SciPy 2024

Connor Stone

I am a postdoctoral fellow at the Université de Montréal in Canada. I apply statistics to astronomical problems and I'm not afraid to develop some open source software along the way! I study Galaxies, strong gravitational lensing, and machine learning.

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Sessions

07-10
13:15
30min
Development of AstroPhot: Fitting Everything Everywhere all at Once in Astronomical Images
Connor Stone

We present AstroPhot, a tool to accelerate the analysis of astronomical images. AstroPhot allows for simultaneously modelling images with galaxies and point sources in multi-band and time domain data. In this talk I will the benefits and challenges of how we used PyTorch (a differentiable and GPU accelerated scientific python library) to allow for fast development without sacrificing numerical performance. I will detail our development process as well as how we encourage users of all skill levels to engage with our documentation/tools.

General
Room 317
0min
Development of Caustics: a differentiable, GPU accelerated, gravitational lensing simulator
Connor Stone, Cordero Core, Don Setiawan

We present Caustics, a tool to accelerate the analysis of gravitational lensing systems for the next generation of astronomical data. Caustics will enable precision measurements of dark matter properties, the expansion rate of the Universe, lensed black holes, the first stars, and more. In this talk I will discuss the benefits and challenges of how we used PyTorch (a differentiable and GPU accelerated scientific python package) to allow for fast development without sacrificing numerical performance. I will detail our development process as well as how we encourage users of all skill levels to engage with our documentation/tools.

General