Learning Objectives:

A brief introduction to photochemistry and climate modeling

Installing Photochem

First photochemistry simulation: a model of Modern Earth

Modifying chemical reaction rates or other internal model data (e.g., photolysis or aerosol cross sections)

Modifying the Photochem source code & contributing to the model

First climate simulations: reproducing the Habitable Zone

If we have time – a photochemistry and climate simulation of TRAPPIST-1e assuming it is an inhabited world.

Organized under the TAP Computation and Data Initiative, Chi-Kwan Chan ran weekly hackathons (11 sessions) open to all TAP members in FY24. 18 participants from Astronomy, Physics, and Computer Science joined the hackathons. The sessions were designed to teach a variety of applications for deep learning in science, train on neural network learning, and provide hands-on experience working through challenging projects and solutions.

Overview doc of all the sessions

• Foundations of Machine Learning
• Convolutional Neural Networks
• Momentum in Gradient Descent