proportional to the sum of all the counts in the camera frame while all the other count sources (bias,

background, etc.) need to be properly subtracted. The camera image is sky subtracted, but the background subtraction is

so critical for the SR measurement that we implemented an automatic check of this value. If the background is properly

considered and removed, the star flux is proportional to the sum of all the counts on the camera frame. Because the light

of the star is spread by the turbulence up to a finite distance Ratm from the PSF center (depending on the seeing

condition this is of the order of 0.5” radius), the sum of the counts out of this region should be zero. The algorithm we

use considers the sum of the counts in squared sub-regions of the frame centered on the PSFM peak and of side l. So

TC(l) (total counts as function of l) is constant when l>2Ratm and it corresponds to our estimation of the total incoming

flux. If the background subtraction gives some residuals, TC(l>2Ratm) is no longer constant with l. Our procedure

evaluates the behavior of TC(l) and discards those PSF images where TC(l>2Ratm) does not converge.

After this sanity check, the procedure rescales the flux of PSFDL to TC(l>2Ratm) and simply computes the ratio

between the counts of the two PSF peaks to obtain the Strehl Ratio: SR = PM/PDL.

Figure 34. Histogram of RON values estimated from the CCD39 frames acquired during the 2010

commissioning nights. (Left) Binning mode #1 with a typical readout speed of 2500 kpixel/s. (Right) Binning

mode #2 with a typical readout speed of 800 kpixel/s. A total of 308 and 242 datasets were considered for this

analysis, respectively.

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5 Adaptive-optics mode: on-sky performance

We will present in this section the main results of the commissioning nights of the FLAO system operating in the AO

correction mode. We have evaluated the CL on-axis performance under various observing conditions (i.e. different star

magnitudes and atmospheric turbulence conditions).

The diagnostics and performance evaluation of the FLAO system were based on the analysis of the acquired

telemetric data comprising IR camera frames, WFS measurements and CCD frames, modal coefficients, actuator

commands, actual ASM positions, etc. From all the performance metrics, the most relevant to assess the quality of the

AO correction is the Strehl Ratio (SR) estimated from a given star image.

5.1 Closed-loop preparation: sequence of operations

The closed-loop preparation is divided in three distinct phases:

1. The Preset phase (PresetAO). The system is pre-configured based on the expected AO star magnitude and

position.

2. The Acquire Reference phase (AcqRefAO). The system acquires the AO star (possibly changing the

configuration based on the actual magnitude) and prepares the system for loop closure.

3. The Start phase (StartAO). The loop is closed and the controller modal gains optimized.

The division has been designed for both efficiency and flexibility: the first part (Preset) does not need any light from

the AO source and can be executed in parallel with other telescope setups and slew. The Acquire phase needs the

telescope tracking (but not guiding) on the target, and leaves the system ready for AO loop closure. Finally, the Start

phase closes the AO loop whenever the user asks for it.

5.1.1 Preset phase

The PresetAO command must be issued to the system before starting an AO observation. The Preset can be executed by

the AO system irrespectively of any other telescope operation, since it is a purely internal preparation.

From the Preset command, the AO system receives the following information:

• AO mode (full correction or tip-tilt only)

• Expected AO star magnitude

• Expected AO star position in the stages patrol field

The Preset only involves the WFS and does not make any changes to the current ASM configuration (which is

assumed to be flat from a previous TCS command). Upon receiving the command the WFS software scans the AO table

shown in Table 8 using the expected AO magnitude and starts to execute the following actions:

• The acquisition camera (CCD47 1024x1024) is configured with the binning and framerate specified in the AO

table.

• The CCD39 is configured with the binning specified in the AO table, and one third of the expected framerate

of the AO loop (with a minimum of 100 Hz). This is done to allow for a better magnitude estimation in low

flux conditions.

• Darks for both CCD39 and CCD47 cameras are acquired.

• Filter wheels #1 and #2 are moved to the optimal filters for source star acquisition. For instance, in the two

extreme settings:

o For bright stars, the flux on the acquisition camera needs to be limited to avoid saturation. Hence,

FW#1 is set to a dichroic 600-1000nm reflecting ~5% of the light towards the acquisition camera, and

FW#2 is set to a narrow band filter (CW800nm BW10nm).

o For faint stars, all light needs to be sent to the acquisition camera. Hence, FW#1 is set to a silvered

mirror transmitting all light to the CCD47, and FW#2 is set to an open position.

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• XYZ stages are moved to the expected AO star position, as specified by the command arguments.

• The pupil re-rotator starts tracking the telescope de-rotator.

When the CCDs are ready, all the movements are done, and the tracking loops are active, the PresetAO command is

completed.

MR CCD39

Binning

mode

CCD39

fs

(Hz)

photons

/ subap.

/ frame

nmod mod.

(±±±±λλλλwfs/D)

CCD47

Binning

mode

CCD47

fs

(Hz)

7.4 1 990 500 400 3.0 4 4.3

8.4 1 990 213 400 3.0 4 4.3

9.4 1 990 85 400 3.0 16 4.3

10.0 1 990 48 400 3.0 16 4.3

10.0 2 990 192 153 3.0 16 12.6

10.9 2 990 82 153 3.0 16 12.6

11.4 2 990 54 153 3.0 16 12.6

11.9 2 990 34 153 3.0 16 12.6

12.4 2 625 34 153 3.0 16 12.6

13.4 2 400 21 153 3.0 16 12.6

13.4 3 500 37 66 6.0 16 12.6

14.4 3 200 38 66 6.0 16 12.6

14.4 4 300 45 36 6.0 16 12.6

15.4 4 200 27 36 6.0 16 12.6

16.4 4 105 21 36 6.0 16 12.6

17.5 4 105 8 10 6.0 16 12.6

Table 8. System configuration table as a function of the equivalent star magnitude in R band.

5.1.2 Acquire reference phase

The AcquireRefAO must be issued to the AO system after two conditions have been met:

1. A previous PresetAO has completed successfully

2. Telescope is tracking on the expected target.

Guiding must be kept off because during the AcquireRefAO, a test closed loop is executed. Hence, the tip-tilt

correction performed by the AO system would interfere with telescope guiding.

The AcquireRefAO is a sequence of the following distinct operations:

• Locate and center AO star on acquisition camera. For this purpose, a series of frames is acquired and

averaged from the acquisition camera. The number of averaged frames (20 for bright stars up to 100 for

faint ones), as well as the integration time, are read from the configuration table loaded during the preset.

The brightest source (if any) is located and the XYZ stages are moved in order to bring the source on the

acquisition camera hot spot. This step is repeated up to 5 times until the source positioning error is less than

0.1 mm, corresponding to ~1/40 arcsec on sky. The source is usually centered after just one iteration,

except under bad seeing conditions in which case additional iterations are required to cope with stronger

image jitter. At the end of this operation, the star is centered on the pyramid.

• Move filter wheels to closed-loop positions. FW#1 is set to the dichroic 600-1000nm (~95% of the light

transmitted to the CCD39) in all cases. FW#2 is set to the narrow band filter (CW800nm BW10nm) for

stars with MR<7.5, and set to the open position for fainter star magnitudes.

• Measure actual AO star magnitude. A set of CCD39 frames is acquired and averaged, and the equivalent

star magnitude is computed based on the number of CCD counts inside the four pupil images. This estimate

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supersedes the one specified in the PresetAO command, and the configuration table (Table 8) is checked

again in order to see whether any parameters need to be adjusted. If this is the case, the new AO parameters

are selected and part of the PresetAO command (the CCD39 setup) is done again.

• Close a low-order loop. A preselected low-order reconstructor (first 5-10 modes) is loaded, and the loop is

closed with an integrator gain of 0.1 (CCD39 framerate unchanged). Also, the TT modulation is set to a

very high radius (±30λ/D) in order to be little sensitive to the non-corrected atmospheric residuals. The

correction of the low-order modes provides a more uniform illumination over the four pupil images and

improves their roundness.

• Pupil centering. It is crucial that the four pupil images are located in the nominal positions defined during

the pupil registration procedure (§ 2.3.3). Each reconstruction matrix is associated with a particular pupil

registration definition. The WFS camera lens is mounted on a piezo translation stage, so that the pupils can

be centered back to their nominal positions with an accuracy of less than ±0.1 pixels.

When the low-order loop is closed, the camera lens tracking loop automatically starts. This loop acquires a

set of CCD39 frames (~4 seconds total exposure). On the averaged CCD39 frame, the position of the four

pupil images is measured and the difference with respect to the expected one is computed (Figure 35). If

the difference is greater than 0.1 pixels, the camera lens is moved to shift the pupils on the CCD39 to the

correct position. When the measured position is inside the 0.1 pixel threshold, an “on target” flag is set and

the camera lens loop takes no action.

• As soon as the “on target” flag is set by the camera-lens tracking loop, the low-order loop is opened, and

the system is reconfigured with the parameters found in step 3. If the CCD39 framerate was adjusted, a new

dark is acquired. Finally, the integrator gain is set to 0.1. The AO system is ready for closed-loop operation.

5.1.3 Start phase: gain optimization procedure

The StartAO command closes the AO loop. This is done by enabling the fastlink fiber which sends the slopes to the

ASM unit. Immediately after loop closure, the gain optimization procedure is launched, just before giving back control

to the TCS.

Figure 35. Pupil centering procedure. (Left) CCD39 frame with four pupil images; the estimated pupil centers are

indicated with red lines. (Right) The CCD39 Viewer GUI showing the pupil data in real time.

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The optimal gain values strongly depend on the atmospheric conditions. The automatic gain optimization procedure

closes the AO loop and sweeps up the gain values from zero up to a predetermined value, while recording WFS signals.

The procedure requires several iterations as outlined below:

1. For the first iteration, a fixed ratio of 0.7 between the two gains is kept (gHO =0.7 gTT). The gain sweep is

repeated several times and WFS signals are collected.

2. WFS signals are multiplied by the AO reconstruction matrix, obtaining a set of modal coefficients vectors.

3. For each set of applied gains, the RMS value of the modal coefficients is calculated. Two separate RMS

values are computed: one for tip-tilt modes, and one for the higher-order modes. As a result, two curves of

RMS value versus gain are produced.

4. The gain for higher-order modes (gHO) is set to the value minimizing the corresponding RMS curve, and

the gain sweep is repeated this time changing only the TT gain (gTT).

5. The gain gTT is set to the value minimizing the new RMS curve, and the gain sweep is repeated for the

third time this time changing only the gain gHO .

The selected gains are the combination of the gTT and gHO values found in the second and third step, respectively.

A value of 0.1 is subtracted from these gains in order to give some additional stability margin in case of some changes

in the atmospheric conditions. The whole automatic gain optimization procedure takes about half a minute.

Once the optimized gains are determined, the AO system remains in closed-loop operation until a StopAO is

requested. Gain values are not further changed during normal AO operation.

5.2 Active settings

We will describe in this section some of the active procedures that have been implemented in the FLAO system. In

particular, the active pupil centering and the active CCD39 background correction.

5.2.1 Active pupil centering

Pupil displacements are expected to occur during the normal operation of the telescope due to residual misalignments

on the WFS board. In particular, it is known that as the telescope derotator changes position, pupil displacements of less

than 0.1 pixels will occur in a rotation of ~1.25 degrees [10]. In order to actively maintain the correct pupil registration

during the normal operation of the AO system, we have implemented an active pupil centering procedure. Basically, the

pupil position is monitored continuously and small offsets with the WFS camera lens are applied whenever required.

Since the illumination level is typically very low, at least 4 seconds of data (corresponding to a minimum of 400 CCD

frames at low sampling rates) are averaged to estimate the pupil position.

It is important to mention that the active pupil centering procedure has contributed to a major improvement in the

loop stability in particular when operating in binning mode #1, for which the pupil position can be maintained with a

precision of ±0.05 pixels. This precision exceeds by far the value of ±0.20 pixels considered in the baseline/goal

performance estimations [10].

5.2.2 Automatic CCD background correction

The CCD39 background level exhibited a strong dependency on temperature. Since background subtraction is

particularly critical when working with faint reference stars, an automatic CCD background correction was

implemented.

The CCD39 background automatic correction procedure maintains in real-time a running mean of background-

subtracted CCD frames and, once every second, estimates the background level on each CCD quadrant. This estimation

is done at the four corners of the CCD, where diffracted light from the pupil images is less likely to occur. For binning

mode #1, a square of 4x4 pixels at each corner is used whereas for binning mode #2 the square is 2x2 pixels and only

1x1 pixels for binning modes #3 and #4.

If the estimated average background level is different from zero, a new background frame is computed taking the

original one and adding to each quadrant the average value found in the corresponding CCD corner. The new

background is then sent to the BCU to be used immediately as the new CCD background.

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In order to avoid BCU lockups while the new background is set, the loop must be momentarily halted by stopping

the CCD integration. The total time required to perform these operations (CCD stop + background upload + CCD

restart) is ~100ms, mostly due to the relatively slow serial line controlling the CCD integration. The background

automatic correction may be required once every second in the worst case of a fast-changing background, but usually

the correction frequency goes down to once every few minutes after temperature has stabilized.

5.3 Day time performance verification

Before going on sky, the performance of the FLAO system was verified during daytime using the retro-reflector

configuration (§ 2.3.2). Daytime tests were crucial to verify the performance obtained with different reconstructors,

optimize automatic settings procedures (§ 5.2), and fine-tune system parameters. The WFS calibration fiber was used to

emulate reference stars of various equivalent magnitudes. Also, atmospheric disturbance was injected by the ASM unit

using the method developed for the tests at the ATT in Arcetri [5]. Figure 36 shows the SR in H band measured with the

IRTC as a function of equivalent R-star magnitude, for an emulated seeing of 0.8 arcsec and Vwind=15m/s. Baseline and

goal performance specifications (when using the retro-reflector) are also shown for comparison [10].

Let us compare the performance obtained with binning modes #1 and #2 for magnitudes between 10 and 10.5. This

is in fact the star flux regime in which to switch between these two system configurations (Table 8). Although binning

mode #1 offers a better performance in this regime, we have chosen to operate the system in binning mode #2 for the

sake of robustness. Indeed, when using binning mode #1, as shown in Table 8, it is expected to get ~48 photons per

subaperture per frame (i.e. ~12 photons on each pupil image). Variations on the received flux (e.g. due to the sudden

arrival of clouds) may cause loop instabilities when using this configuration. Of course, an alternative solution would

have been to keep binning mode #1 and work with slower sampling frequencies. However, due to the presence of

telescope vibrations, we have also preferred to run the system at its maximum frame rate (~1kHz), whenever possible,

to have a higher rejection bandwidth.

5.4 On-sky commissioning results

Figure 37 summarizes the on-sky performance results attained by the FLAO#1 system during the whole 2010

commissioning campaign. The SR in H band (1.60µm) was estimated from the long-exposure PSFs measured with the

IRTC [7]. Total integration times varied from 50ms for high-flux PSF measurements up to 120s for the low-flux ones.

The camera was operated in the narrow field-of-view mode with a pixel scale of 10 mas/pixel. A total of 597 Strehl

Ratio estimations at star magnitudes from ~7.5 to ~18 are shown in the plot. Seeing values estimated from AO real-time

data are coded in color. The histogram of seeing values is shown in Figure 38. Measurements at star magnitudes MR >13

Figure 36. Summary of daytime performance results: SR in H band as a function of the equivalent star

magnitude in R. Emulated turbulence parameters: s=0.8” and Vwind=15m/s. Binning modes: (+) #1; (∗) #2; (◊)

#3, and (�) #4. Dashed and dotted curves: goal and baseline performance specifications, respectively.

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for which seeing values are strongly under-estimated with this method are shown in black. Figure 37 also indicates

which system configuration (i.e. binning mode) has been used for each acquisition. Finally, the expected performance

estimated from numerical simulations and for different seeing values (0.6”, 0.8”, 1.0”, 1.2”, and 1.5”) is also shown in

the plot. It is important to note that the measured SR values are in accordance with the simulated ones, showing that the

FLAO#1 system meets the expected performance.

Figure 37. Summary plot of FLAO#1 performance commissioning results. Strehl Ratio in H band versus star magnitude

(R) and for different seeing values (estimated from AO real-time data). Points (MR >13) for which seeing values are

strongly under-estimated are shown in black. Different binning modes are indicated with symbols. Lines correspond to

expected performance from numerical simulations with different seeing values; from top to bottom: 0.6”, 0.8”, 1.0”,

1.2”, and 1.5”.

Figure 38. Histogram of seeing values estimated from AO real-time data corresponding to the datasets shown in

color in Figure 37. A total of 431 datasets were taken into account (MR <13). The median seeing from these

estimates is 0.7arcsec.

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Figure 39 shows some examples of AO-corrected PSFs sampling the range of star magnitudes 8<MR<17, and for a

seeing value of about 0.8arcsec. Note that a diffraction-limited resolution of 40mas is achieved down to magnitude ~12.

In the next subsections we will discuss some cases of particular interest.

Figure 39. Examples of AO-corrected PSFs (normalized to the diffraction-limited peak) acquired at different star

magnitudes. The system configurations are listed in Table 8. The seeing value for all of these acquisitions was about 0.8

arcsec. An OL PSF is also shown for comparison.

5.4.1 Performance at the bright end: high-contrast imaging

Figure 40 shows an example of a high-order corrected PSF in H band taken on June 25th

2010. Several images were

acquired (saturated and non-saturated) to compute the PSF profile with the required resolution. The equivalent R

magnitude of the GS (HD175658) is 6.5 and the estimated seeing value from real-time AO data oscillated between 0.6

and 0.8 arcsec. The AO loop was running at 1 kHz controlling 400 KL modes. Some residual TT vibrations @ 13.0-

13.7Hz of 6 to 8 mas RMS were present. The estimated SR in H band is >80%.

Figure 40 also shows the radial-averaged profiles of the AO-corrected and the diffraction-limited PSFs. Note that a

contrast better than 10-4

is achieved at a radial distance of ~0.4arcsec from the central peak. On the PSF image, it is

possible to count up to 10 rings around the diffraction-limited core of 40mas FWHM, up to the turbulence residual halo

(also known as the control radius) occurring at ~0.5arcsec. This value matches the theoretical value of λ/(2d) =

0.47arcsec where d is the effective inter-actuator distance d=dact (672/nmod)1/2

, and nmod stands for the number of

controlled modes (nmod=400) and dact is the actuator pitch projected to the primary mirror (dact=27cm), resulting in

d=35cm in this case.

The characteristics of this image confirm on sky for the first time the deep annular region where the non-aliased

correction offered by the pyramid sensor achieves the maximum contrast [17].

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5.4.2 Effect of residual vibrations

In this section we will show how the performance is affected by the presence of telescope vibrations. We will consider

the case of bright reference stars (7.5 < MR < 8.5) because under these conditions it is possible to acquire IRTC images

at fast sampling rates and hence estimate the TT residuals directly from the PSF image jitter.

Figure 41(left) shows the SR in H band versus the seeing value in this range of star magnitudes. The SR values

obtained from numerical simulations for MR=8.5 are also shown for comparison. Note that for a particular seeing value,

the spread of SR values can be quite wide. We have correlated the SR values obtained with a seeing of 0.9±0.1 arcsec

with the TT residual jitter due to the strongest vibrations occurring in the range from 13.0 to 13.7 Hz (§4.3). Figure

41(right) shows the SR versus the TT residual power cumulated in this frequency range, putting in evidence the loss in

performance due to telescope vibrations. The theoretical SR curve computed with the analytical SR attenuation factor

given by [15] is also shown in the plot. This theoretical curve represents an upper limit to the maximum SR value that

can be achieved. Note that the SR drops from the maximum attained of 75% to ~45% when the TT vibration residual

power in question reaches ~15 mas RMS.

Figure 40. (Left) High-order AO-corrected PSF using a bright star (MR = 6.5) under median seeing conditions

(seeing~0.7”±0.1”). (Right) Comparison between the diffraction-limited PSF (black full curve) and the AO-corrected

PSF profiles (red full curve). Profiles are normalized to the diffraction-limited peak.

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5.4.3 Performance at the faint end

We will present in this section the performance of the FLAO system with faint reference stars, close to the current

limiting magnitude. Figure 42 shows an example of the results obtained at MR= 17.2. The star observed was LP154-66

(MR=13.20, MH=10.17), and a neutral density filter was placed on the WFS channel to emulate a 17.2 R-magnitude star.

The system was operated with binning mode #4 and controlling only 10 modes giving a SR of ~3.5%. The FWHM of

the AO-corrected PSF is reduced a factor of 1.7 with respect to the seeing-limited one, and their peaks ratio equals 2.6.

A seeing estimate for this acquisition was not available from the DIMM. We can nevertheless use the FWHM of the

seeing-limited PSF and, assuming a given outer scale value, estimate the seeing as described in Sec. 4.2.3. Following

this method, and considering an outer scale of L0 = 40m, we get a seeing estimate of 0.72” (@ 500nm) for this

observation.

Figure 42. Example of the FLAO performance in H band at its faint end (MR= 17.2). (Left) Seeing-limited image.

(Middle) AO-corrected image. System parameters: binning mode #4, 10 controlled modes, 100Hz, and a modulation of

±6λs/D. Both images are normalized to their peak intensities. (Right) Images placed side by side to show the gain in

energy concentration. These images were produced from 5 IRTC frames of 3s exposure time each.

Figure 41. (Left) SR in H band versus seeing in high-flux regime (7.5 < MR < 8.5). Symbols stand for different

reference stars. Dashed curve: simulation results for MR=8.5. (Right) SR in H band versus TT residual power in the

frequency range from 13.0 to 13.7 Hz where the strongest telescope vibration is located. The seeing values were

restricted to 0.8” < s < 1.0”. Dashed curve: Theoretical SR in H band versus TT residual jitter according to [15].

Overall system parameters: binning mode #1, 400 modes, fs ≥ 990Hz, and fIRTC > 30Hz.

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Figure 43(Left) shows the FWHM of the measured PSFs (both in CL and OL) versus the estimated SR for datasets

taken with equivalent star magnitudes of MR=16.0±0.5. The system parameters are: bin#4, 36 modes, 100-200Hz, and a

modulation of ±6λs/D. The reduction of the FWHM provided by AO correction, and hence the gain in energy

concentration with respect to the OL (seeing-limited) PSFs is clearly seen in this plot. DIMM seeing values were not

available for these datasets. An estimate of the seeing value from the set of OL PSFs acquired close in time to the CL

PSFs are reported in Figure 43(Right).

5.5 Verification of FLAO operational requirements

5.5.1 System offsets in closed loop

The AO system is able to perform closed-loop offsets in X, Y and Z. The time required to execute the closed-loop offset

is of the order of a few (3-5) seconds per arcsecond. This makes this type of offsets efficient for on-sky displacements

of less than a few arcseconds and inefficient for larger values that could require several tens of seconds. Larger offsets

are generated using the open loop offset. The relative accuracy of the offsets in closed loop has been measured to be

less than 15mas PtV or 2.5 mas RMS. The offsets relative accuracy is related to the XYZ stages optical encoder

accuracy that is nominally of 0.3µm in the F/15 plane, leading to a maximum accuracy of less than 1 mas.

5.5.2 System offset in open loop

The AO system is able to perform open loop offsets in X, Y and Z. The time required to execute the open loop offsets is

largely independent of the AO system and of the offset amplitude. These offsets require usually around 20-30 seconds

to be performed. The time is dominated by the offset procedure of the telescope.

5.5.3 Static modes offloading to TCS

After the shell of the ASM is set and the pre-calibrated flattening command is applied, the current capacitive sensor

position is read and stored as reference position for offloading. When AO is in closed loop the difference between the

current capacitive sensor reading and the reference position is computed, averaged for 0.5 seconds and decomposed in

the first 22 Zernike coefficients using the inverse of the matrix described in Sec. 3.3. The piston term is rejected. The

Zernike coefficient vector is passed to AOS that converts it in TCS-PSF/MCS units multiplying them by a gain vector

and sent it to TCS-PSF (Z5,…,Z22) and MCS (Z2,Z3,Z4) for offloading if above a given threshold (in AOS units).

Thresholds and gains are stored in AOS configuration file DXOffloadModes.dat. When a Zernike mode is applied

following the procedure described in Sec. 3.3 (as for Astigmatism LUT versus elevation), the reference position is

changed accordingly to avoid the forced Zernike terms that are applied to the shell will be offloaded. The Tip, Tilt and

Focus terms have been routinely offloaded during all the AO runs without problems. The higher Zernike polynomials

have been tested on 11 Jun 2011 in collaboration with John Hill following the procedure:

Ref Star Seeing value

(arcsec)

AO1066 1.05 ± 0.07

AO1067 0.85 ± 0.02

AO182 NA

Wref311 0.97 ± 0.04

Wref347 0.76 ± 0.03

Figure 43. (Left) FWHM of the measured PSFs versus the SR for star magnitudes MR=16.0±0.5.

(Right) Estimated seeing value from the OL PSFs considering an outer scale of L0=50m.

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• the FLAO system is in closed loop on a bright star

• j-th Zernike is applied on primary mirror using Active Optics by John Hill with an amplitude Aj in TCS-

PSF units

• the WFE is corrected by the adaptive loop and the error is transferred to the gap between the shell and the

reference body

• the offload mechanism of the AO software (fastdiag process) computes the Zernike amplitude Bj to offload

without sending it to TCS-PSF through AOS

• the gain factor Cj=Aj/Bj is computed for the gain vector of AOS

• repeat for j=5, 6, … , 11

The calibrated gains Cj are stored in the AOS configuration file DXOffloadModes.dat and the test is repeated

enabling the offloading to TCS-PSF though AOS to verify that the offloading mechanism is converging. The

convergence was successful.

The calibrated gains Cj are reported in Table 9. Note that:

• AOS computes Zernike coefficients to offload in meters of RMS WFE

• Thresholds are given in meters of Zernike coefficients as computed by AOS

• Calibration has been done for just first 11 Zernike polynomials. Z12-Z22 coefficients are forced to zero.

j-th

Zernike

Cj Theshold

[m]

Receiver

(MCS/TCS-PSF)

1 0 1.0

2 -0.3×10-6

0.1×10-6

MCS

3 0.3×10-6

0.1×10-6

MCS

4 2×10-4

0.1×10-6

MCS

5 -0.2×10-9

0.1×10-6

TCS-PSF

6 -0.2×10-9

0.1×10-6

TCS-PSF

7 0.2×10-9

0.1×10-6

TCS-PSF

8 0.2×10-9

0.1×10-6

TCS-PSF

9 -0.2×10-9

0.1×10-6

TCS-PSF

10 -0.2×10-9

0.1×10-6

TCS-PSF

11 -0.2×10-9

0.1×10-6

TCS-PSF

12-22 0 0.5 TCS-PSF

Table 9. Calibrated gains for modal offloading of Zernike modes.

5.5.4 System operation at low and high elevations

We verified that the FLAO system can operate between 33 and 87 degrees of elevation. At high elevations, no issues

were detected regarding the fast de-rotations required. The limit at low elevations is due to the M2 shell, which cannot

be in “set configuration” below 20deg. Indeed, below this elevation the magnet-coil coupling starts to be repulsive

introducing instability on the shell in-plane rotation (see [13]) forcing the shell to go on rest mode. Therefore, the AO

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Arbitrator avoids setting the shell when the telescope goes below 25deg elevation; the 5deg more being a safe threshold

that takes into account the possible delay of elevation communication from the TCS to the AO Arbitrator.

6 Conclusions

The FLAO#1 system has been commissioned in the period February 2010-October 2011. The commissioning efforts

were in agreement with the original commissioning plan in terms of required manpower and overall required time. The

two main objectives of the commissioning plan have been achieved. The on sky results demonstrated (a) that the system

is able to reach the results expected using numerical simulations, (b) that the AO automatic control SW can operate the

system with an acceptable loss in performance. In absolute terms the FLAO system at the LBT telescopes got a step

forward in high angular resolution observations using ground based telescopes demonstrating SRs higher than 80% and

contrast better than 10^-4 in H band for reference star magnitude brighter than 9-10. Moreover the system limiting

magnitude was found to be around 17 mag where a SRs of about 5% in H band has been measured with good seeing.

Acknowledgments

The Arcetri AO group wants to thank all LBTO personnel and especially the LBTO mountain staff for the

continuous support during all the phases of the commissioning campaign.

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FLAO#1 commissioning report

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Transcript of FLAO#1 commissioning report