I use arch and I don't have the rust package installed. In it's stead, I have the rustup package installed. As the rust project recommends the use rustup to manage multiple possible installed versions of rust, my guess is that most arch users only install rustup.
I'm not sure if the values for rust on this graph account for the rustup package.
I've read the regular languages section of Michael Sipser's "Introduction to the theory of Computation" and I really liked how it was written and how the material was presented. The first chapter is an introduction to the mathematical background you will need as well as quick primer on proofs. The following sections are "Automata and Languages" (regular/context free languages), Computability Theory (Turing machines, decidability & more) and Complexity Theory. The book flows like this: Sipser initially starts with an example or two to demonstrate an idea, and then formalises the idea with definitions or proofs. I'd recommend you have a look at it!
As for why Turing machines matter, from my understanding, this comes from the notion of Turing completeness. Essentially if it's possible to compute something, it can be done on a turning machine. Note that different computational models, such as the lambda calculus, can have the same level of power (Church-Turing thesis). An example of something that can't compute the things that a Turing machine can compute, is definite finite automata which are equivalent to regular languages/regexes. So, now we come to the most interesting bit, what are the limits of Turing machines? By understanding them, we understand what the limitations of our computational tools. This is where the halting problem comes in. It's not possible (on a Turing machine) to write a program that can figure out if a general program will terminate. This implies there are things that we can't really compute. There was a great answer of CS stack exchange regarding this: https://cs.stackexchange.com/a/32853
I hope that helps, let me know if you have any further questions.
For context I studied physics for about 2 years in university, before I switched to maths with the intention of returning with better mathematical foundations.
That being said let's start with the maths you will need to be comfortable with:
- Complex Numbers (e^(i*theta))
- Linear Algebra (Matrix Multiplication, Basis of a vector space, Finding Eigenvalues)
- Calculus and some Differential Equations (Taylor Expansions, Solving DEs)
- Probability, Expectation values and Distributions
That's probably what you'll need to dive into textbooks. For a deeper understanding, it would help to know these (worry about these later):
- Analysis (My math major friends say that functional analysis is required later on)
- Hamiltonian Mechanics (QM is littered with Hamiltonians)
- Group theory (if you want to get into Particle Physics)
I'd also recommend having a good grasp on classical mechanics because quantum mechanics builds on it. On my todo list is to review this using:
All of this is at an undergraduate level. It's probably best to grab one of the books and start running through, consulting the others when you want another explanation.
Let me know if you have any further questions. QM is damn cool dude, I hope you have a fun time delving into it.
I just want to note that Capcom, another Japanese company, has managed to make Street Fighter an Esport starting with Ultra Street Fighter 4 in 2014 and continuing now with Street Fighter 5. They did this by having a qualifying circuit for their Capcom cup tournament at the end of the year which had a prize of $250k for 1st place. It's nowhere as big as the 3 you mentioned, but I think that's mostly due to size of the scene.
What are specfic benefits L-Theanine gives you? I've read that L-Theanine is more of a relaxant that counteracts the anxiety casuing effects of caffiene, so I can't really see how it helps you focus.