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Comment by atemerev | Hacker News Reader

Currently trying to learn quantum physics on my own (with no previous education in physics, only a CS degree). Very hard, but surprisingly, some analogies from machine learning can be helpful (a ket vector is like the sample, a bra vector is the set of coefficients, multiplying both gives you a measurement... this kind of thing). It can be wrong, but similarities in mathematical structures help immensely.

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If you're ever interested in digging into other areas of physics, take a look at this blog post by Susan J Fowler which gives a comprehensive overview with references to various topics: https://www.susanjfowler.com/blog/2016/8/13/so-you-want-to-l...

Thank you so much!

Try starting with Townsend’s book. https://amzn.com/1891389785/

http://www.feynmanlectures.caltech.edu/

https://openstax.org/details/books/university-physics-volume...

That's fundamentally because they're both just linear algebra. You'd have an even easier time if you thoroughly mastered linear algebra and then "merely" applied your knowledge to whatever you'd like to learn in CS and physics that requires it.

It's interesting you mention similarities with machine learning, when in fact, chronologically speaking, the formalisation of Quantum Mechanics used (complex) tools from Hilbert Space.

Both QM and ML are very heavy in linear algebra. Some might say they’re both glorified (or unglorified?) linear algebra. ;)

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