John Gill
Exploring the Universe with python.
Ottawa, Canada
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I grew up in the same small Yorkshire town as Fred Hoyle, the astronomer who coined the term Big Bang.
Later I studied mathematics at Warwick University, with Professor Colin Rourke as my personal tutor.
It was over 20 years ago, working in Dublin that I discovered python, and soon after matplotlib.
I contributed a table module to matplotlib, and a version of this now resides in blume, which is intended to explore tables more generally. My idea was to create a few examples as I explored data sets that interested me and use that to shape the table module.
Seven years ago Rourke published, "A New Paradigm for the Universe". It outlines a complete model for the universe, without the need for dark matter or dark energy.
When the second edition was published, under the new title, The Geometry of the Universe, I started the gotu project, to help me explore the ideas in the book and test the theories in the book with the incredible data available from space based missions.
Rourke's theory suggests that Fred Hoyle was correct after all and the Big Bang did not happen. With JWST showing fully formed galaxies soon after the Big Bang, it is a theory that deserves investigation.
My goal with the gotu project is to raise awareness of Rourke's work and enable others to explore his ideas with python software and matplotlib visualisations.
Area of Expertise
Topics
Introduction to the Geometry of the Universe.
The workshop will feature modules from my gotu project, exploring the geometry of the universe.
It will cover downloading and visualising data from the James Webb Space Telescope and the Gaia mission to visualise the rotation curve for the Milky Way.
Simulate the Milky Way's rotation curve assuming the Sciama Principle: a rotating mass induces a rotation on the surrounding space time. Compare to the Gaia image.
Introduction to de Sitter Space. This will use matplotlib to visualise geodesics in de Sitter Space, allowing us to explore the subtle relation between redshift and distance.
Downloading and visualising the supernovae data and testing whether it is consistent with de Sitter Space.
Since gotu uses blume, the workshop will begin with an introduction to blume.
The goal is for attendees to have at least half the workshop time to explore the ideas and data sets for themselves.
Exploring the Milky Way with astropy, matplotlib and Gaia
We are living at an incredible time for astronomy.
Space based telescopes are providing large amounts of wonderful open data.
python is central to the complex data processing and analysis that is happening through huge collaborations.
The talk will focus on two personal python projects.
The first, blume, is a general toolkit I used to help me working with matplotlib. It actually began it's life here in Dublin some 20 years ago, and was part of my introduction to matplotlib.
The second is gotu, a project I started to help me explore the ideas in Professor Colin Rourke's book, The Geometry Of The Universe. It mostly consists of tools to visualise data with matplotlib and it uses blume.
Three modules from gotu will be covered:
gotu.jwst: a tool to download and view jwst data.
gotu.gaia: a tool that downloads a subset of Gaia data and uses it to visualise the Milky Way's rotation curve: how the velocity of stars vary as you move out from the centre of the Milky Way.
gotu.spiral: how the Sciama Principle and de Sitter Space can explain what we are seeing.
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