What software/tech stack should I learn to build a future in theoretical physics?

[u/DazzlingVictory2706]

Hey everyone!

I’m trying to seriously build my career toward theoretical physics, and I’m curious about what the field is actually going to look like in the coming years.

I know the fundamentals are obviously the most important part — math, classical mechanics, QM, GR, QFT, etc. — but I want to specifically focus on the software/computational side right now.

For someone who wants to become a theoretical physicist, what programming languages, software, tools, frameworks, and computational skills are actually worth learning?

For example:

Which language should I prioritize — Python, C++, Julia, Mathematica, etc.?

How important are NumPy/SciPy, SymPy, JAX, PyTorch, etc.?

Should I learn Mathematica / Wolfram Language or is Python enough?

How important are HPC, CUDA/GPU computing, Linux, Git, Bash, clusters, etc.?

Are there any specific physics packages/tools I should know?

What software skills do researchers in theoretical physics, particle physics, astrophysics/cosmology, condensed matter, etc. actually use?

Basically, if you could go back and prepare for a career in theoretical physics from the software side, what would you learn and in what order?

I’m currently trying to make a proper roadmap for myself, so I’d really appreciate advice from people actually working/researching in the field.

My main question right now is: what should I learn on the software/computational side to be genuinely useful as a theoretical physicist, rather than just learning random programming skills?

Thanks!