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Analytic-Domain Lens Design with Proximate Ray Tracing

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Analytic-Domain Lens Design with Proximate Ray Tracing Zheng et al. Vol. 27, No. 8/August 2010/J. Opt. Soc. Am. A 1791 Analytic-domain lens design with proximate ray tracing Nan Zheng,1 Nathan Hagen,2,* and David J. Brady2,3 1Department of Physics, Duke University, Durham, North Carolina 27708, USA 2Department of Electrical and Computer Engineering, Fitzpatrick Institute for Photonics, Duke University, Durham, North Carolina 27708, USA 3E-mail: [email protected] *Corresponding author: [email protected] Received February 17, 2010; revised June 3, 2010; accepted June 5, 2010; posted June 7, 2010 (Doc. ID 124169); published July 14, 2010 We have developed an alternative approach to optical design which operates in the analytical domain so that an optical designer works directly with rays as analytical functions of system parameters rather than as dis- cretely sampled polylines. This is made possible by a generalization of the proximate ray tracing technique which obtains the analytical dependence of the rays at the image surface (and ray path lengths at the exit pupil) on each system parameter. The resulting method provides an alternative direction from which to ap- proach system optimization and supplies information which is not typically available to the system designer. In addition, we have further expanded the procedure to allow asymmetric systems and arbitrary order of approxi- mation, and have illustrated the performance of the method through three lens design examples. © 2010 Op- tical Society of America OCIS codes: 080.2740, 080.6755, 220.3620. 1. INTRODUCTION generalization which is made possible through the power The design of an optical system typically proceeds with of modern computer algebra systems [9] to manipulate the use of a modern computer program for performing ex- large analytical equations. act ray tracing. The user first models the optical layout In its original form, proximate ray tracing involves first and constructs a merit function, after which the program analytically calculating the formulas for transfer and re- uses ray trace data to minimize the merit function by ad- fraction at each polynomial order of approximation. A ray justing the system parameters. The most common optimi- trace then involves calculating the numerical values of zation algorithm used is damped least-squares [1], which the ray-surface intersection point at each surface, at each is fast but has the drawback that it is limited to finding order of approximation. The procedure was thus devel- only local minima. If the starting optical configuration is oped as an efficient method of numerically calculating far enough from the global minimum, and the merit func- higher-order aberration coefficients, and it requires trac- tion is complicated enough to possess a number of local ing only a small set of special rays to obtain the aberra- minima (as in almost all cases of interest), then the tion coefficient values. The generalization we present chance of converging on the global solution quickly ap- here extends proximate ray tracing’s analytical approach proaches zero. Global optimization techniques [2] such as to the entire design process, without numerical substitu- simulated annealing [3] or genetic algorithms [4] can of tion. Thus, rather than obtaining analytical formulas for course get around this problem, but require extensive each individual refraction and transfer step in the trace, computational resources [5]. While it is possible to mini- we obtain a single formula for the rays at the image plane mize the computational effort needed by providing the al- (and exit pupil). We can thus obtain the aberration coeffi- gorithm with a starting configuration which is as close as cients in analytical form, in which the functional depen- possible to the global solution, thereby minimizing the dence of the lens merit function on the system parameters search space, the method for doing this relies heavily on is retained. The aim is to show that with the aid of mod- the intuition of the designer and on tools developed in ern computer algebra systems, optical design problems classical aberration theory (such as aberration cancella- that are currently performed numerically can also be tion in symmetric systems). done in the analytical domain, and that this can have sig- We present what we believe to be a new design tool nificant advantages for understanding the design prob- which approaches the problem from a different direction, lem. and thus may be helpful in situations where traditional A closely related approach for analytical ray tracing tools get stuck: a ray tracing engine that provides the ex- was taken by Kondo and Takeuchi [10] through the use of pression for the rays, to any desired polynomial order of matrices and the selection of a proper vector basis for approximation, as an analytical function of the system pa- modeling the nonlinear effects present in ray tracing (up rameters. The approach is a generalization of the proxi- to the desired order of approximation). While similar to mate ray tracing method developed by Hopkins [6–8]—a the approach presented here, it lacks the conceptual sim- 1084-7529/10/081791-12/$15.00 © 2010 Optical Society of America 1792 J. Opt. Soc. Am. A/Vol. 27, No. 8/August 2010 Zheng et al. plicity of proximate ray tracing, and thus we feel that it is taken to be the optical axis, and multiplying w by the re- a much more cumbersome tool to work with. That is, for fractive index n of the medium gives the ray optical path many optical engineers, the concept of equating terms of length. The refraction equations can be written as [[17], p. like order in the Taylor expansion of a nonlinear equation 133] is a much more familiar process than that of constructing ͑ ϫ ͒ Ј͑ Ј ϫ ͒ ͑ ͒ a nonorthogonal vector basis in which to represent a non- n c N = n c N , 2 linear transformation. This conceptual simplicity becomes where N=͑Nx ,Ny ,Nz͒ is the normal vector of the surface, important for understanding what to do with the large set and of polynomial terms generated by either approach. ١f͑r͒, ͑3͒ = Kondo and Takeuchi’s matrix approach was modified by N Lakshminarayanam and Varadharajan [11], and also by ͑ ͒ Almeida [12], and adapted for use in a computer algebra when f r =0 defines the surface. Note that the optical system [13], but published work has been limited to opti- path length of a ray through the entire system is given by ͚S−1 cal modeling rather than design, in that it does not treat W= s=1 nsws when ws is the ray path length for transfer the merit function or the optimization procedure. This from surface s to s+1. misses one of the central strengths of working in the ana- The first step in the proximate ray trace procedure is to lytical domain: the tractability of polynomial equations expand all of the relevant variables in the transfer and re- allows the use of more robust optimization techniques. fraction equations in various orders of approximation. Other attempts at analytical ray tracing have also been Thus, each ray trace variable is expressed in the form made. Walther [14,15] developed an analytical approach x =0+x͑1͒ + x͑2͒ + x͑3͒ + x͑4͒ + , which makes use of eikonals rather than rays and is thus ¯ ´ less accessible for many optical engineers. Kryszczynski ͑1͒ ͑2͒ ͑3͒ ͑4͒ [16] provided some tentative steps toward analytical de- y =0+y + y + y + y + ¯ , sign based on rays, but only supplies an outline of an al- ͑0͒ ͑1͒ ͑2͒ ͑3͒ ͑4͒ gorithm. Although it may at first appear mathematically z = z + z + z + z + z + ¯ , complex, we hope to show that the proximate ray tracing method makes the analytical approach both accessible ͑1͒ ͑2͒ ͑3͒ ͑4͒ cx =0+cx + cx + cx + cx + ¯ , and practical. In the discussion below, we first review Hopkins’ ͑1͒ ͑2͒ ͑3͒ ͑4͒ method [6–8] and show how it can be readily generalized cy =0+cy + cy + cy + cy + ¯ , to arbitrary orders of approximation and to asymmetric ͑1͒ ͑2͒ ͑3͒ ͑4͒ systems. We then show how to construct the merit func- cz =1+cz + cz + cz + cz + ¯ , tion and optimizer for designing optical systems with this approach and present three example designs. Finally, we ͑0͒ ͑1͒ ͑2͒ ͑3͒ ͑4͒ ͑ ͒ w = w + w + w + w + w + ¯ . 4 conclude with a discussion of the advantages and disad- vantages of this technique. The superscripts in parentheses indicate the order of ap- proximation so that the first nonzero term on the right hand side of each of these equations represents a paraxial 2. TRANSFER variable, and succeeding terms represent the nonlinear Hopkins [6–8] described proximate ray tracing as an it- dependence on the paraxial variables. The term z͑0͒ rep- erative ray tracing technique in algebraic form. The basic resents the axial transfer distance from the surface vertex approach is to the previous surface (and is thus a negative quantity for rays propagating from left to right). 1. A polynomial series expansion for basic and inter- The primary variables used to define the rays, the en- mediate variables are inserted into the exact ray trace trance pupil coordinates ͑x ,y ͒ and the field angles equations. ep ep ͑␪ ,␪ ͒, are treated as paraxial variables and thus do not 2. Any sines and cosines are series-expanded, and any x y have an order-expansion. The final expressions for the multiplications, divisions, and square roots are performed rays will give the image coordinates in terms of these pri- as series operations. mary variables and of the parameters used to define each 3. Terms of a given order are collected together, and surface. In aberration theory it is more common to work higher-order terms are obtained using lower-order solu- with normalized field angles H, defined either as tions via a triangular set of equations.
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