Lens System Optimization with reTORT Ray Tracer

Lens System Optimization Covariance Matrix Adaptation Evolution Strategy

Lens system optimization is the ultimate goal in any design. To this end, reTORT offers wizards for fast setups. In this way, with a single click, you select built-in optimization goal selections.

reTORT ray tracer uses two different approaches to optimization. This aids in reaching your objective and matching your desired workflow. These two approaches are a local gradient based method and a global optimization method.

Local optimization uses the traditional damped least squares algorithm. Our local optimization uses finite differencing to determine the gradients of each optimized lens parameter. These parameters may include lens curvature, thickness, air gap or a GRIN lens property. Then, the optimizer exports the gradients to the damped least squares optimizer.

Our global optimization is based on a genetic algorithm. We use the covariance matrix adaptation evolution strategy. But let’s just call this CMAES from now on, okay?

CMAES uses an evolutionary strategy to fully explore the problem space. Hence, it is truly global. It will find a global minimum during optimization. Therefore, it does not get stuck in a local minima.

This article on evolution strategies gives a plain language explanation. It includes a section on CMAES. This source often uses cute graphics to explain it’s point. You can see a visual of getting stuck in a local minima right here.

Global optimization - getting stuck in a local minima

Lens System Optimization Setup

We offer a handy optimization wizard setup. Our wizard allows minimum and maximum ranges to be set for individual variables. Pickups and other solves are easy to configure.

Here’s a typical example.

optimization wizard

In fact, here is a screenshot of the reTORT ray tracer wizard’s parameter solve interface.

reTORT ray tracer wizard’s parameter solve interface CMAES ray tracer
reTORT ray tracer wizard’s parameter solve interface CMAES ray tracer

You also have granular control of each optimization goal. The designer, that is you, can control how focal metrics are computed. Whether to do lateral color correction is your decision. And, you have control over secondary goals such as lens center and edge thicknesses.

The two primary optimization goals are minimize spot size and minimize wavefront error. Note this screenshot setting up a spot size optimization.

optimization goals are minimize spot size and minimize wavefront error ray tracer CMAES
optimization goals are minimize spot size and minimize wavefront error ray tracer CMAES

E x H reTORT ray tracer gives you tremendous flexibility and options for your lens system optimization. Damped least squares is a tried and true local optimizer method. And, the E x H implementation of CMAES has produced superior results time and again.

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About E x H, Inc.

Our mission is to provide you with advanced simulation tools. These tools allow you to design optical and RF systems that are smaller, lighter, faster and have greater clarity than ever before.

We license some of our solvers from Penn State University. PSU’s world reknowned Computational Electromagnetics and Antennas Research Laboratory. have developed these solvers.

CEARL has educated many of our scientists and engineers.

We have also participated on multiple programs funded by DARPA as well as other sectors of the Department of Defense.

On the business side, we have been backed by Gran Sasso Ventures, the same venture capitalists that funded collaboration software firm Compoze Software, now a part of Oracle [ORCL:NYSE], and multitouch technology inventor FingerWorks, the driver of touch screen technology and now a part of Apple [AAPL:NASDAQ].

E x H is at the forefront of transformation optics.

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