Comment by vibe42
6 hours ago
Something related and fun is parsing a simple CSV file of exoplanets.
https://exoplanetarchive.ipac.caltech.edu/cgi-bin/TblView/np...
Download Table -> All Columns, All Rows.
Tried a few new, open, local AI models by giving them the CSV file and asking them to write a simple python script:
1. Parse all rows and build statistical distribution of mass, radius etc.
2. Use those distributions to generate fictional exoplanets.
Playing with this for a space game idea where star systems are populated with fictional exoplanets, but all their params are from the real statistical distributions of all known exoplanets.
A way to get some harder sci-fi using real world data :)
Keep in mind that our current instruments are not really sensitive to most exoplanets that would be interesting for a sci-fi setting.
Current instruments are mostly good at finding large planets around small stars, we are basically blind to earth-like planets around sun-like stars.
See e.g. https://www.nobelprize.org/prizes/physics/2019/queloz/lectur...
Thank you for the data source. I'll eventually add it to the project that I'm working on
I've got a little orbital dynamics simulator written in C that I've been tinkering with for the past little while. I've got the solar system planets and some asteroids going, I was going to work on moons and artificial satellites / probes next.
My goal was to tinker with simulating a solar system based economy that used Aldrin cyclers for lunar / asteroid mining.
The author of this software posts on HN quite frequently, but I can't remember their username: https://caltech-ipac.github.io/kete/