Torch Lens Maker – Differentiable Geometric Optics in PyTorch
Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems. Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made…
In plain words
Torch Lens Maker is an open-source Python library for designing optical systems using differentiable geometric optics in PyTorch. It allows users to model and optimize lenses and optical elements using PyTorch's automatic differentiation and neural network building blocks. The library treats optical systems similarly to neural network architectures, enabling developers to stack optical components and leverage state-of-the-art optimization techniques. Currently experimental, it aims to provide an intuitive API for optical system design analogous to OpenSCAD but for optics.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems. Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made between layers of a neural network, and optical elements in a so-called sequential optical system. So the magic is that we can stack lenses as if we were stacking Conv2D and ReLu layers and everything works out. Instead of Conv2D you have ray-surface collision detection, instead of ReLu you have the law of refraction. Designing lenses is surprisingly like training a neural network. Check out the docs for examples of using the API. My favorite one is the rainbow :) https://victorpoughon.github.io/torchlensmaker/examples/rain... You should be able to `pip install torchlensmaker` to try it out, but I just set it up so let me know if there's any trouble. I was part of the Winter 1'24 batch at the Recurse Center (https://www.recurse.com/) working on this project pretty much full time. I'm happy to talk about that experience too!
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, March 2025
the whole month →
Mimic Human Research & Save Findings in AI Knowledge Base
AI · 2025 · sider.ai
