Gravitational Waves Data Analysis Tutorial

Presented by Suyog Garg @ Ewha on 2025/11/18

Welcome! This is a 3-part hands-on tutorial series on computational methods for gravitational waves data analysis. We will explore waveform implementations, ssh access to remote clusters, and introduction to neural networks using interactive Jupyter notebooks and markdown guides. All notebooks will be run live via RISE slides for an engaging session.

Tutorial Parts

Part 0: Set-up Colab, Jupyter, Conda
Part 1: Native Implementations of GW Approximants
Part 2: Working with Remote Computing Clusters
Part 3: End-to-end CNN for MNIST with keras・sklearn・TF・PyTorch

Session Resources

Save these files to your work directory, via Right Click -> Save Link As, and then run on Google Colab or Jupyter Notebook.

Jupyter Notebook: Part1_GW_Waveform_Zoo_Native_Implementations
TXT: Part3_requirements
Jupyter Notebook: Part3A_Keras_MNIST_CNN
Jupyter Notebook: Part3B_ScikitLearn_SciKeras_MNIST_CNN
Jupyter Notebook: Part3C_TensorFlowCore_MNIST_CNN
Jupyter Notebook: Part3D_PyTorch_MNIST_CNN
Jupyter Notebook: Part3E_Compare_Frameworks

Note: During the session, Jupyter notebooks will be presented live using RISE slides. You can access all materials above for reference and follow along.