I always found "wave function collapse" to be a terribly overcomplicated name for a pretty intuitive concept. The first paragraph does a good job explaining the term, but still I wonder how many people stray away from such things when the name alone is overwhelming.
For many, the name is intuitive as its encapsulating the idea that a cell can hold a variety of states until it gets "collapsed".
I prefer the name given in mathematical optimization, which is Constraints Satisfaction Problems; instead of using an imprecise physics metaphor, it gets a descriptive logical term of what's going on.
In CSPs, each cell is a 'decision variable' with a 'domain' of values, which get pruned by 'constraints' that propagate to values invalidated by the decisions made in the connected variables, until the whole 'problem' gets into either a solution which 'satisfies' all the constraints, or a contradictory state where a variable's domain is empty, causing the algorithm to backtrack.
CSPs have the advantage of having clear and efficient methods to go back to a previous state and keep exploring every alternate possibility, rather than having to restart from the beginning. The article hints at that possibility ('saving checkpoints' or'reverse the collapsing of a cell'); there's a whole field of study dedicated on the best ways to do that on a large scale for very general problems.
Boris the brave coined the term "Constraint Based Tile Generators" (CBTG) [0], which is a specialization of the more general CSPs to this particular domain.
Personally, I find CSPs overly general and mired in esoteric, byzantine terminology. It's a large cognitive load to put on people to run through the glossary of terms just to talk about the problem set up. I don't think the quantum mechanic analogy is great but I can see it being much more intuitive than the obscure language of CSPs.
[0] https://www.boristhebrave.com/2021/10/31/constraint-based-ti...
Surely the 'solving' part of CSPs may be obscure, but the basic concept can be readily explained with the metaphor of crosswords and sudoku (both are very direct instances of CSPs); there's not much obscurity to that. In fact, the article resorts to that same metaphor to explain with precision what the 'waveform' metaphor couldn't.
Of course terminology for CSPs will get confusing when you get to represent them mathematically; but that happens to anything that you turn into math. The core concept is quite familiar and intuitive.