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Curr. Opt. Photon. 2022; 6(5): 445-452

Published online October 25, 2022 https://doi.org/10.3807/COPP.2022.6.5.445

Copyright © Optical Society of Korea.

Development and Characterization of an Atmospheric Turbulence Simulator Using Two Rotating Phase Plates

Ji Yong Joo1, Seok Gi Han1, Jun Ho Lee1,2 , Hyug-Gyo Rhee3,4, Joon Huh5, Kihun Lee5, Sang Yeong Park6

1Department of Optical Engineering and Metal Mold, Kongju National University, Cheonan 31080, Korea
2Institute of Application and Fusion for Light, Kongju National University, Cheonan 31080, Korea
3Optical imaging and metrology team, Advanced Instrumentation Institute, Korea Research Institute of Standards and Science, Daejeon 34113, Korea
4Department of Science of Measurement, University of Science and Technology, Daejeon 34113, Korea
5Defense Industry Technology Center, Seoul 07062, Korea
6Space Surveillance System TF Team, Hanwha Systems Co., Seongnam 13524, Korea

Corresponding author: *jhlsat@kongju.ac.kr, ORCID 0000-0002-4075-3504

Received: August 16, 2022; Revised: September 8, 2022; Accepted: September 15, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

We developed an adaptive optics test bench using an optical simulator and two rotating phase plates that mimicked the atmospheric turbulence at Bohyunsan Observatory. The observatory was reported to have a Fried parameter with a mean value of 85 mm and standard deviation of 13 mm, often expressed as 85 ± 13 mm. First, we fabricated several phase plates to generate realistic atmospheric-like turbulence. Then, we selected a pair from among the fabricated phase plates to emulate the atmospheric turbulence at the site. The result was 83 ± 11 mm. To address dynamic behavior, we emulated the atmospheric disturbance produced by a wind flow of 8.3 m/s by controlling the rotational speed of the phase plates. Finally, we investigated how closely the atmospheric disturbance simulation emulated reality with an investigation of the measurements on the optical table. The verification confirmed that the simulator showed a Fried parameter of 87 ± 15 mm as designed, but a little slower wind velocity (7.5 ± 2.5 m/s) than expected. This was because of the nonlinear motion of the phase plates. In conclusion, we successfully mimicked the atmospheric disturbance of Bohyunsan Observatory with an error of less than 10% in terms of Fried parameter and wind velocity.

Keywords: Adaptive optics, Atmospheric disturbance, Fried parameter, Phase plate, Turbulence simulator

OCIS codes: (010.1080) Active or adaptive optics; (010.1330) Atmospheric turbulence; (120.4640) Optical instruments

Before using adaptive optics (AO) systems, performance estimation and verification tests are essential [1-6]. In addition, there are temporal and spatial limitations to performing performance verification on-sky [7-9]. At the laboratory level, atmospheric turbulence simulations avoid these limitations. The phase plate is one of the laboratory level methods used for atmospheric turbulence simulation [1015]. Other methods include atmospheric turbulence simulations using air heating [16], a deformable mirror (DM) [15, 17, 18], and a liquid crystal (LC) [19, 20].

Among these approaches, the air heating method is the most cost-effective and easy to implement. However, it is difficult to control the atmospheric turbulence parameters, and it can undesirably heat nearby optical elements [16]. LC and DM are popular for simulating various atmospheric conditions since they have high spatial and temporal capability, to modulate the optical path lengths [1518]. But they are still expensive, and it remains difficult to simulate atmospheric turbulence with a small fried parameter without the use of beam reducing optics.

The phase plate does not have these disadvantages and can produce very high resolution and low-cost atmospheric turbulence simulations [1015]. In addition, it is possible to change the effective turbulence characteristics in a limited way by overlapping multiple phase plates along the beam path [11, 15].

We recently developed an optical test bench with an atmospheric simulator to evaluate a recently developed AO system for 1.6 m telescopes with a reduction ratio of 71.4, as shown in Fig. 1. The AO system first uses a newly developed DM [21], so the optical test bench implements an AO system almost identical to an optical bench to confirm the performance predictions estimated with statistical analysis and computer simulation [6]. Specifically, the atmospheric simulator successfully mimicked the atmospheric turbulence at Bohyunsan Observatory, one of the candidate sites for the AO system, by rotating two phase plates in opposite directions. In this paper, we report on the fabrication and evaluation of the atmospheric simulator.

Figure 1.Schematic diagram of the adaptive optics (AO) under development [6].

We have organized this paper as follows: in the following section, we report the fabrication of the phase plates used in the atmospheric simulator, which was done using etching and spray techniques on glass substrates to generate realistic atmospheric-like atmospheric turbulence, i.e. Kolmogorov turbulences. Then we report the emulation of the atmospheric disturbance at Bohyunsan Observatory in terms of spatial and temporal behaviors. In Section 3, we analyze how closely the atmospheric disturbance simulation emulated reality with an investigation of the measured wavefronts on the optical table.

As far as we are aware [22, 23], this is the first report on an analysis of how the rotating phase plates dynamically emulate atmospheric disturbance in terms of wind speed and directions. The analysis is important because it prevents the beam from rotating as the plate rotates, which is unnatural, but could occur due to the residual wedge angles of the phase plates.

2.1. Overview

We are currently developing an AO system for a 1.6-m ground telescope using a DM that was recently developed in South Korea [21]. The telescope focuses the incoming beam to its Nasmyth focus, which is then collimated to the AO system (called an AO module) with a beam reduction ratio (BR) of 1/71.4 regarding the telescope pupil diameter, per Eq. (1). Table 1 summarizes its system specifications.

TABLE 1 System specifications of the adaptive optics (AO) system

ParametersValue
Beam DiameterTelescope Pupil1,600 mm
AO Module22.4 mm
Shack-Hartmann Wavefront SensorDiameter22.4 mm
Sub-aperture23 × 23


BR=ReducedbeamdiameterTelescopediameter

where the telescope diameter is the entrance pupil diameter of the telescope, i.e. 1.6 m, and the reduced beam diameter is the collimated beam diameter entering the AO module.

The optical bench test implements an almost identical AO system (or module) on an optical table, to confirm the predicted system performance [6]. Figure 2 shows a schematic layout of the testbed composed of an atmospheric simulator and an AO simulator. Between the collimating optics and the tip/tilt mirror is the atmospheric simulator. The atmospheric simulator produces the atmospheric disturbance, by rotating two phase plates in the same direction or in different directions.

Figure 2.Schematic layout of the adaptive optics (AO) testbed.

The diameter of the entire phase-plate was 200 mm, and the actual beam diameter was 22.4 mm, located 70 mm away from the center. The two rotating phase plates can rotate in the same direction or in different directions, and the rotation speed is also adjustable. Figure 3 shows a schematic diagram of the phase plates and Fig. 4 shows a picture of two rotating plates.

Figure 3.Schematic diagram of the phase plate: (a) major dimensions, (b) effective sub-aperture of the phase plate as it rotates.

Figure 4.A picture of two rotating phase plates.

2.2. Atmospheric Disturbance at the Telescope Site

We mostly describe the optical effects of atmospheric disturbance using the Fried parameter (ro), and the coherence time or critical time constant (τo), as given below [1-3].

r0(λ)=0.185λ6/5cos3/5ς Cn2(h)dh3/5,

τ0=0.314r0V0

where Cn2h is the refractive index structure function at altitude h. The observed wavelength is λ in microns, and the observed angle is ξ, and the average velocity of the turbulence is Vo. We can convert the Fried parameter at one wavelength to another wavelength using the equation below:

r0λ=r00.5(λ/0.5)6/5.

From previous studies [5, 24, 25], Bohyunsan Observatory was measured to have a Fried parameter (ro) with a mean value of 85 mm and standard deviation of 13 mm at a wavelength of 0.5 μm, often simply expressed as 85 ± 13 mm. Table 2 lists the principal parameters of the atmospheric disturbance used for the design of the AO system. Table 3 lists the Fried parameters at four principal wavelengths.

TABLE 2 Atmospheric disturbance conditions at 0.5 μm

ParametersSymbolValues
Fried Parameterr085 ± 13 mm
Wind SpeedV08.3 ± 1.4 m/s


TABLE 3 Fried parameters at four principal wavelengths

ConditionWavelength (μm)Values (mm)
Reference (SLODARa)0.5085 ± 13
Wavefront Sensing (Rayleigh LGSb)0.5392 ± 13
Wavefront Sensing (Sodium LGS)0.59103 ± 14
Science Imaging0.63114 ± 16


2.3. Fabrication of the Phase Plates

We fabricated the phase plates on glass (BK7) substrates using etching and spray techniques to generate realistic atmospheric-like atmospheric turbulence, i.e. Kolmogorov turbulences [13, 14]. We etched the glass substrate with hydrofluoric acid to produce an overall turbulence profile shape, then applied a Krylon transparent acrylic paint to fabricate high-frequency patterns. The detailed process parameters, which will be reported in another publication, including etching time, spraying position/distance, and number of spraying injections, were investigated prior to fabrication.

Figure 5 shows interferograms of the four phase plates. In operation, a beam passes through a small area, a 22.4 mm diameter aperture, as drawn in Fig. 3. Figure 6 shows phase maps of a phase plate as it rotates with 30° increments.

Figure 5.Interferograms of the fabricated phase plates (unit: wave).

Figure 6.Sub-aperture phase maps of a phase plate as it rotates.

2.4. Spatial Behavior: Fried Parameters of the Fabricated Phase Plates

In Kolmogorov’s theory, we express the phase structure function of the phase ϕ at the entrance pupil of the telescope, with the piston and tip/tilt terms removed, as expressed below [1-3].

Dϕr=|ϕxϕx'|2=1.03 r r0 5/3

r=xx,

where x, x’ are position vector coordinates, and r is the distance between them. <> refers to the ensemble average.

We can rewrite Eq. (5) regarding the Fried parameter at the telescope pupil as below:

r0=1BR0.95 |ϕxϕx'|25/3r.

Using Eq. (7) in a least square regression manner, we can estimate the Fried parameter of a phase plate from its measured phase ϕA over a small aperture of 22.4 mm diameter as it rotates, as shown in Fig. 4. Table 4 summarizes the Fried parameters of the four phase plates at the reference wavelength, i.e. 0.5 μm, named plates 1, 2, 3, and 4.

TABLE 4 Fried parameters of the four fabricated phase plates

Plate No.Mean (mm)Standard Deviation (mm)
Plate 110927
Plate 211627
Plate 313813
Plate 415645


With two phase plates in use, the total wavefront deformation ϕt is a sum of the wavefront deformation due to each plate, designated ϕ1 and ϕ2.

ϕtx=ϕ1x+ϕ2x.

Similarly, we can equate the structure function of the total wavefront deformation as below.

Dϕtr=|ϕxϕx'|2=1.03 r r0,t 5/3,

where the total or effective Fried parameter is r0,t . Combining Eq. (5)–(9), we can estimate the total Fried parameter r0,t from the two Fried parameters of the phase plates in use, namely r0,1 and r0,2 equated as below:

r0,t=r0,1r0,2 r 0,1 5/3+r 0,2 5/33/5.

Table 5 summarizes the estimated Fried parameters of all pairs. The pair of plate 2 and plate 3, expressed as Plate 2 + 3, provided values most similar to the Fried parameters at the site.

TABLE 5 Fried parameters of the overlapped phase plates

PairMean (mm)Standard Deviation (mm)
Plate 1 + 27418
Plate 1 + 38011
Plate 1 + 48422
Plate 2 + 38311
Plate 2 + 48722
Plate 3 + 49612


2.5. Dynamic Behavior: Velocity of the Turbulence

The average velocity of the turbulence (Vo) corresponds to the duration over which the standard deviation of the phase fluctuations at a given point is of the order of 1 rad [13], equated as below:

Vo=V h 53Cn2 hdhCn2 hdh3/5.

With two phase plates in use, the total average velocity of the turbulence (Vo,t) can be approximated as the weighted sum of the velocities of each plate, named Vo,1 and Vo,2, respectively, as below:

Vo,t= V o,1 5/3 r 0,1 5/3+ V o,2 5/3 r 0,2 5/3 r 0,1 5/3+r 0,2 5/33/5.

To emulate the effect of wind at Bohyunsan Observatory, we rotated the phase plates at an angular speed to match the wind speed (Vo) of the site. Considering that the beam is reduced by the factor of the beam reduction ratio (BR) and the reduced beam is located 70 mm away from the center, as in Fig. 3, the simulated wind speed VS in m/s is formulated as below:

VS=1BR2πw60r,

where r is the offset distance in meters from the center, i.e. 70 mm, and w is the rotational speed of the phase plate in revolutions per minute (rpm).

The phase plates in use have strengths similar to the atmospheric disturbance as shown in Table 4. In addition to that, since the phase plates are statistically uncorrelated, we can determine the rotational speed of the phase plates, given below, which is approximately 15.9 rpm for the simulation at an average wind velocity (Vo) of 8.3 m/s.

w=BR602πVor,

3.1. Set-up

Figure 7 shows a picture of the optical test bench. It consists of an atmospheric simulator and an AO simulator. A wavefront sensor (Shack-Hartmann sensor) within the AO simulator records the deformed wavefront of the collimated beams that have passed through the atmospheric simulator. Table 6 summarizes the specifications of wavefront sensing.

TABLE 6 Specifications of wavefront sensing

ParametersValueSymbols
Sensor TypeShack-Hartmann Sensor [26]-
Wavelength532 nm-
Format (Lens Array)23 × 23N × N
Pitch112 μmP
Frame Rates1 KHzF


Figure 7.The optical test bench with the adaptive optics (AO) simulator and atmospheric simulator.

From a prior study using computer simulation [6], we found that the wavefront disturbance exhibits a run-to-run variation due to the random nature of atmospheric disturbance, which converges to values when the simulation time length is longer than 0.9 seconds, i.e. approximately 240 times the critical time constant of the applied atmospheric disturbance. Based on this finding, we recorded 1,000 wavefront data sampled for 1 second at 1 KHz. We present the nth wavefront as ϕn where ϕn is a phase matrix of 23 × 23.

In addition to that, the wavefront was converted to the reference wavelength of 0.5 μm from the wavefront sensing wavelength, i.e. 0.532 μm, using Eq. (4) prior to application in the following analysis.

3.2. Statistical Behavior: Fried Parameter

We calculated the Fried parameters of the recorded 1,000 wavefront samples using Eq. (7). Figure 8 plots a histogram of the calculated Fried parameters with a bin size of 10 mm. Table 7 summarizes the Fried parameters of the site and the atmospheric simulator. The simulated mean value of the Fried parameter has a deviation of 2.4% from the design value, i.e. 85 mm.

TABLE 7 Fried parameters of the site and the simulator

ConditionMinimum (1 sigma) (mm)Mean (mm)Maximum (1 sigma) (mm)
At the Site728598
Simulator(Design)728394
Simulator(Experiment)7287102


Figure 8.Histogram of the measured Fried parameters of the atmospheric simulator.

3.3. Dynamic Behavior: Wind Velocity

We estimated the wind velocity and direction with an analysis of the temporal correlation between two temporally adjacent wavefront samples, namely: ϕn and ϕn+1. We first calculated the correlation matrix C between the two adjacent waterfronts as we shifted the two wavefronts with respect to each other until the two phases overlapped one pixel [27]. In this study, C was a matrix of 45 × 45. For a shift of (δi, δj), the value of C(δi, δj) is given as below:

Cδi,δj=ijϕn i,jϕ n+1 i+δi,j+δjOδi,δj,

where (i, j) are the coordinates of a phase map. O(δi, δj) is the number of overlapped pixels with a shift of (δi, δj). Figures 9 and 10 show the overlapping matrix O and the correlation matrix C.

Figure 9.Overlapping matrix O.

Figure 10.Correlation matrix C.

Then we found the wind velocity (V) and direction (θ) by calculating the vector between the center point (i0, j0) and the peak point (ip, jp) in Fig. 10, as formulated below:

V=PFBR ipi02+jpj021/2,

θ=tan1jpj0ipi0.

Figure 11 plots the calculated direction and intensity of the wind in polar coordinates. Table 8 summarizes the calculated wind velocities. The mean velocity of the wind was 7.5 m/sec, which was 90.4% of the mean wind velocity of the site, i.e. 8.3 m/sec. We estimated that the difference would come from the nonlinear angular rotation of the phase plates. In order to compensate for the effect, we needed to rotate the phase plate with an angular speed of 10% more than the expected value, based on a linear motion assumption, i.e. 17.5 rpm.

TABLE 8 Wind velocity at the site and from the atmospheric simulator

ConditionMinimum (m/s)Mean (m/s)Maximum (m/s)
At the site6.98.39.7
Simulator (Design)8.3
Simulator (Experiment)5.07.510.0


Figure 11.Wind velocity and direction of the atmospheric simulator.

We developed an atmospheric simulator that emulated the atmospheric turbulence at Bohyunsan Observatory by rotating two phase plates in opposite directions. The emulated atmospheric disturbance was tested to have a Fried parameter of 87 ± 15 mm and wind velocity of 7.5 ± 2.5 m/s. The Fried parameters were within 2.4% of the estimation, but the wind velocities were about 9.6% slower than expected, which was due to the nonlinear motion, i.e., the angular rotation of the phase plates. We found that we needed about 10% faster speed than the value expected from the linear wind motion.

In conclusion, we successfully mimicked the astronomical optical disturbance of Bohyunsan Observatory with an error of less than 10% in terms of Fried parameter and wind velocity.

Data underlying the results presented in this paper are not publicly available at this time, but may be obtained from the authors upon reasonable request.

Supported by the Defense Industry Technology Center through a research program entitled “high-speed optical wavefront deformable mirror system performance analysis technology development research (UC180003D).”

  1. J. M. Beckers, “Adaptive optics for astronomy: principles, performance, and applications,” Annu. Rev. Astron. Astrophys. 31, 13-62 (1993).
    CrossRef
  2. D. L. Fried and J. F. Belsher, “Analysis of fundamental limits to artificial-guide-star adaptive-optics-system performance for astronomical imaging,” J. Opt. Soc. Am. A 11, 277-287 (1994).
    CrossRef
  3. M. Northcott, “Performance estimation and system modeling,” in Adaptive Optics in Astronomy, F. Roddier, Ed. (Cambridge University Press, Cambridge, UK, 1999), Chapter 2-7.
    CrossRef
  4. R. C. Flicker, “Efficient first-order performance estimation for high-order adaptive optics systems,” Astron. Astrophys. 405, 1177-1189 (2003).
    CrossRef
  5. J. H. Lee, S. E. Lee, and Y. J. Kong, “Performance prediction of a laser-guide star adaptive optics system for a 1.6 m telescope,” Curr. Opt. Photonics 2, 269-279 (2018).
  6. S. G. Han, J. Y. Joo, J. H. Lee, S. Y. Park, Y. S. Kim, Y. S. Jung, D. H. Jung, J. Huh, and K. Lee, “Performance prediction for an adaptive optics system using two analysis methods: statistical analysis and computational simulation,” Korean J. Opt. Photonics 33, 167-176 (2022).
  7. F. Rigaut, G. Rousset, P. Kern, J. C. Fontanella, J. P. Gaffard, F. Merkle, and P. Léna, “Adaptive optics on a 3.6-m telescope: results and performance,” Astron. Astronphys. 250, 280-290 (1991).
  8. J. S. Lawrence, “Adaptive-optics performance of Antarctic telescopes,” Appl. Opt. 43, 1435-1449 (2004).
    Pubmed CrossRef
  9. R. Briguglio, F. Quirós-Pacheco, J. R. Males, M. Xompero, A. Riccardi, L. M. Close, K. M. Morzinski, S. Esposito, E. Pinna, A. Puglisi, L. Schatz, and K. Mille, “Optical calibration and performance of the adaptive secondary mirror at the Magellan telescope,” Sci. Rep. 8, 10835 (2018).
    Pubmed KoreaMed CrossRef
  10. T. A. Rhoadarmer and R. P. Angel, “Low-cost, broadband static phase plate for generating atmospheric-like turbulence,” Appl. Opt. 40, 2946-2955 (2001).
    Pubmed CrossRef
  11. S. Thomas, “A simple turbulence simulator for adaptive optics,” Proc. SPIE 5490, 766-773 (2004).
    CrossRef
  12. S. Hippler, F. Hormuth, D. J. Butler, W. Brandner, and T. Henning, “Atmosphere-like turbulence generation with surface-etched phase-screens,” Opt. Express 14, 10139-10148 (2006).
    Pubmed CrossRef
  13. R. Rampy, D. Gavel, D. Dillon, and S. Thomas, “Production of phase screen for simulation of atmospheric turbulence,” Appl. Opt. 51, 8769-8778 (2012).
    Pubmed CrossRef
  14. X. Li, J. Lu, and Z. Feng, “Effect hydrofluoric acid etching of glass on the performance of organic-inorganic glass laminates,” Compos. B. Eng. 52, 207-210 (2013).
    CrossRef
  15. J. H. Lee, S. Shin, G. N. Park, H.-G. Rhee, and H.-S. Yang, “Atmospheric turbulence simulator for adaptive optics evaluation on an optical test bench,” Curr. Opt. Photonics 1, 107-112 (2017).
    CrossRef
  16. O. Keskin, L. Jolissaint, and C. Bradley, “Hot-air optical turbulence generator for the testing of adaptive optics systems: principles and characterization,” Appl. Opt. 45, 4888-4897 (2006).
    Pubmed CrossRef
  17. C. C. Wilcox, T. Martinez, F. Santiago, J. R. Andrews, S. R. Restaino, S. W. Teare, and D. Payne, “Atmospheric simulator for testing adaptive optic systems,” Proc. SPIE 7093, 709305 (2008).
    CrossRef
  18. L. A. Bolbasova, A. N. Gritsuta, V. V. Lavrinov, V. P. Lukin, A. A. Selin, and E. L. Soin, “Adaptive optics test bench for predictive wavefront correction,” Proc. SPIE 11056, 110563D (2019).
    CrossRef
  19. L. Hu, L. Xuan, D. Li, Z. Cao, Q. Mu, Y. Liu, Z. Peng, and X. Lu, “Real-time liquid-crystal atmosphere turbulence simulator with graphic processing unit,” Opt. Express 17, 7259-7268 (2009).
    Pubmed CrossRef
  20. X. Shan, M. Liu, N. N. Zhang, and Y. Ai, “Laboratory simulation of non-Kolmogorov turbulence based on a liquid crystal spatial light modulator,” Opt. Eng. 56, 026111 (2017).
    CrossRef
  21. P. Kang, J. Huh, K. Lee, S. Park, and H.-G. Rhee, “Design of a discrete flexure for a SiC deformable mirror with PMN stacked-actuators,” Opt. Express 29, 31778-31795 (2021).
    Pubmed CrossRef
  22. C. Ting, M. Giles, and D. Voelz, “Laboratory phase plate turbulence strength characterization,” Proc. SPIE 6306, 63060P (2006).
  23. X. Qiang, Y. Li, F. Zong, and J. Zhao, “Measurement of laboratory-simulated atmospheric turbulence by PSD,” in Proc. 9th International Conference on Electronic Measurement & Instruments (Beijing, China, Aug. 16-19, 2009), pp. 2-90-2-94.
  24. T. Butterley, R. W. Wilson, and M. Sarazin, “Determination of the profile of atmospheric optical turbulence strength from SLODAR data,” Mon. Not. R. Astron. Soc. 369, 835-845 (2006).
    CrossRef
  25. J. H. Lee, S. J. Ro, K. Kim, T. Butterley, R. Wilson, Y. Choi, and S. Lee, “Robotic SLODAR development for seeing evaluations at Bohyunsan Observatory,” in Proc. Advanced Maui Optical and Space Surveillance Technologies Conference (Maui, Hawaii, USA, Sep. 15-18, 2015).
  26. ALPAO, “Wavefront sensors,” (ALPO), https://www.alpao.com/products-and-services/wavefront-sensors/ (Accessed date: Aug. 10, 2022).
  27. L. Wang, M. Schöck, and G. Chanan, “Atmospheric turbulence profiling with SLODAR using multiple adaptive optics wavefront sensors,” Appl. Opt. 47, 1880-1892 (2008).
    Pubmed CrossRef

Article

Article

Curr. Opt. Photon. 2022; 6(5): 445-452

Published online October 25, 2022 https://doi.org/10.3807/COPP.2022.6.5.445

Copyright © Optical Society of Korea.

Development and Characterization of an Atmospheric Turbulence Simulator Using Two Rotating Phase Plates

Ji Yong Joo1, Seok Gi Han1, Jun Ho Lee1,2 , Hyug-Gyo Rhee3,4, Joon Huh5, Kihun Lee5, Sang Yeong Park6

1Department of Optical Engineering and Metal Mold, Kongju National University, Cheonan 31080, Korea
2Institute of Application and Fusion for Light, Kongju National University, Cheonan 31080, Korea
3Optical imaging and metrology team, Advanced Instrumentation Institute, Korea Research Institute of Standards and Science, Daejeon 34113, Korea
4Department of Science of Measurement, University of Science and Technology, Daejeon 34113, Korea
5Defense Industry Technology Center, Seoul 07062, Korea
6Space Surveillance System TF Team, Hanwha Systems Co., Seongnam 13524, Korea

Correspondence to:*jhlsat@kongju.ac.kr, ORCID 0000-0002-4075-3504

Received: August 16, 2022; Revised: September 8, 2022; Accepted: September 15, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We developed an adaptive optics test bench using an optical simulator and two rotating phase plates that mimicked the atmospheric turbulence at Bohyunsan Observatory. The observatory was reported to have a Fried parameter with a mean value of 85 mm and standard deviation of 13 mm, often expressed as 85 ± 13 mm. First, we fabricated several phase plates to generate realistic atmospheric-like turbulence. Then, we selected a pair from among the fabricated phase plates to emulate the atmospheric turbulence at the site. The result was 83 ± 11 mm. To address dynamic behavior, we emulated the atmospheric disturbance produced by a wind flow of 8.3 m/s by controlling the rotational speed of the phase plates. Finally, we investigated how closely the atmospheric disturbance simulation emulated reality with an investigation of the measurements on the optical table. The verification confirmed that the simulator showed a Fried parameter of 87 ± 15 mm as designed, but a little slower wind velocity (7.5 ± 2.5 m/s) than expected. This was because of the nonlinear motion of the phase plates. In conclusion, we successfully mimicked the atmospheric disturbance of Bohyunsan Observatory with an error of less than 10% in terms of Fried parameter and wind velocity.

Keywords: Adaptive optics, Atmospheric disturbance, Fried parameter, Phase plate, Turbulence simulator

I. INTRODUCTION

Before using adaptive optics (AO) systems, performance estimation and verification tests are essential [1-6]. In addition, there are temporal and spatial limitations to performing performance verification on-sky [7-9]. At the laboratory level, atmospheric turbulence simulations avoid these limitations. The phase plate is one of the laboratory level methods used for atmospheric turbulence simulation [1015]. Other methods include atmospheric turbulence simulations using air heating [16], a deformable mirror (DM) [15, 17, 18], and a liquid crystal (LC) [19, 20].

Among these approaches, the air heating method is the most cost-effective and easy to implement. However, it is difficult to control the atmospheric turbulence parameters, and it can undesirably heat nearby optical elements [16]. LC and DM are popular for simulating various atmospheric conditions since they have high spatial and temporal capability, to modulate the optical path lengths [1518]. But they are still expensive, and it remains difficult to simulate atmospheric turbulence with a small fried parameter without the use of beam reducing optics.

The phase plate does not have these disadvantages and can produce very high resolution and low-cost atmospheric turbulence simulations [1015]. In addition, it is possible to change the effective turbulence characteristics in a limited way by overlapping multiple phase plates along the beam path [11, 15].

We recently developed an optical test bench with an atmospheric simulator to evaluate a recently developed AO system for 1.6 m telescopes with a reduction ratio of 71.4, as shown in Fig. 1. The AO system first uses a newly developed DM [21], so the optical test bench implements an AO system almost identical to an optical bench to confirm the performance predictions estimated with statistical analysis and computer simulation [6]. Specifically, the atmospheric simulator successfully mimicked the atmospheric turbulence at Bohyunsan Observatory, one of the candidate sites for the AO system, by rotating two phase plates in opposite directions. In this paper, we report on the fabrication and evaluation of the atmospheric simulator.

Figure 1. Schematic diagram of the adaptive optics (AO) under development [6].

We have organized this paper as follows: in the following section, we report the fabrication of the phase plates used in the atmospheric simulator, which was done using etching and spray techniques on glass substrates to generate realistic atmospheric-like atmospheric turbulence, i.e. Kolmogorov turbulences. Then we report the emulation of the atmospheric disturbance at Bohyunsan Observatory in terms of spatial and temporal behaviors. In Section 3, we analyze how closely the atmospheric disturbance simulation emulated reality with an investigation of the measured wavefronts on the optical table.

As far as we are aware [22, 23], this is the first report on an analysis of how the rotating phase plates dynamically emulate atmospheric disturbance in terms of wind speed and directions. The analysis is important because it prevents the beam from rotating as the plate rotates, which is unnatural, but could occur due to the residual wedge angles of the phase plates.

Ⅱ. Atmospheric Simulator: Design and Analysis

2.1. Overview

We are currently developing an AO system for a 1.6-m ground telescope using a DM that was recently developed in South Korea [21]. The telescope focuses the incoming beam to its Nasmyth focus, which is then collimated to the AO system (called an AO module) with a beam reduction ratio (BR) of 1/71.4 regarding the telescope pupil diameter, per Eq. (1). Table 1 summarizes its system specifications.

TABLE 1. System specifications of the adaptive optics (AO) system.

ParametersValue
Beam DiameterTelescope Pupil1,600 mm
AO Module22.4 mm
Shack-Hartmann Wavefront SensorDiameter22.4 mm
Sub-aperture23 × 23


BR=ReducedbeamdiameterTelescopediameter

where the telescope diameter is the entrance pupil diameter of the telescope, i.e. 1.6 m, and the reduced beam diameter is the collimated beam diameter entering the AO module.

The optical bench test implements an almost identical AO system (or module) on an optical table, to confirm the predicted system performance [6]. Figure 2 shows a schematic layout of the testbed composed of an atmospheric simulator and an AO simulator. Between the collimating optics and the tip/tilt mirror is the atmospheric simulator. The atmospheric simulator produces the atmospheric disturbance, by rotating two phase plates in the same direction or in different directions.

Figure 2. Schematic layout of the adaptive optics (AO) testbed.

The diameter of the entire phase-plate was 200 mm, and the actual beam diameter was 22.4 mm, located 70 mm away from the center. The two rotating phase plates can rotate in the same direction or in different directions, and the rotation speed is also adjustable. Figure 3 shows a schematic diagram of the phase plates and Fig. 4 shows a picture of two rotating plates.

Figure 3. Schematic diagram of the phase plate: (a) major dimensions, (b) effective sub-aperture of the phase plate as it rotates.

Figure 4. A picture of two rotating phase plates.

2.2. Atmospheric Disturbance at the Telescope Site

We mostly describe the optical effects of atmospheric disturbance using the Fried parameter (ro), and the coherence time or critical time constant (τo), as given below [1-3].

r0(λ)=0.185λ6/5cos3/5ς Cn2(h)dh3/5,

τ0=0.314r0V0

where Cn2h is the refractive index structure function at altitude h. The observed wavelength is λ in microns, and the observed angle is ξ, and the average velocity of the turbulence is Vo. We can convert the Fried parameter at one wavelength to another wavelength using the equation below:

r0λ=r00.5(λ/0.5)6/5.

From previous studies [5, 24, 25], Bohyunsan Observatory was measured to have a Fried parameter (ro) with a mean value of 85 mm and standard deviation of 13 mm at a wavelength of 0.5 μm, often simply expressed as 85 ± 13 mm. Table 2 lists the principal parameters of the atmospheric disturbance used for the design of the AO system. Table 3 lists the Fried parameters at four principal wavelengths.

TABLE 2. Atmospheric disturbance conditions at 0.5 μm.

ParametersSymbolValues
Fried Parameterr085 ± 13 mm
Wind SpeedV08.3 ± 1.4 m/s


TABLE 3. Fried parameters at four principal wavelengths.

ConditionWavelength (μm)Values (mm)
Reference (SLODARa)0.5085 ± 13
Wavefront Sensing (Rayleigh LGSb)0.5392 ± 13
Wavefront Sensing (Sodium LGS)0.59103 ± 14
Science Imaging0.63114 ± 16


2.3. Fabrication of the Phase Plates

We fabricated the phase plates on glass (BK7) substrates using etching and spray techniques to generate realistic atmospheric-like atmospheric turbulence, i.e. Kolmogorov turbulences [13, 14]. We etched the glass substrate with hydrofluoric acid to produce an overall turbulence profile shape, then applied a Krylon transparent acrylic paint to fabricate high-frequency patterns. The detailed process parameters, which will be reported in another publication, including etching time, spraying position/distance, and number of spraying injections, were investigated prior to fabrication.

Figure 5 shows interferograms of the four phase plates. In operation, a beam passes through a small area, a 22.4 mm diameter aperture, as drawn in Fig. 3. Figure 6 shows phase maps of a phase plate as it rotates with 30° increments.

Figure 5. Interferograms of the fabricated phase plates (unit: wave).

Figure 6. Sub-aperture phase maps of a phase plate as it rotates.

2.4. Spatial Behavior: Fried Parameters of the Fabricated Phase Plates

In Kolmogorov’s theory, we express the phase structure function of the phase ϕ at the entrance pupil of the telescope, with the piston and tip/tilt terms removed, as expressed below [1-3].

Dϕr=|ϕxϕx'|2=1.03 r r0 5/3

r=xx,

where x, x’ are position vector coordinates, and r is the distance between them. <> refers to the ensemble average.

We can rewrite Eq. (5) regarding the Fried parameter at the telescope pupil as below:

r0=1BR0.95 |ϕxϕx'|25/3r.

Using Eq. (7) in a least square regression manner, we can estimate the Fried parameter of a phase plate from its measured phase ϕA over a small aperture of 22.4 mm diameter as it rotates, as shown in Fig. 4. Table 4 summarizes the Fried parameters of the four phase plates at the reference wavelength, i.e. 0.5 μm, named plates 1, 2, 3, and 4.

TABLE 4. Fried parameters of the four fabricated phase plates.

Plate No.Mean (mm)Standard Deviation (mm)
Plate 110927
Plate 211627
Plate 313813
Plate 415645


With two phase plates in use, the total wavefront deformation ϕt is a sum of the wavefront deformation due to each plate, designated ϕ1 and ϕ2.

ϕtx=ϕ1x+ϕ2x.

Similarly, we can equate the structure function of the total wavefront deformation as below.

Dϕtr=|ϕxϕx'|2=1.03 r r0,t 5/3,

where the total or effective Fried parameter is r0,t . Combining Eq. (5)–(9), we can estimate the total Fried parameter r0,t from the two Fried parameters of the phase plates in use, namely r0,1 and r0,2 equated as below:

r0,t=r0,1r0,2 r 0,1 5/3+r 0,2 5/33/5.

Table 5 summarizes the estimated Fried parameters of all pairs. The pair of plate 2 and plate 3, expressed as Plate 2 + 3, provided values most similar to the Fried parameters at the site.

TABLE 5. Fried parameters of the overlapped phase plates.

PairMean (mm)Standard Deviation (mm)
Plate 1 + 27418
Plate 1 + 38011
Plate 1 + 48422
Plate 2 + 38311
Plate 2 + 48722
Plate 3 + 49612


2.5. Dynamic Behavior: Velocity of the Turbulence

The average velocity of the turbulence (Vo) corresponds to the duration over which the standard deviation of the phase fluctuations at a given point is of the order of 1 rad [13], equated as below:

Vo=V h 53Cn2 hdhCn2 hdh3/5.

With two phase plates in use, the total average velocity of the turbulence (Vo,t) can be approximated as the weighted sum of the velocities of each plate, named Vo,1 and Vo,2, respectively, as below:

Vo,t= V o,1 5/3 r 0,1 5/3+ V o,2 5/3 r 0,2 5/3 r 0,1 5/3+r 0,2 5/33/5.

To emulate the effect of wind at Bohyunsan Observatory, we rotated the phase plates at an angular speed to match the wind speed (Vo) of the site. Considering that the beam is reduced by the factor of the beam reduction ratio (BR) and the reduced beam is located 70 mm away from the center, as in Fig. 3, the simulated wind speed VS in m/s is formulated as below:

VS=1BR2πw60r,

where r is the offset distance in meters from the center, i.e. 70 mm, and w is the rotational speed of the phase plate in revolutions per minute (rpm).

The phase plates in use have strengths similar to the atmospheric disturbance as shown in Table 4. In addition to that, since the phase plates are statistically uncorrelated, we can determine the rotational speed of the phase plates, given below, which is approximately 15.9 rpm for the simulation at an average wind velocity (Vo) of 8.3 m/s.

w=BR602πVor,

III. Experiment

3.1. Set-up

Figure 7 shows a picture of the optical test bench. It consists of an atmospheric simulator and an AO simulator. A wavefront sensor (Shack-Hartmann sensor) within the AO simulator records the deformed wavefront of the collimated beams that have passed through the atmospheric simulator. Table 6 summarizes the specifications of wavefront sensing.

TABLE 6. Specifications of wavefront sensing.

ParametersValueSymbols
Sensor TypeShack-Hartmann Sensor [26]-
Wavelength532 nm-
Format (Lens Array)23 × 23N × N
Pitch112 μmP
Frame Rates1 KHzF


Figure 7. The optical test bench with the adaptive optics (AO) simulator and atmospheric simulator.

From a prior study using computer simulation [6], we found that the wavefront disturbance exhibits a run-to-run variation due to the random nature of atmospheric disturbance, which converges to values when the simulation time length is longer than 0.9 seconds, i.e. approximately 240 times the critical time constant of the applied atmospheric disturbance. Based on this finding, we recorded 1,000 wavefront data sampled for 1 second at 1 KHz. We present the nth wavefront as ϕn where ϕn is a phase matrix of 23 × 23.

In addition to that, the wavefront was converted to the reference wavelength of 0.5 μm from the wavefront sensing wavelength, i.e. 0.532 μm, using Eq. (4) prior to application in the following analysis.

3.2. Statistical Behavior: Fried Parameter

We calculated the Fried parameters of the recorded 1,000 wavefront samples using Eq. (7). Figure 8 plots a histogram of the calculated Fried parameters with a bin size of 10 mm. Table 7 summarizes the Fried parameters of the site and the atmospheric simulator. The simulated mean value of the Fried parameter has a deviation of 2.4% from the design value, i.e. 85 mm.

TABLE 7. Fried parameters of the site and the simulator.

ConditionMinimum (1 sigma) (mm)Mean (mm)Maximum (1 sigma) (mm)
At the Site728598
Simulator(Design)728394
Simulator(Experiment)7287102


Figure 8. Histogram of the measured Fried parameters of the atmospheric simulator.

3.3. Dynamic Behavior: Wind Velocity

We estimated the wind velocity and direction with an analysis of the temporal correlation between two temporally adjacent wavefront samples, namely: ϕn and ϕn+1. We first calculated the correlation matrix C between the two adjacent waterfronts as we shifted the two wavefronts with respect to each other until the two phases overlapped one pixel [27]. In this study, C was a matrix of 45 × 45. For a shift of (δi, δj), the value of C(δi, δj) is given as below:

Cδi,δj=ijϕn i,jϕ n+1 i+δi,j+δjOδi,δj,

where (i, j) are the coordinates of a phase map. O(δi, δj) is the number of overlapped pixels with a shift of (δi, δj). Figures 9 and 10 show the overlapping matrix O and the correlation matrix C.

Figure 9. Overlapping matrix O.

Figure 10. Correlation matrix C.

Then we found the wind velocity (V) and direction (θ) by calculating the vector between the center point (i0, j0) and the peak point (ip, jp) in Fig. 10, as formulated below:

V=PFBR ipi02+jpj021/2,

θ=tan1jpj0ipi0.

Figure 11 plots the calculated direction and intensity of the wind in polar coordinates. Table 8 summarizes the calculated wind velocities. The mean velocity of the wind was 7.5 m/sec, which was 90.4% of the mean wind velocity of the site, i.e. 8.3 m/sec. We estimated that the difference would come from the nonlinear angular rotation of the phase plates. In order to compensate for the effect, we needed to rotate the phase plate with an angular speed of 10% more than the expected value, based on a linear motion assumption, i.e. 17.5 rpm.

TABLE 8. Wind velocity at the site and from the atmospheric simulator.

ConditionMinimum (m/s)Mean (m/s)Maximum (m/s)
At the site6.98.39.7
Simulator (Design)8.3
Simulator (Experiment)5.07.510.0


Figure 11. Wind velocity and direction of the atmospheric simulator.

IV. Conclusions

We developed an atmospheric simulator that emulated the atmospheric turbulence at Bohyunsan Observatory by rotating two phase plates in opposite directions. The emulated atmospheric disturbance was tested to have a Fried parameter of 87 ± 15 mm and wind velocity of 7.5 ± 2.5 m/s. The Fried parameters were within 2.4% of the estimation, but the wind velocities were about 9.6% slower than expected, which was due to the nonlinear motion, i.e., the angular rotation of the phase plates. We found that we needed about 10% faster speed than the value expected from the linear wind motion.

In conclusion, we successfully mimicked the astronomical optical disturbance of Bohyunsan Observatory with an error of less than 10% in terms of Fried parameter and wind velocity.

DISCLOSURES

The authors declare no conflict of interest.

DATA AVAILABILITY

Data underlying the results presented in this paper are not publicly available at this time, but may be obtained from the authors upon reasonable request.

FUNDING

Supported by the Defense Industry Technology Center through a research program entitled “high-speed optical wavefront deformable mirror system performance analysis technology development research (UC180003D).”

Fig 1.

Figure 1.Schematic diagram of the adaptive optics (AO) under development [6].
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 2.

Figure 2.Schematic layout of the adaptive optics (AO) testbed.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 3.

Figure 3.Schematic diagram of the phase plate: (a) major dimensions, (b) effective sub-aperture of the phase plate as it rotates.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 4.

Figure 4.A picture of two rotating phase plates.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 5.

Figure 5.Interferograms of the fabricated phase plates (unit: wave).
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 6.

Figure 6.Sub-aperture phase maps of a phase plate as it rotates.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 7.

Figure 7.The optical test bench with the adaptive optics (AO) simulator and atmospheric simulator.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 8.

Figure 8.Histogram of the measured Fried parameters of the atmospheric simulator.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 9.

Figure 9.Overlapping matrix O.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 10.

Figure 10.Correlation matrix C.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

Fig 11.

Figure 11.Wind velocity and direction of the atmospheric simulator.
Current Optics and Photonics 2022; 6: 445-452https://doi.org/10.3807/COPP.2022.6.5.445

TABLE 1 System specifications of the adaptive optics (AO) system

ParametersValue
Beam DiameterTelescope Pupil1,600 mm
AO Module22.4 mm
Shack-Hartmann Wavefront SensorDiameter22.4 mm
Sub-aperture23 × 23

TABLE 2 Atmospheric disturbance conditions at 0.5 μm

ParametersSymbolValues
Fried Parameterr085 ± 13 mm
Wind SpeedV08.3 ± 1.4 m/s

TABLE 3 Fried parameters at four principal wavelengths

ConditionWavelength (μm)Values (mm)
Reference (SLODARa)0.5085 ± 13
Wavefront Sensing (Rayleigh LGSb)0.5392 ± 13
Wavefront Sensing (Sodium LGS)0.59103 ± 14
Science Imaging0.63114 ± 16

TABLE 4 Fried parameters of the four fabricated phase plates

Plate No.Mean (mm)Standard Deviation (mm)
Plate 110927
Plate 211627
Plate 313813
Plate 415645

TABLE 5 Fried parameters of the overlapped phase plates

PairMean (mm)Standard Deviation (mm)
Plate 1 + 27418
Plate 1 + 38011
Plate 1 + 48422
Plate 2 + 38311
Plate 2 + 48722
Plate 3 + 49612

TABLE 6 Specifications of wavefront sensing

ParametersValueSymbols
Sensor TypeShack-Hartmann Sensor [26]-
Wavelength532 nm-
Format (Lens Array)23 × 23N × N
Pitch112 μmP
Frame Rates1 KHzF

TABLE 7 Fried parameters of the site and the simulator

ConditionMinimum (1 sigma) (mm)Mean (mm)Maximum (1 sigma) (mm)
At the Site728598
Simulator(Design)728394
Simulator(Experiment)7287102

TABLE 8 Wind velocity at the site and from the atmospheric simulator

ConditionMinimum (m/s)Mean (m/s)Maximum (m/s)
At the site6.98.39.7
Simulator (Design)8.3
Simulator (Experiment)5.07.510.0

References

  1. J. M. Beckers, “Adaptive optics for astronomy: principles, performance, and applications,” Annu. Rev. Astron. Astrophys. 31, 13-62 (1993).
    CrossRef
  2. D. L. Fried and J. F. Belsher, “Analysis of fundamental limits to artificial-guide-star adaptive-optics-system performance for astronomical imaging,” J. Opt. Soc. Am. A 11, 277-287 (1994).
    CrossRef
  3. M. Northcott, “Performance estimation and system modeling,” in Adaptive Optics in Astronomy, F. Roddier, Ed. (Cambridge University Press, Cambridge, UK, 1999), Chapter 2-7.
    CrossRef
  4. R. C. Flicker, “Efficient first-order performance estimation for high-order adaptive optics systems,” Astron. Astrophys. 405, 1177-1189 (2003).
    CrossRef
  5. J. H. Lee, S. E. Lee, and Y. J. Kong, “Performance prediction of a laser-guide star adaptive optics system for a 1.6 m telescope,” Curr. Opt. Photonics 2, 269-279 (2018).
  6. S. G. Han, J. Y. Joo, J. H. Lee, S. Y. Park, Y. S. Kim, Y. S. Jung, D. H. Jung, J. Huh, and K. Lee, “Performance prediction for an adaptive optics system using two analysis methods: statistical analysis and computational simulation,” Korean J. Opt. Photonics 33, 167-176 (2022).
  7. F. Rigaut, G. Rousset, P. Kern, J. C. Fontanella, J. P. Gaffard, F. Merkle, and P. Léna, “Adaptive optics on a 3.6-m telescope: results and performance,” Astron. Astronphys. 250, 280-290 (1991).
  8. J. S. Lawrence, “Adaptive-optics performance of Antarctic telescopes,” Appl. Opt. 43, 1435-1449 (2004).
    Pubmed CrossRef
  9. R. Briguglio, F. Quirós-Pacheco, J. R. Males, M. Xompero, A. Riccardi, L. M. Close, K. M. Morzinski, S. Esposito, E. Pinna, A. Puglisi, L. Schatz, and K. Mille, “Optical calibration and performance of the adaptive secondary mirror at the Magellan telescope,” Sci. Rep. 8, 10835 (2018).
    Pubmed KoreaMed CrossRef
  10. T. A. Rhoadarmer and R. P. Angel, “Low-cost, broadband static phase plate for generating atmospheric-like turbulence,” Appl. Opt. 40, 2946-2955 (2001).
    Pubmed CrossRef
  11. S. Thomas, “A simple turbulence simulator for adaptive optics,” Proc. SPIE 5490, 766-773 (2004).
    CrossRef
  12. S. Hippler, F. Hormuth, D. J. Butler, W. Brandner, and T. Henning, “Atmosphere-like turbulence generation with surface-etched phase-screens,” Opt. Express 14, 10139-10148 (2006).
    Pubmed CrossRef
  13. R. Rampy, D. Gavel, D. Dillon, and S. Thomas, “Production of phase screen for simulation of atmospheric turbulence,” Appl. Opt. 51, 8769-8778 (2012).
    Pubmed CrossRef
  14. X. Li, J. Lu, and Z. Feng, “Effect hydrofluoric acid etching of glass on the performance of organic-inorganic glass laminates,” Compos. B. Eng. 52, 207-210 (2013).
    CrossRef
  15. J. H. Lee, S. Shin, G. N. Park, H.-G. Rhee, and H.-S. Yang, “Atmospheric turbulence simulator for adaptive optics evaluation on an optical test bench,” Curr. Opt. Photonics 1, 107-112 (2017).
    CrossRef
  16. O. Keskin, L. Jolissaint, and C. Bradley, “Hot-air optical turbulence generator for the testing of adaptive optics systems: principles and characterization,” Appl. Opt. 45, 4888-4897 (2006).
    Pubmed CrossRef
  17. C. C. Wilcox, T. Martinez, F. Santiago, J. R. Andrews, S. R. Restaino, S. W. Teare, and D. Payne, “Atmospheric simulator for testing adaptive optic systems,” Proc. SPIE 7093, 709305 (2008).
    CrossRef
  18. L. A. Bolbasova, A. N. Gritsuta, V. V. Lavrinov, V. P. Lukin, A. A. Selin, and E. L. Soin, “Adaptive optics test bench for predictive wavefront correction,” Proc. SPIE 11056, 110563D (2019).
    CrossRef
  19. L. Hu, L. Xuan, D. Li, Z. Cao, Q. Mu, Y. Liu, Z. Peng, and X. Lu, “Real-time liquid-crystal atmosphere turbulence simulator with graphic processing unit,” Opt. Express 17, 7259-7268 (2009).
    Pubmed CrossRef
  20. X. Shan, M. Liu, N. N. Zhang, and Y. Ai, “Laboratory simulation of non-Kolmogorov turbulence based on a liquid crystal spatial light modulator,” Opt. Eng. 56, 026111 (2017).
    CrossRef
  21. P. Kang, J. Huh, K. Lee, S. Park, and H.-G. Rhee, “Design of a discrete flexure for a SiC deformable mirror with PMN stacked-actuators,” Opt. Express 29, 31778-31795 (2021).
    Pubmed CrossRef
  22. C. Ting, M. Giles, and D. Voelz, “Laboratory phase plate turbulence strength characterization,” Proc. SPIE 6306, 63060P (2006).
  23. X. Qiang, Y. Li, F. Zong, and J. Zhao, “Measurement of laboratory-simulated atmospheric turbulence by PSD,” in Proc. 9th International Conference on Electronic Measurement & Instruments (Beijing, China, Aug. 16-19, 2009), pp. 2-90-2-94.
  24. T. Butterley, R. W. Wilson, and M. Sarazin, “Determination of the profile of atmospheric optical turbulence strength from SLODAR data,” Mon. Not. R. Astron. Soc. 369, 835-845 (2006).
    CrossRef
  25. J. H. Lee, S. J. Ro, K. Kim, T. Butterley, R. Wilson, Y. Choi, and S. Lee, “Robotic SLODAR development for seeing evaluations at Bohyunsan Observatory,” in Proc. Advanced Maui Optical and Space Surveillance Technologies Conference (Maui, Hawaii, USA, Sep. 15-18, 2015).
  26. ALPAO, “Wavefront sensors,” (ALPO), https://www.alpao.com/products-and-services/wavefront-sensors/ (Accessed date: Aug. 10, 2022).
  27. L. Wang, M. Schöck, and G. Chanan, “Atmospheric turbulence profiling with SLODAR using multiple adaptive optics wavefront sensors,” Appl. Opt. 47, 1880-1892 (2008).
    Pubmed CrossRef