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Beamshapy is a Python-based module designed for crafting laser beam shaping masks for use on phase-only Spatial Light Modulators (SLM). It leverages Fast Fourier Transform (FFT) propagation and relies on the Lightpipes package for its core functionality.
Beamshapy provides two primary methods for mask design:
Manual Design:
Gerchberg and Saxton Algorithm:
Beamshapy includes several examples to demonstrate its capabilities:
example_simple_FT_propagation.py
: Simple propagation with a wrapped wedge displayed on the SLM.example_mask_design_BG_modul.py
: Mask design and propagation, used to design the masks featured in the associated article.example_mask_design_fresnel.py
: Mask design for a Fresnel lens.example_mask_design_GSA.py
: Target intensity design and Gerchberg and Saxton optimization routine to obtain the phase mask for the targeted intensity in the conjugate Fourier plane.For a practical application of Beamshapy, refer to our article: Selective excitation of high-order modes in two-dimensional cavity resonator integrated grating filters, A. Rouxel et al, 2024. Read the article
To install beamshapy
, follow these steps:
Clone the repository from GitHub:
git clone https://github.com/a-rouxel/beamshapy.git
cd beamshapy
Create a dedicated Python environment using Miniconda: If you don't have Miniconda installed, follow the instructions here.
# Create a new Python environment
conda create -n beamshapy python=3.9
# Activate the environment
conda activate beamshapy
Install the necessary Python packages:
The required packages are listed in the requirements.txt
file in the repository.
# Install necessary Python packages with pip
pip install -r requirements.txt
Beamshapy is open-source and available under the MIT License.
Contributions are welcome! Please feel free to submit issues, fork the repository, and send pull requests.
For any questions or feedback, please contact the repository owner at arouxel@laas.fr.
FAQs
a package for simulations of laser beam shaping experiments
We found that beamshapy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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