GitHub

FluxOptics.jl

FluxOptics.jl

Differentiable optical propagation and inverse design in Julia

FluxOptics.jl is a Julia package for simulating scalar optical field propagation with full support for automatic differentiation. Design and optimize optical systems through gradient-based methods.

Features

  • 🌊 Scalar field propagation: Angular Spectrum, Rayleigh-Sommerfeld, Collins integral, Beam Propagation Method
  • 🎭 Optical components: Phase masks, amplitude masks, DOEs, graded-index media
  • 🎯 Optimization ready: Fully differentiable with Zygote/Enzyme support via ChainRulesCore
  • 🔧 Proximal operators: TV regularization, sparsity, constraints
  • 📊 Built-in metrics: Power coupling, field matching, intensity shaping
  • 🚀 GPU support: CUDA acceleration available

Quick Example

using FluxOptics, CairoMakie

# 1. Create Gaussian source
gaussian = Gaussian(20.0)
xv, yv = spatial_vectors(256, 256, 1.0, 1.0)
u = ScalarField(gaussian(xv, yv), (1.0, 1.0), 1.064)
source = ScalarSource(u)

# 2. Optical system with vortex phase mask
probe = FieldProbe()
vortex_phase = Phase(u, (x, y) -> atan(y, x))  # topological charge l=1
propagator = ASProp(u, 1000.0)  # 1mm far-field propagation

system = source |> vortex_phase |> probe |> propagator

# 3. Execute system
result = system()
output_mode = result.out
probe_mode = result.probes[probe]

# 4. Visualize evolution
visualize((probe_mode, output_mode), (intensity, phase);
	colormap=(:inferno, :viridis), show_colorbars=true, height=120)
Example block output

Documentation Structure

Tutorials

Learn FluxOptics through practical examples covering inverse design and optical simulation:

  • Fox-Li Cavity Simulation: Find cavity eigenmodes in a semi-degenerate laser resonator. Demonstrates iterative simulation, gain media, and quasi-Ince-Gaussian mode formation near degeneracy points.

  • Phase Retrieval from Intensity: Reconstruct complex optical fields from intensity-only measurements. Shows gradient-based optimization, multi-plane propagation, and handling non-convex inverse problems.

  • Multi-Wavelength Beam Shaping: Design chromatic diffractive optical elements that independently control red, green, and blue beams. Illustrates wavelength-dependent optimization and cascaded DOE systems.

  • Waveguide Tomography: Reconstruct refractive index profiles of photoinscribed waveguides from angle-resolved intensity data. Demonstrates full-wave tomography with joint aberration estimation.

API Reference

Complete documentation of all modules, types, and functions:

  • GridUtils: Coordinate systems and transformations
  • Modes: Gaussian beams, HG/LG modes, spatial layouts
  • Fields: ScalarField type and field operations
  • Optical Components: Propagators, masks, sources, systems
  • OptimisersExt: Optimization rules and proximal operators
  • Metrics: Loss functions for inverse design

Getting Help

  • 📖 Browse the API Reference for detailed function documentation
  • 💬 Open an issue on GitHub for bugs or feature requests
  • 📧 Contact the maintainers for questions

Citation

If you use FluxOptics.jl in your research, please cite:

@software{fluxoptics2025,
  author = {Barré, Nicolas},
  title = {FluxOptics.jl: Differentiable Optical Simulations},
  year = {2025},
  url = {https://github.com/anscoil/FluxOptics.jl}
}