Here’s part 10 of my Linear Algebra for Quantum Computing cheat sheet series! I had to include fewer topics in the sheet than I had anticipated because I decided to include information that could help anyone who might be stuck on Exercise 12.64 in Section 2.2 in the first edition version of Jack Hidary’s textbook Quantum Computing: An Applied Approach. It’s a system of equations problem which you’re supposed to be able to solve “with enough effort”…and if it’s been a while since you’ve done a system of equations problem or row operations, it might be a decent amount of effort. I was able to solve it eventually, but had to get help from my network, and they let me know that I should introduce a constant into the problem. I include my own example of this type of problem in the sheet, as well as the steps to solve it and the solution.

The sheet is mainly about inverse transformations - and more specifically, how to find the inverse matrix and the inverse function associated with the transformation, which also leads to a discussion about the adjugate matrix.

UPDATE 08.31.2022: Since these sheets are now complete, styled, reviewed, edited, and published, you can pick up the whole pack of 15 in my shop here!