ShapePipe: A modular weak-lensing processing and analysis pipeline
- Room:
- Liffey Hall 1
- Start (Dublin time):
- Start (your time):
- Duration:
- 45 minutes
Abstract
I will the present the first public release of ShapePipe, an open-source and modular weak-lensing measurement, analysis and validation pipeline written in Python. I will begin by giving an (easy-to-follow) introduction on how and why we measure the shapes of galaxies to map the distribution of dark matter in the Universe. I will then describe the design of the software, mentioning the numerous Python packages we used, and justify the choices we made. I will conclude by discussing some of the lessons we learned along the way and how these can be applied to other scientific software development projects.
Talk~None of the above
Description
Why would you want to listen to this talk?
Cosmology is the study of the origin, evolution, structure and ultimate fate of the Universe. From the largest galaxies down to the smallest Python programmers our story begins with the Big Bang. The particles that make up all of things we can touch and see only account for 5% of the energy density of the Universe. Leaving us quite literally in the dark! Weak gravitational lensing, a barely perceptible change to the shape of galaxies that we observe, is an indispensable tool for understanding the nature of dark matter and dark energy. However, measuring the shape of galaxies to the precision required is actually quite a tricky problem.
What could be more interesting? 😁
What does this have to do with Python?
Well, Python has steadily become the standard programming language for cosmologists over the last decade or so... and we are no exception! In this talk I will describe the tools we have developed in Python to help us solve some of the problems with measuring the shapes of galaxies and how various existing Python packages have made this possible.
We hope that some of the things we have learned could be useful to other teams, in particular those developing scientific software.