What: 

Removing stellar noise in data from space telescopes is essential if we have to analyse the data further to understand the predict the physical properties and chemical composition of the exoplanets.

The workshop will focus on creating hybrid machine learning models to remove noise of stellar spots in light transit curves in different wavelengths. The output will be better estimation of the planet to star radius ratios in different wavelengths. This becomes the key to identifying different molecules present in the exoplanetary atmospheres. Different chemical molecules are transparent to some wavelengths, while absorbing other wavelengths of light.

This changes the effective radius of the transiting exoplanet.

What to bring:

Workshop will be carried over Jupyter Notebooks. Installing instructions will be provided.

ZOOM ROOM: MITOCHONDRIA

https://mit.zoom.us/j/92760695320

Want to ask questions about the workshop: Email artash.nath@gmail.com