Ciro Santilli @cirosantilli 37

This is the hardest one to do iteratively.

Bibliography:

www.physics.udel.edu/~jim/PHYS424_17F/Class%20Notes/Class_5.pdf by James MacDonald shows it well.

The operators are a natural guess on the lines of "if p and x were integers".

And then we can prove the ladder properties easily.

The commutator appear in the middle of this analysis.

10 2-hour lessons.

Lecturer: Leonard Susskind.

What it adds on top of reverse debugging: not only can you go back in time, but you can do it instantaneously.

Or in other words, you can access variables from any point in execution.

TODO implementation? Apparently Pernosco is an attempt at it, though proprietary.

Conda is like pip, except that it also manages shared library dependencies, including providing prebuilts.

This has made Conda very popular in the deep learning community around 2020, where using Python frontends like PyTorch to configure faster precompiled backends was extremely common.

It also means that it is a full package manager and extremely overbloated and blows up all the time. People should just use Docker instead for that kind of stuff: www.reddit.com/r/learnmachinelearning/comments/kd88p8/comment/keco07k/

You also have to buy a license to use their repos if you are part of a large-enough organization: stackoverflow.com/questions/74762863/are-conda-miniconda-and-anaconda-free-to-use-and-open-source

One of their learning sites: www.qutube.nl/

The educational/outreach branch of QuTech.

Show up in the solution of the quantum harmonic oscillator after separation of variables leading into the time-independent Schrödinger equation, much like solving partial differential equations with the Fourier series.

I.e.: they are both: