Tailored freeform surfaces for illumination with extended sources

Muschaweck, Julius

doi:10.1117/12.2632439

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…It is currently solved by numerically solving system-specific differential equations or through optimization, with every step validated using a (non-differentiable) non-sequential ray tracer (Wu et al, 2018). Great effort is involved in generalizing these methods to account for varying amounts of optical surfaces (Anthonissen et al, 2021), their optical surface and volume properties (Kronberg et al, 2022;Lippman and Schmidt, 2020), or the source model (Muschaweck, 2022;Tukker, 2007;Sorgato et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Gradient descent-based freeform optics design using algorithmic differentiable non-sequential ray tracing

Koning¹,

Heemels²,

Adam³

et al. 2023

Preprint

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Algorithmic differentiable ray tracing is a new paradigm that allows one to solve the forward problem of how light propagates through an optical system while obtaining gradients of the simulation results with respect to parameters specifying the optical system. Specifically, the use of algorithmically differentiable non-sequential ray tracing provides an opportunity in the field of illumination design. We demonstrate its potential by designing freeform lenses that project a prescribed irradiance distribution onto a plane. The challenge consists in finding a suitable surface geometry of the lens so that the light emitted by a light source is redistributed into a desired irradiance distribution. We discuss the crucial steps allowing the non-sequential ray tracer to be differentiable. The obtained gradients are used to optimize the geometry of the freeform, and we investigate the effectiveness of adding a multi-layer perceptron neural network to the optimization that outputs parameters defining the freeform lens. Lenses are designed for various sources such as collimated ray bundles or point sources, and finally, a grid of point sources approximating an extended source. The obtained lens designs are finally validated using the commercial non-sequential ray tracer LightTools.

show abstract

Section: Introductionmentioning

confidence: 99%

Gradient descent-based freeform optics design using algorithmic differentiable non-sequential ray tracing

Koning¹,

Heemels²,

Adam³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…One common assumption to solve the problem is to design for zero-étendue sources, such as point sources or highly collimated sources, e.g., lasers. This assumption in most practical applications is too strict as the size or divergence of the actual source is not negligible, and hence we have to design for a finite étendue source [7][8][9][10]. However, when solving this problem for finite étendue sources, there is no guarantee that the desired irradiance distribution is realizable with the given source.The issue of realizing an irradiance distribution with high spatial details with a finite étendue source can be discussed in terms of the resolution limits of freeform optical elements [11].…”

Section: Introductionmentioning

confidence: 99%

Limits of realizing irradiance distributions with shift-invariant illumination systems and finite étendue sources

2023

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When redistributing the light emitted by a source into a prescribed irradiance distribution, it is not guaranteed that, given the source and optical constraints, the desired irradiance distribution can be achieved. We analyze the problem by assuming an optical black box that is shift-invariant, meaning that a change in source position does not change the shape of the irradiance distribution, only its position. The irradiance distribution we can obtain is then governed by deconvolution. Using positive-definite functions and Bochner’s theorem, we provide conditions such that the irradiance distribution can be realized for finite étendue sources. We also analyze the problem using optimization, showing that the result heavily depends on the chosen source distribution.

show abstract

Gradient descent-based freeform optics design for illumination using algorithmic differentiable non-sequential ray tracing

Koning,

Heemels,

Adam

et al. 2023

Optim Eng

View full text Add to dashboard Cite

Algorithmic differentiable ray tracing is a new paradigm that allows one to solve the forward problem of how light propagates through an optical system while obtaining gradients of the simulation results with respect to parameters specifying the optical system. Specifically, the use of algorithmically differentiable non-sequential ray tracing provides an opportunity in the field of illumination engineering to design complex optical system. We demonstrate its potential by designing freeform lenses that project a prescribed irradiance distribution onto a plane. The challenge consists in finding a suitable surface geometry of the lens so that the light emitted by a light source is redistributed into a desired irradiance distribution. We discuss the crucial steps allowing the non-sequential ray tracer to be differentiable. The obtained gradients are used to optimize the geometry of the freeform, and we investigate the effectiveness of adding a multi-layer perceptron neural network to the optimization that outputs parameters defining the freeform lens. Lenses are designed for various sources such as collimated beams or point sources, and finally, a grid of point sources approximating an extended source. The obtained lens designs are finally validated using the commercial non-sequential ray tracer LightTools.

show abstract

Tailored freeform surfaces for illumination with extended sources

Cited by 4 publications

References 4 publications

Gradient descent-based freeform optics design using algorithmic differentiable non-sequential ray tracing

Gradient descent-based freeform optics design using algorithmic differentiable non-sequential ray tracing

Limits of realizing irradiance distributions with shift-invariant illumination systems and finite étendue sources

Gradient descent-based freeform optics design for illumination using algorithmic differentiable non-sequential ray tracing

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