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This is fantastic, although the statement about the intended audience cracked me up a bit: "intended for a general audience including ... anyone interested in a concise intro/overview of QM. Prerequisites: linear algebra, calculus, ..."

The PDF is essentially higher math with QM-related narrative interspersed here and there. Even if you're a STEM graduate, I found that these skills atrophy pretty quickly if you're not using them day-to-day in your work. Scientists often vastly overestimate how conversant their readers are with "obvious" prerequisites such as vector calculus.

And you can often tell on HN, because you have a thread where two mathematicians chat with each other, and then everyone else is just relating anecdotes about quantum mechanics.

Nice, I like how you start out with the finite dimensional case here. Personally though, I don't think I really "got" quantum mechanics until I saw Bell's inequality, so I prefer to put that front and center.

Maybe a pointless nitpick, but is a PDF on GitHub really the best way to distribute this though? I guess you also didn't want to give away the .tex file? arXiv is usually the best place to upload these kinds of notes so they can be indexed and easily found.

Nice effort. As far as textbooks for QM, Electrodynamics, and any sufficiently complex field of study goes, I always feel that these have been written using abstractions that people have developed much later retroactively. I understand the advantages: it makes the entire content concise, structured, and basically straightforward. However, what I crave is a technical book that is based upon the history of the subject. Something that doesn't start immediately with Hilbert spaces but starts off by talking about why Max Plank did what he did, how did Einstein improve upon it, what mistakes were made, what misguided hypothesis were later corrected in what manner, how were different things then unified... you get the point. I think this narrative based approach would motivate me much better than something that's condensed and distilled.

After a colleague asked about this, my interest was primed on quantum computing. I found wikipedia hard to follow and the textbooks were really expensive. Then I stumbled on this course by IBM:

https://quantum.cloud.ibm.com/learning/en/courses/basics-of-...

It has prereqs in complex numbers and linear algebra, but is quite easy to follow if you have these.

I like how it first uses quantum notations to describe the non quantum world, so you get used to the reasoning. Then it adds the actual quantum stuff on top of the now understandable reasoning.

One issue: 'classical mechanics' section doesn't introduce Hamiltonian, and instead it's introduced in chapter 2.2 as if it is a QM concept.

In my uni Classical Mechanics course was a pre-requisite to QM to ensure that students have a good intuition about Lagrangian and Hamiltonian formalisms, because those are non-trivial concepts by themselves.

Note sure if it is the route I recommend. Starting with classical mechanics takes more background that needed, is likely to be more confusing that needed and to build very wrong intuitions and conceptions.

I really suggest starting with quantum itself, before spin-1/2 systems are easier to start, and photons (in my opinion), even easier (vide Sec. 2 in https://doi.org/10.1117/1.OE.61.8.081809).

So, I recommend starting from "Quantum Mechanics Theoretical Minimum" by Leonard Susskind and Art Friedman, "Six Quantum Pieces: A First Course in Quantum Physics" by Valerio Scarani or "Introduction to Quantum Information Science" by Artur Ekert (https://github.com/thosgood/qubit.guide). To dive deeper, I recommend " Lectures on Quantum Mechanics" by Berthold-Georg Englert.

It's wrong to assume people know classical physics formalism well and then and only then, they'll learn QM!

QM pedagogy problem is, how to teach QM to people who don't know physics beyond [F= ma], and math beyond algebra, differential calculus, & virtually no probability beyond mean & std dev?

A very short book is Quantum Theory: A Very Short Introduction, part of Oxford University Press's very short introduction series is good.

As a member of the general audience I was disappointed to find no color illustrations. Faced with walls of text and an absence of enjoyable distraction and marginalia, I began to think (which rarely happens) "wouldn't the relevant audience desire more mathematical equations?". And then I closed the pdf.