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1.INTRODUCTIONSpace telescopes with 10-m-class primary mirrors are currently being studied for astronomy, in particular for characterization of exoplanets, and for Earth observation from the geostationary orbit. Such telescopes will need to have segmented, lightweight primaries in order to reduce mass and stowed volume. Active optics at the primary mirror and/or in a plane conjugate to the primary mirror will be required to co-phase the segments, align the optical telescope, and correct for manufacturing errors and slow drifts caused by thermo-elastic effects and gravitational release. The method we discuss here requires a continuous surface of the active element, because we use the Zernike modes to describe the active element. Therefore, in the case of a segmented mirror, the segments should be already co-phased by using another technique. Conventional adaptive optics measures the wavefront and applies its inverse to the corrective active element. Direct wavefront sensing using a dedicated wavefront sensor requires a bright guide star and results in non-common path errors. In addition, the angular separation between the science target and the guide star leads to anisoplanatism. In ground-based telescopes, anisoplanatism is reduced with sophisticated concepts such as multi-conjugate adaptive optics, by using several guide stars, wavefront sensors, and corrective elements. Indirect wavefront sensing uses the science camera and an iterative method, e.g., phase diversity, to retrieve the wavefront. Although phase diversity is technically image-based, here we use the term “image-based” to refer to correction methods that do not require the wavefront information. In this sense, phase diversity is not an image-based method. Our image-based method evaluates the image of the science camera and adapts the surface of the active element to increase a merit function. It can handle large aberrations, in contrast to wavefront sensing that has limited dynamic range. Using an image-based method, active optics would allow image optimization for different objectives, e.g., for maximization of contrast in high or in low spatial frequencies, depending on the science target. In this paper we discuss the landscape of an image-sharpness metric used as merit function when we control the surface of the active element with Zernike modes. Zernike modes are orthogonal to each other over a unit circle with respect to the wavefront. They are also orthogonal to each other with respect to our merit function for small aberrations, but we demonstrate that this is not valid for aberrations of more than λ/8 RMS. We aim at the optimization of severely aberrated systems with several λ of aberration and low Strehl ratio. This is represented by the second transition in the graphic representation in Fig. 1. Once the optical system is near the Maréchal limit, the Zernike modes become orthogonal to each other with respect to the merit function. 2.IMAGE-BASED WAVEFRONT CORRECTIONOur image-based wavefront correction without wavefront sensing is a blind optimization of a merit function that evaluates the quality of the image of the science camera. The configuration parameters for the correction are: 1. the merit function, 2. the control domain, and 3. the algorithm. In this section we discuss our selection of the merit function (2.1) and of the control domain (2.2). The design of the algorithm is determined by these parameters but is outside the scope of this paper. 2.1Merit functionIt is often desirable to state the performance of an optical system by a single number. This immediately allows ranking of different optical systems, optimization of an optical system during its design, or finding the optimum state of an active or adaptive optics system. Examples of performance metrics that deliver a single numerical value are the Strehl ratio (S), the RMS wavefront error (σ), and image-sharpness metrics. Examples of performance metrics that deliver more than a single number, and thus contain more information, are the point spread function (PSF), the modulation transfer function (MTF), wavefront maps, and spot diagrams. Since all single-number performance metrics lack detailed information about the performance of an optical system, the question arises, which single-number metric is most suitable for a certain imaging scene (e.g., for Earth observation typical imaging applications are urban areas, forests, and maritime surveillance) and for a certain task (e.g. tracking fast moving objects), and what its limitations are. An image-based metric can be applied in different image regions and thus achieve optimal performance for different field angles. For example, when trying to resolve a double star, the region of interest will be a small region of the image. Thus the active optics should correct a narrow field of view. On the other hand, when observing star clusters and nebulas, a larger image region should be corrected, and the correction of the active optics should be balanced over a wide field of view. We use the image-sharpness metric S1 introduced by Muller and Buffington1. This is a single-number metric: S1: = ∫ I(x, y)2 dx dy, where I(x, y) is the irradiance at the point (x, y) of the image plane. Our merit function (MF) is a discretized adaptation of S1: In the above formula x and y are the axes of the image plane, Nx and Ny are the numbers of pixels in each axis, and I is the pixel value. The minus sign converts the sharpness maximization to a minimization problem. MF balances the influences from the contrast of all spatial frequencies. 2.2Control domainIn optical systems design, the optimization variables are parameters of the optical elements, e.g., material, diameter, thickness, surfaces’ curvatures, and position. Examining the performance of sets of values for all the parameters, the designer tries to optimize a merit function. In an adaptive optics system, the adaptive element offers additional degrees of freedom to compensate for aberrations. The optimization variables are the inputs of the adaptive element, i.e., the voltages of the electrodes for a deformable mirror or a spatial light modulator. But the relation of the voltages of a deformable mirror with the optical performance is complex. For this reason, we wish to transform the space of the voltages of the deformable mirror to wavefront shapes, which can be expressed, e.g., as Zernike modes. Assuming a linear deformable mirror†, this is done with the influence functions. Using the Zernike modes as variables, we gain insight into the optimization procedure and can possibly reduce the number of the variables in order to speed up the optimization. The Zernike modes used in this paper are listed in the Appendix. Having selected the merit function and the control domain, an algorithm to search the space of Zernike modes should be designed. 3.IMAGE SHARPNESS WHEN VARYING ZERNIKE MODES3.1Simulation methodWe simulate the pupil wavefront of an imaging system with a uniformly circular aperture in MATLAB over a 300 pixels × 300 pixels grid. We obtain the PSF by using the 2-D fast Fourier transform of the wavefront. We choose the width of the diffraction-limit PSF to be 40 pixels, significantly larger than the required width of 5 pixels, according to the Nyquist sampling theorem. To reduce the computational cost, we limit the total grid of the PSF to 1201 pixels × 1201 pixels, 30 times larger than the diffraction-limited PSF. The error caused by this truncation is negligible. Finally, we generate the MTF of the system by the 2-D fast Fourier transform of the PSF. We assume that the corrective active element is placed in a plane conjugate to the pupil and that it is controlled with Zernike modes. We normalize the aberrated PSFs to the maximum of the diffraction-limited PSF, to allow comparison among PSFs with different aberrations. Throughout the paper we use the Zernike notation of Wyant and Creath3. We call Zi the i-th Zernike mode and Zi its coefficient. 3.2RMS wavefront error and Strehl ratioThe RMS wavefront error (σ) is a common merit function in optical systems design. For small aberrations, the RMS wavefront error is directly related to the Strehl ratio and to the modulation transfer function (MTF). Maréchal formulated the following relation with the Strehl ratio: S ≈ [1 − 2π2σ2/λ2]2, where λ is the wavelength. Shannon formulated an empirical formula with the MTF4: MTF(ν) = DTF(ν){1 − (σ/0.18)2[1 − 4(ν − 0.5)2]}, where ν is the normalized spatial frequency and DTF(ν) the diffraction-limited MTF. The Zernike modes are balanced with respect to the RMS wavefront error for every aberration. Therefore, for small aberrations, the Zernike modes are also balanced with respect to the Strehl ratio and to the MTF. This means that, as long as the total aberration is sufficiently small, adding any aberration to the wavefront leads to deterioration of all image quality metrics: increase of the RMS wavefront error, decrease of the Strehl ratio, and decrease of the MTF for all spatial frequencies. For large aberrations, the Strehl ratio and the MTF can be multiple-valued for the same RMS wavefront error5,6. Higher RMS wavefront error may thus lead to lower or higher Strehl ratio depending on the aberration modes contributing to the aberration. The same is also true for the MTF4. The term “large aberrations” commonly refers to σ > λ/4 or S < 0.4. To illustrate the complex relation between the RMS wavefront error and the Strehl ratio for large aberrations, we calculate them when defocusing (Zernike mode Z3) in the presence of different values of astigmatism 0° (Zernike mode Z4) and show the results in Fig. 2. The RMS wavefront error (Fig. 2a) increases monotonically when the aberration increases, because the Zernike modes are balanced with respect to the RMS wavefront error. On the other hand, the Strehl ratio (Fig. 2b) decreases monotonically for increasing |z3| only as long as z4 ≤ 0.4λ (dark blue, orange and yellow curves). For z4 ≥ 0.6λ (violet, green and light blue curves), the Strehl ratio has two maxima away from z3 = 0. The multiple-valued Strehl ratio with respect to the RMS wavefront error is shown in Fig. 2c for σ > 0.2λ. 3.3Merit function for combinations of Zernike modesWe recently showed7 that for large aberrations the Zernike modes are not orthogonal to each other with respect to the merit function defined by (1). Here, we further explore this dependence by running simulations for combinations of two Zernike mode aberrations. Incoherent images of extended objects can be generated by the 2-D convolution of an extended object and the PSF. Using an extended object would restrict the validity of the results in the spatial frequencies that are present in the object. However, the PSF contains all spatial frequencies and can be used to draw conclusions for every spatial frequency that may be present in the object. Therefore, we calculate the merit function for the 1201 pixels × 1201 pixels image of the PSF. The combinations of Zernike modes shown in this paper are characteristic examples to investigate the physical causes for the non-orthogonality of the Zernike modes with respect to the merit function. To this end, we use wavefront maps, the PSF, and the MTF. In section 3.3.1 we discuss the combination of defocus (Z3) and astigmatism 0° (Z4). In section 3.3.2 we discuss the combination of astigmatism 0° (Z4) and secondary astigmatism 0° (Z11), as an example for the combination of Zernike modes with the same azimuthal order. The next two sections discuss combinations of trefoil 0° (Z9): the section 3.3.3 with coma x (Z6), and the section 3.3.4 with astigmatism 0° (Z4). The global minimum (optimum) of the merit function is for zero aberration, as expected, in all cases. We show that for large aberrations, the merit function can be improved by adding a Zernike mode, despite the fact that this increases the RMS wavefront error. 3.3.1Defocus and astigmatismFigure 3 shows our merit function calculated for the PSF under the same conditions as in Fig. 2, that is when defocusing in the presence of different values of astigmatism 0°. The merit function has a single minimum at z3 = 0 as long as z4 ≤ 0.2λ, but has two minima for opposite values of z3 when z4 ≥ 0.4λ. Although the progression of the curve resembles that of the Strehl ratio (Fig. 2b), it is different, because the Strehl ratio is just the maximum of the PSF, i.e., the value at a single point, whereas the merit function takes into account the whole PSF. We examine two aberrations, marked as “Aberration 1” and “Aberration 2” in Fig. 3. They both have z4 = 0.6λ. Aberration 2 has additional defocus z3 = 0.3λ and lower (better) merit function than aberration 1. Figure 4 shows the wavefront maps, the PSF and the MTF for these aberrations. The Zernike modes of defocus (Z3) and astigmatism 0° (Z4) contribute to the first-order field-independent aberration of focus3: . If only Z3 and Z4 exist in the system, the first-order field-independent focus becomes zero when |z3| = z4/2, the ratio of the coefficients for the aberration 2. Then the system suffers only from first-order field-independent astigmatism (W22). Adding defocus of |z3| = z4/2 in the presence of astigmatism 0° slightly increases the width of the PSF in one axis of the image plane (the axis x for the aberration 2). This leads to deterioration of the contrast and of the resolution for spatial frequencies oriented in the direction of this axis. At the same time, this significantly shrinks the PSF in the other axis of the image plane, leading to diffraction-limited contrast and resolution for spatial frequencies oriented in the direction of that axis (the axis y for the aberration 2). This principle is applied to astigmatic systems which are focused differently depending on the object. 3.3.2Zernike modes with the same azimuthal orderIn our recent publication7, we showed that for large aberrations the Zernike modes for defocus (Z3) and spherical aberration (Z8) are not orthogonal to each other with respect to the merit function. Here, we show another example for combination of Zernike modes with the same azimuthal order, Z4 and Z11, i.e., the Zernike modes for astigmatism 0° and secondary astigmatism 0°, both of azimuthal order of +2. Figure 5 shows the merit function calculated for the PSF, when varying z4 in the presence of different values of z11. For z11 = 0 there is a single minimum for the merit function at z4 = 0. For z11 > 0 the global minimum shifts towards positive values of z4. Due to our step size for the Zernike coefficients, we first resolve this shift of the global minimum when z11 = 0.4λ (yellow curve). In Fig. 6 we examine the aberrations marked as “Aberration 1” and “Aberration 2” in Fig. 5. Both have z11 = 0.6λ (violet curve), but aberration 2 has additional astigmatism 0° z4 = 0.6λ and lower (better) merit function than aberration 1. The addition of astigmatism 0° increases the wavefront deviation at the edges of the aperture, but smoothens the wavefront in the central part. This becomes obvious in Fig. 7 that shows the wavefront profiles for the aberrations 1 and 2 along the red dotted lines in Fig. 6. The wavefront with only secondary astigmatism 0° (aberration 1) has smaller variance, but the addition of astigmatism 0° (aberration 2) leads to a flatter wavefront in the central region of the aperture. We can calculate the Zernike modes over a smaller radius. Using the formulas for scaling the Zernike modes from the aperture where they are defined (radius r) to a smaller radius8, we find that for the aberration 2 there exists a radius r′ = 0.86r on which . On this radius the scaled Zernike modes comprise only . For comparison, for the aberration 1 the scaled Zernike modes on the radius r′ comprise and . The calculations are shown in the Appendix. In the image plane, the relative heights of the side lobes of the PSF decrease from 41% to 13%. Consequently, energy is squeezed into the central lobe, slightly increasing its width but also increasing its peak (the Strehl ratio). The narrower central lobe of the PSF for the aberration 1 can be interpreted as a higher resolution limit. This is valid, provided that the detection routine doesn’t misinterpret the side lobes (with 41% relative height) as distinct objects. Finally, the MTF for the aberration 1 falls fast for low spatial frequencies until 30% of the diffraction-limited cutoff frequency (νcut) and rises again with a peak near the diffraction-limited contrast at about 50% of the νcut. The MTF for the aberration 2 is in general smoother and achieves better contrast at low and mid spatial frequencies. 3.3.3Trefoil and comaThe Zernike mode of trefoil 0° is Z9 = ρ3 cos(3ϑ) = 4ρ3 cos3 ϑ − 3ρ3 cos ϑ. The first term (4ρ3 cos3 ϑ) is the fifth-order aberration of trefoil. The second term (3ρ3 cos ϑ) is the third-order coma (neglecting the field dependence) and is added to make the Zernike mode orthogonal to the lower order modes on the unit circle and to minimize the RMS wavefront error. The fifth-order aberration ρ3 cos3 ϑ (neglecting the field dependence) is called “trefoil” when studying the wavefront. It is also called “elliptic coma”, based on the image plane intensity: the circles that appear in the image spot for third-order coma turn into ellipses when fifth-order aberration of trefoil is added9,10. This relation between trefoil and coma is revealed when we vary the Zernike coma x (Z6) in the presence of different values of Zernike trefoil 0° (Z9). Figure 8 shows the merit function calculated for the PSF. For z9 ≤ 0.2λ there is a single minimum for the merit function at z6 = 0. For z9 > 0.4λ the global minimum shifts towards positive values of z6. In Fig. 9 we examine the aberrations marked as “Aberration 1” and “Aberration 2” in Fig. 8. They both have z9 = 0.8λ, but aberration 2 has additional coma x z6 = 0.7λ and lower (better) merit function than aberration 1. Adding positive coma x in the presence of trefoil 0° (aberration 2) makes the wavefront resemble to a single ripple in the u axis. The wavefront is practically uniform in one axis, the v axis of the coordinate system of the aperture. The wavefront actually becomes completely independent of v when z6 = z9, in which case the wavefront is W = z9(4u3 − 2u) and two of the three ripples of the wavefront vanish. In the image plane, adding coma x increases the Strehl ratio and shrinks the PSF, for both x and y axes. The PSF width in the y axis decreases until the diffraction-limited width. Finally, at the cost of the contrast reduction for low spatial frequencies oriented in the x axis, the MTF increases at mid and high frequencies for spatial frequencies oriented in both x and y axes. It even reaches the diffraction limit MTF for spatial frequencies oriented in the y axis in the case of positive coma x of the same magnitude as the trefoil 0° (z6 = z9). 3.3.4Trefoil and astigmatismApart from “trefoil” and “elliptic coma”, the fifth-order aberration ρ3 cos3 ϑ (neglecting the field dependence) is also called “triangular astigmatism” in part of the literature10. This is connected to the image plane intensity: in the presence of third-order astigmatism adding fifth-order aberration of trefoil turns the image spot into a triangle. This motivated us to research the combination of the Zernike modes of astigmatism and trefoil. We varied the trefoil 0° (Z9) in the presence of different values of astigmatism 0° (Z4) and show the merit function calculated for the PSF in Fig. 10. For z4 ≤ 0.2λ there is a single minimum for the merit function at z9 = 0. For z4 ≥ 0.6λ two equal minima appear, for opposite values of z9. In Fig. 11 we examine the aberrations marked as “Aberration 1” and “Aberration 2” in Fig. 10. They both have z4 = 0.6λ, but aberration 2 has additional trefoil 0° z9 = 0.4λ and lower (better) merit function than aberration 1. The addition of trefoil 0° partially compensates the ripple caused by the astigmatism 0° at one half of the aperture. For the aberration 2 with positive trefoil 0°, it’s the left half of the aperture (π/2 ≤ θ ≤ 3π/2, negative u). The wavefront aberration is W = z4Z4 + z9Z9 = (z4 + z9u)(u2 − υ2) − 2z9uυ2 and its v-derivative is 𝜕W/𝜕υ = − 2υ(z4 + 3z9u). We notice that for u = ±0.5, the v-dependence of the wavefront vanishes when z4/z9 = ∓3/2. This is equal to the ratio of the Zernike coefficients of Z4 and Z9 for the aberration 2 (0.6λ/0.4λ). In the image plane, the PSF shrinks and its peak intensity increases. Ripples with relatively small peaks appear, the highest being 17% of the peak intensity. Finally, the MTF with additional trefoil 0° is slightly lower for spatial frequencies up to about 25% of the νcut, but is significantly higher for mid spatial frequencies between 25% and 70% of the νcut. This leads to higher resolution. Setting the limiting resolution at about 10% contrast, the cutoff frequency is about 0.3νcut for z4 = 0.6λ (aberration 1) and increases to 0.5νcut by adding trefoil 0° . 4.CONCLUSIONSWe have shown that for aberrations of more than λ/8 RMS the Zernike modes are not orthogonal to each other with respect to the common image-sharpness metric of Muller and Buffington1. The non-orthogonality of the Zernike modes should be taken into account when designing the algorithm for image-based wavefront correction, because it may slow down the process or lead to premature convergence. If the algorithm optimizes the Zernike modes separately, several iterations over all Zernike modes are required to ensure that the global minimum is found. We discussed several combinations of two Zernike modes and investigated the physical causes for their non-orthogonality using wavefront maps, the PSF, and the MTF. We found that in certain cases when adding a Zernike mode, the merit function is improved, although the RMS wavefront error increases. In all the examples we discussed, the improvement of the merit function comes with an increase of the Strehl ratio. However, we cannot directly connect the merit function to the improvement of contrast at a certain range of spatial frequencies. In section 3.3.2 we have shown that for combinations of Zernike modes with the same azimuthal order, a flatter wavefront in the central region of the aperture is more important than the RMS wavefront error across the full aperture for achieving a low (good) merit function. The results indicate that although the RMS wavefront error is an important metric for image quality, it can be misleading, especially for optical systems with several λ of aberration and low Strehl ratio. In this case, image-based active optics can improve the image quality by adding a low-order Zernike mode to partially compensate an uncorrectable higher-order Zernike mode. An example was discussed in section 3.3.2, where secondary astigmatism 0° (Z11) was partially compensated by adding astigmatism 0° (Z4). This improved the merit function by 58% and the Strehl ratio by 33%, although the RMS wavefront error increased by 63%. ACKNOWLEDGMENTSThis work is supported by the funding programme “Qualifizierungsstelle” of Münster University of Applied Sciences. REFERENCESMuller, R. A. and Buffington, A.,
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APPENDIXSome low-order Zernike modes
*In the text the Cartesian coordinates of the aperture are (u, υ). (x, y) are the Cartesian coordinates in the image plane. Scaling Zernike modes in smaller apertures (according to [8])with reference to Fig. 6 zi is the coefficient of the i-th Zernike mode in the aperture r is the coefficient of the i-th Zernike mode in the aperture r′ < r Aberration 2: z4 = 0.6λ and z11 = 0.6λ. To find the radius r′ on which the scaled is zero: The scaled on the radius r′ is: Aberration 1: z4 = 0 and z11 = 0.6λ. The scaled Zernike modes on the radius r′ are: Notes[2] Deformable mirrors often employ actuators which suffer from hysteresis, e.g., piezoelectric actuators. Hysteresis can be eliminated in closed-loop operation with a wavefront sensor. If no wavefront sensor is used, hysteresis can be reduced by using a nonlinear model. The control algorithm should cope with the residual hysteresis, caused by modelling errors2. |