Comment by ajkjk
3 days ago
I think it's a big improvement. Stiffness is something you can picture directly, so the data -> conclusions inference "stiffness" -> "mass and short range" follows directly from the facts you know and your model of what they mean. Whereas "particles have mass" -> "short range" requires someone also telling you how the inference step (the ->) works, and you just memorize this as a fact: "somebody told me that mass implies short range". You can't do anything with that (without unpacking it into the math), and it's much harder to pattern-match to other situations, especially non-physical ones.
It seems to me like the right criteria for a good model is:
* there are as few non-intuitable inferences as possible, so most conclusions can be derived from a small amount of knowledge
* and of course, inferences you make with your intuition should not be wrong
(I suppose any time you approximate a model with a simpler one---such as the underlying math with a series of atomic notions, as in this case---you have done some simplification and now you might make wrong inferences. But a lot of the wrongness can be "controlled" with just a few more atoms. For instance "you can divide two numbers, unless the denominator is zero" is such a control: division is intuitive, but there's one special case, so you memorize the general rule plus the case, and that's still a good foundation for doing inference with)
Intuition does not work in quantum mechanics. Intuition is based on observations at your scale, and this breaks dramatically at quantum levels. So this is not a good criterium.
That's false. Intuition does work in quantum mechanics, if you do the work to build up a good intuition for quantum mechanics. Which means exactly what I'm talking about: building your intuition on models that give true results in the situation, and which allow you to combine and remix atomic ideas in useful ways.
Unfortunately the version of QM that is taught in textbooks is not especially useful for figuring out what the intuition is. I have my own model that I've concocted that does a much better job, but there are still plenty of things I don't understand well (having not done, like, a graduate degree in it).
I have a PhD in physics, which does not say much apart from the fact that I had to think about this a lot. My PhD was in particle physics.
What I learned over the years is that, unfortunately, at some point you rely on maths. You solve equations, make predictions, and compare this to measurements. Uf they match your model (conveyed through equations) is "good for now"
The problem is that a lot of what you mathematically witness, then measure at macro scales (you do not get to measure quantum effects at their scale, only their effects on the apparatus) does not make sense at our scale.
A particle appearing for a shirt moment from nothing, interacting with another particle and vanishing, WTF?
A particle with energy X hitting a "wall" with energy Y > X and going through? WTF?
Single particles interacting with each other? Another WTF
QM is full of surprises that sound cool when presented with enthusiasm and simple words, or used in MARVEL movies but they are as intuitive for typical people as cosmic travel for Neanderthals . Sure you can handwave your way through them but how does that work with a cave and wall paintings - which is what they would witness on an everyday basis.
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