Abstract
We present an analytic methodology to guide the selection of a surface within an optical design to apply freeform optimization. The methodology is discussed in the context of other means currently available, such as human intuition, aberration theory, and other direct surface construction methods. We describe the selection criteria for our proposed method and provide the form of the parametric fitness function used to combine the criterion. Finally, a case study comparing a design optimization procedure guided by the proposed methodology to human intuition is presented based on a real instrument designed for a millimeter-wave astronomy application. The methodology is shown to be effective even in the case of an optical system with a large number of freeform/optical surfaces. The proposed approach provides an objective and scalable solution to guide freeform optical system design by aiding a human's design intuition.
Highlights
Freeform optics are revolutionizing the capabilities of optical systems with applications across the entire optical design spectrum [1]
The ray data is composed of a location and direction in three dimensions, where typically the location is expressed in Cartesian coordinates (x, y, z) and the direction is given by the direction cosines (L, M, N)
The ray direction vector is a unit vector given by the direction cosines (L, M, N), which leads to the vector Hì = L x + M y + N zwhose magnitude H = 1
Summary
Freeform optics are revolutionizing the capabilities of optical systems with applications across the entire optical design spectrum [1]. In the space of freeform optical design, methods to directly generate a starting configuration from a set of planes have been developed [8,9,10]. Further methods develop the surface in a step-by-step method, growing the FOV and the surface [13] Another method defines a construction technique to generate the geometry and power distribution in a design optimally suited for freeform optimization [14]. Aberration theory may be used to determine which surface limits the optical performance and which freeform terms to apply, or even to determine the initial system design [15]. We present a parametric numerical alternative methodology to guide the process of choosing an optimal surface in an existing design to optimize into a freeform optic. Some commercial software provide similar or limited features, but the methodology and specifics are trade-secrets
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