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1 Simplified Method of Modeling Complex Systems of Simple Optics using Wave-Optics: An Engineering Approach Dr. Justin D. Mansell, Steve.

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Presentation on theme: "1 Simplified Method of Modeling Complex Systems of Simple Optics using Wave-Optics: An Engineering Approach Dr. Justin D. Mansell, Steve."— Presentation transcript:

1 1 Simplified Method of Modeling Complex Systems of Simple Optics using Wave-Optics: An Engineering Approach Dr. Justin D. Mansell, Steve Coy, Liyang Xu, Anthony Seward, and Robert Praus MZA Associates Corporation

2 2 Outline Introduction –Ray Matrices –Lens Law –Fourier Optics Aperture Imaging Into Input Space Finding the Field Stop & Aperture Stop Mesh Determination for Complex Systems Conclusions

3 3 Ray Matrix Formalism

4 4 Introduction - ABCD Matrices The most common ray matrix formalism is the 2x2 or ABCD that describes how a ray height, x, and angle, θ x, changes through a system. θxθx x θ x x

5 5 2x2 Ray Matrix Examples Propagation Lens θxθx x x θxθx x θ x

6 6 Example ABCD Matrices Matrix TypeFormVariables PropagationL = physical length n = refractive index Lensf = effective focal length Curved Mirror (normal incidence) R = effective radius of curvature Curved Dielectric Interface (normal incidence) n 1 = starting refractive index n 2 = ending refractive index R = effective radius of curvature

7 7 3x3 and 4x4 Formalisms Siegmans Lasers book describes two other formalisms: 3x3 and 4x4 The 3x3 formalism added the capability for tilt addition and off- axis elements. The 4x4 formalism included two-axis operations like axis inversion and image rotation. E = Offset F = Added Tilt 3 x 3 4 x 4

8 8 5x5 Formalism We use a 5x5 ray matrix formalism as a combination of the 2x2, 3x3, and 4x4. –Previously introduced by Paxton and Latham

9 9 Lens Law This equation governs the location of the formation of an image. f d2d2 d1d1 objectimage

10 10 Huygens Principle In 1678 Christian Huygens expressed an intuitive conviction that if each point on the wavefront of a light disturbance were considered to be a new source of a secondary spherical disturbance, then the wavefront at any later instant could be found by constructing the envelope of the secondary wavelets. -J. Goodman, Introduction to Fourier Optics (McGraw Hill, 1968), p. 31.

11 11 Huygens-Fresnel Integral 1 2

12 12 Fresnel Approximation Fresnel found that in modeling longer propagations, –the cosine term could be neglected and –the spherical term could be approximated by a r 2 term. Huygens-Fresnel Integral Fresnel Approximation

13 13 Notation Simplification Quadratic Phase Factor (QPF): Equivalent to the effect a lens has on the wavefront of a field. Fourier Transform Multiplicative Phase Factor: Takes into account the overall phase shift due to propagation

14 14 Fresnel Approximation Validity radius spherical parabolic

15 15 Fresnel Approximation Validity Examples a (cm)z >> (π/4 a 4 /λ) 1/3 Goodman N f max m m m mm μm μm5 λ = 1.0 μm

16 16 Implementing Fourier Propagation One-Step Fourier Transform –Single Fourier integral Convolution Propagator –Short distances Two Cascaded One- Step Propagations –Longer distances

17 17 Discrete Sample Implementation When implementing Fourier propagation on a computer, the field is sampled at discrete points. The mesh spacing between samples (δ) and the number of mesh points (N) required for accurate modeling are discussed later. The mesh spacing can be different at the beginning of a propagation (δ 1 ) than at then end (δ 2 ) δ

18 18 Samples, Not Local Area Averages We represent the continuous wave with a series of samples, which is NOT a local average. This can be most easily shown by Fourier transforming a 2D grid of ones. The result is a single non-zero mesh point at the center of a mesh, but adding a guard- band shows that the single non-zero mesh point is really an under-sampled sine function x=1:1:128; x3=1:0.5:128.5; E = ones(1,128); E2 = fftshift(fft(fftshift(E))); E3 = fftshift(fft(fftshift(addGuardBand(E',1)))); figure; plot(x,E./max(E),'-o'); hold on; plot(x3,abs(E3)./max(abs(E3)),'g*-'); plot(x,E2./max(E2),'rx-'); zoomOut(0.1); Matlab Script

19 19 One-Step Fourier Propagator Steps: –Multiply by QPF –Fourier Transform –Multiply by QPF & Phase Factor Comments –Least computationally expensive –Offers no control over the resulting mesh spacing

20 20 Convolution Propagator Steps: –Fourier transform –multiplication by the Fourier transformed kernel –an inverse Fourier transform Advantage: –Maintains the mesh spacing

21 21 Two-Step Forward Propagator Steps: –Fourier Propagate Comments: –Easy to scale the mesh by picking intermediate plane location. –Works well in long propagation cases because the quadratic phase factor is applied before the Fourier transform z1z1 z2z2 δ1δ1 δ2δ2 δiδi

22 22 Scaling with the Convolution Propagator One drawback of the convolution propagator is its apparent inability to scale the mesh spacing in a propagation. Scaling the mesh is important when propagating with significant wavefront curvature. The convolution propagator can be modified to model propagation relative to a spherical reference wavefront curvature such that the mesh spacing can follow the curvature of the wavefront. We call this Spherical-Reference Wave Propagation or SWP.

23 23 Spherical Reference Wave Propagation 1/3 Consider convolution propagation with a built in wavefront curvature relative to the lens law. Based on imaging, light propagated through an ideal lens to a distance d1 will be the same shape as if it were propagated to a distance d2 where f -1 =d1 -1 +d2 -1 except for a magnification term. For example: a beam propagating 48 cm toward a focus through a 50cm lens. Based on the lens law, this is equivalent to propagating a 1200 cm without going through the focus. It is significantly easier to propagate 1200 cm than it is to propagate 48cm. f d2d2 d1d1 objectimage

24 24 Spherical Reference Wave Propagation 2/3 The real advantage of SWP is the ability to scale the mesh to track the evolution of the beam size. The spherical reference wave radius of curvature (R ref ) can be determined based on the desired magnification (M). z R ref δ1δ1 δ2δ2

25 25 Spherical Reference Wave Propagation 3/3 Procedure: –Specify desired magnification (M) and propagation distance (z) –Calculate effective reference curvature (R ref ) –Determine new effective propagation distance (z eff ) –Propagate the effective distance and then change the sample spacing by the magnification factor

26 26 Mathematical Comparison of Convolution & Double Propagation Convolution Propagator with SWPDouble Propagator With the SWP addition, the Double Propagator and the Convolution Propagator are equivalent.

27 27 Conclusions We use the convolution propagator in WaveTrain with spherical-reference wave propagation. This allows us to solve any general wave- optics problem.

28 28 Computer Modeling of Fourier Propagation

29 29 Computer Fourier Propagation Modeling In most situations, the most rapidly varying part of the field is the QPF. In a complex field, the phase is reset every wavelength or 2π radians. To achieve proper sampling, sampling theory dictates that we need two samples per wave. Adequate SamplingInadequate Sampling k = 1; R = 16; x = -63:1:64; p = exp(j*k* (x.^2)./ (2*R)); plot(angle(p),'b*-') Samples Phase (radians)

30 30 Methods of Determining Sampling Diffraction Limit Angular Bandwidth

31 31 Mesh Sampling: Whittaker-Shannon Theory We need 2 samples for each wave of amplitude. For a parabolic phase surface, this is most limiting at the edge of the phase surface. λ 2δ2δ

32 32 Mesh Sampling: Diffraction Diffraction is the fundamental limit of our ability to model propagation. If we assume we need 2 samples per diffraction spot radius on BOTH sides of a propagation, we get a maximum value for the mesh spacing. z D1D1 D2D2

33 33 Mesh Sampling: Angular Bandwidth D1D1 D2D2 z

34 34 Virtual Adjacent Apertures Now that we know the mesh sampling intervals (δ 1 and δ 2 ), we need to know how big a mesh we need to use to accurately model the diffraction. The Fourier transform assumes a repeating function at the input. –This means that there are effective virtual apertures on all sides of the input aperture. We need a mesh large enough that these virtual adjacent apertures do not illuminate our area of interest.

35 35 Mesh Size: Equal Sized Apertures To avoid adjacent apertures (D up and D down ) from interfering with the output area of interest, the modeled region should be D+θz in diameter. This means that the number of mesh points should be this diameter divided by the mesh spacing (δ). For equal apertures, this means a factor of two guard-band. D+θz DD z D up D down

36 36 Unequal Apertures For unequal apertures (such as spherical-reference wave propagation), the same geometric argument can be made. The resulting form can be thought of as the average of the number of mesh points required to cover each of the input apertures plus a diffractive term. If we set the two mesh spacings to their maximum value, the number of mesh points reduces to a familiar form: –the Fresnel number.

37 37 Fresnel Number The Fresnel number is –the number of half waves of phase of a parabolic wavefront over the aperture. –half the number of diffraction limited spots diameters over the aperture. –roughly the number of diffraction ripples across an aperture. z

38 38 Mesh Size and Fresnel Number For equal sized apertures, the number of mesh points equals 16 times the Fresnel number. For unequal apertures, the same is true if we define an effective Fresnel number as r 2 r 1 /λz. Equal Sized Apertures Unequal Sized Apertures

39 39 Summary of Mesh Determination Derived by either: –Diffraction limit OR –Required angular bandwidth Derived based on eliminating overlap between adjacent virtual apertures and the region of interest. Mesh Sample Spacing Mesh Size

40 40 Conclusions For a simple system of two limiting apertures, we have determined a set of inequalities that govern the choice of the mesh. Next we will look at –how phase aberrations impact the mesh choice, and –how this can be extended to a system of multiple apertures.

41 41 Impact of Phase Aberrations on Mesh Determination

42 42 Sinusoidal Phase Grating

43 43 Turbulence-Induced Aperture Blurring Turbulence acts to increase the size of the point spread function This effectively blurs the apertures at each end. The blurred apertures can be thought of as being larger if we want to capture most of the energy. Gaussian PSF Blurred Aperture

44 44 Blur Effect on Aperture Size Turbulence can be thought of as diffracting light as if it were sent through a grating with a period equal to r 0, which is Frieds coherence length. –r 0 can be though of as the characteristic turbule size. A scaling parameter, c turb, is used to control the amount of energy captured in the calculation. –c turb 4 is for 99% of the energy. Blurred Edge of a Hard Aperture

45 45 Procedure to Determine the Mesh while Considering Turbulence z D1D1 D2D2 1.Simplify the turbulence distribution along the path into effective r 0 values for each effective aperture. 2.Modify the aperture size using the effective r 0. 3.Use the new effective aperture sizes to determine the mesh. D 2 D 1

46 46 Determining Fourier Propagation Mesh Parameters for Complex Optical Systems of Simple Optics

47 47 Introduction The determination of mesh parameters for wave-optics modeling can be uniquely determined by a pair of limiting apertures separated by a finite distance. An optical system comprised of a set of ideal optics can be analyzed to determine the two limiting apertures that most restrict rays propagating through the system using field and aperture stop techniques.

48 48 Definitions of Field & Aperture Stop Aperture Stop = the aperture in a system that limits the cone of energy from a point on the optical axis. Field Stop = the aperture that limits the angular extent of the light going through the system. NOTE: All this analysis takes place in ray- optics space.

49 49 Example System f= D=15 D=5 L1 L L2 L1 A2 A1 A2 A1 D=1 Input Space Optical System Plane 2 Plane 3Plane 4Input

50 50 Procedure for Finding Stops 1/3 1.Find the location and size of each aperture in input space. 1.Find the ABCD matrix from the input of the system to each optic in the system. 2.Solve for the distance (z image ) required to drive the B term to zero by inverting the input-space to aperture ray matrix. This matrix is the mapping from the aperture back to input space. 3.The A term is the magnification (M image )of the image of that aperture.

51 51 Procedure for Finding Stops 2/3 2.Find the angle formed by the edges of each of the apertures and a point in the middle of the object/input plane. The aperture which creates the smallest angle is the image of the aperture stop or the entrance pupil L2 L1 A2 A1

52 52 Procedure for Finding Stops 3/3 2.Find the aperture which most limits the angle from a point in the center of the image of the aperture stop in input space. This aperture is the field stop L2 L1 A2 A1

53 53 Example: Fourier Propagation L2 L1 A2 A1 Input Space D1 = 1 mm, D2 = 15 mm, λ = 1 μm, z = 0.15 m Minimal Mesh = 400 x μm = 3.75 mm

54 54 Example System f= D=15 D=5 L1 L2 A2 A1 D=1 Optical System Plane 2 Plane 3Plane 4Input

55 55 N=1024, δ=6.6 μm Plane 2Plane 3Plane 4Input Over-Sampled

56 56 N=512, δ=9.4 μm Plane 2Plane 3Plane 4Input Minimal Sampling

57 57 N=256, δ=13.3 μm Plane 2Plane 3Plane 4Input Under Sampled

58 58 Conclusions of Complex System Mesh Parameter Determination We have devised a procedure to reduce a complex system comprised of simple optics into a pair of the most restricting apertures. It would be nice to have a way of simplifying a complex system of simple optics so that modeling it is computationally easier…

59 59 ABCD Ray Matrix Wave-Optics Propagator

60 60 Implementation Options Siegman combined the ABCD terms directly in the Huygens integral. He then also introduced a way of decomposing any ABCD propagation into 5 individual steps.

61 61 Polishing the Siegman Decomposition Algorithm We found that one of the magnification terms was unnecessary (M 1 =1.0). Siegmans algorithm did not address two important situations: image planes and focal planes. We worked a bit more on how to pick an appropriate magnification when considering diffraction.

62 62 Siegman Decomposition Algorithm Choose magnifications M 1 & M 2 (M=M 1 *M 2 ) Calculate the effective propagation length and the focal lengths.

63 63 Eliminating a Magnification Term We determined that one of the two magnification terms that Siegman put into his decomposition was unnecessary. –There were five unknowns and four inputs.

64 64 Image Plane: B=0 This case is an image plane. There is no propagation involved here, but there is –curvature and –magnification. SiegmanOur Algorithm

65 65 Focal Plane Case We were trying to automate the selection of the magnification by setting it equal to the A term of the ABCD matrix. –This minimizes the mesh requriements In doing so, we found that the decomposition algorithm was problematic at a focal plane. Siegman, M=A

66 66 Propagation to a Focus: A=0 Siegman, M=1Siegman, M=A For a collimated beam going to a focus, this ray envelope diameter is zero. To handle this case, we augmented the magnification determination with diffraction.

67 67 Choosing Magnification while Considering Diffraction We propose here to add a diffraction term to the magnification to avoid the case of M=0. We added a tuning parameter, η, which is the number of effective diffraction limited diameters. We leave the selection of magnification to the user.

68 68 Common Diffraction Patterns Airy Sinc Gaussian Normalized Intensity Normalized Radius

69 69 Integrated Energy Threshold = Airy Sinc Gaussian Integrated Energy η We concluded that η=5 is sufficient to capture more than 99% of the 1D integrated energy.

70 70 Modified Decomposition Algorithm If at an image plane (B=0) M=A (possible need for interpolation) Apply focus Else Specify M, considering diffraction if necessary Calculate and apply the effective propagation length and the focal lengths.

71 71 Implementing Negative Magnification After going through a focus, the magnification is negated. We implement negative magnification by inverting the field in one or both axes. –We consider the dual axis ray matrix propagation using the 5x5 ray matrix formalism.

72 72 Dual Axis Implementation In our implementation, we handle the case of cylindrical telescopes along the axes by dividing the convolution kernel into separate parts for the two axes.

73 73 Example: ABCD Propagator

74 74 Example System 2f D f f/2

75 75 Magnitude z=2f before lensz=2f after lensz=2.5f z=3fz=3.5fz=4f

76 76 Unwrapped Phase z=2f before lensz=2f after lensz=2.5f z=3fz=3.5fz=4f

77 77 ABCD Ray Matrix Fourier Propagation Conclusions We have modified Siegmans ABCD decomposition algorithm to include several special cases, including: –Image planes –Propagation to a focus This enables complex systems comprised of simple optical elements to be modeled in 4 steps.

78 78 Questions? (505) x122

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