I am currently on the road to particle physics by re-implementing AI-related papers . I will post my progress here and share how deep learning is being used in physics . As I progress, I will add more papers to the list
Paper 1 : Quantum mechanics - Using a neural network to model the wave function ansatz [link][code]
I am currently working on the prerequisites and implementing papers along the way to get there. I will repeat the process for nanoscience, neuroscience, material science, astrophysics, and synthetic biology
It’s a very interesting topic, It’s a good thing that you are starting with the basics. I also have a interest in this field. Certainly i will learn something.
I meant - what are you using for working on the prerequisites? What materials are you showing in the above screenshots? Are they notebooks you’re creating? Are you sharing them publicly? How are you creating them?
What materials are you showing in the above screenshots?
It’s my notes from mechanics and electricity
Are they notebooks you’re creating?
Yes, I use sympy for symbolic calculations and pint for unit conversion
Are you sharing them publicly?
Yes, all of my notes above and other notes are shared publicly.
code: GitHub - xrsrke/homework: Notes
physics summary: url
mechanics summary: url
electricity summary: url
quantum mechanics summary: url
… for other notes (like deep learning, RL, NLP, chemistry…) go: url and search the name
How are you creating them?
I use Notion for notes, Miro.com for diagrams, Mathpix to convert images to LaTeX, OwlOCR to convert images to text, and ChatGPT and Perplexity.ai to search for information and learn new concepts.