New tutorial alert!

We are excited to share the news that our most recent preprint, The Hitchhiker’s Guide to Differential Dynamic Microscopy has been submitted to arXiv. Authored by our postdocs Enrico Lattuada and Maxime Lavaud, master student Fabian Krautgasser, in collaboration with Fabio Giavazzi.

Whether you’re a soft matter physicist, biophysicist, or microscopy enthusiast—if you’re looking to measure dynamics without tracking, this guide is for you.

A comprehensive tutorial that covers:

✔️ Physics of DDM

✔️ Mathematical foundations

✔️ Image formation

✔️ Practical data analysis

✔️ Common pitfalls

✔️ Real datasets & examples

Through this guide, we also introduce fastDDM—an open-source, high-performance Python package that speeds up DDM analysis by up to 4 orders of magnitude.

GPU + FFT + smart averaging = minutes instead of hours of image processing.

📊 Reproducibility first!

Each section is paired with Jupyter notebooks using real or datasets. 🔄 You can follow every step, run the code, and adapt it to your system.

✅ Educational

✅ Extensible

✅ Transparent

🧪 What can you do with this tutorial?

We guide you through:

✅ Particle sizing

✅ Merging fast & slow acquisitions

✅ Handling 2D vs. 3D dynamics

✅ Detecting axial drift & sedimentation

✅ Quantifying uncertainty

✅ Using image windowing

✅ Optimizing experimental design

🧵 Read it, 🔧 use it..

💡 And reach out with feedback—fastDDM is community-driven!