5 ms·

Take for example entanglement. The math that describes it is known precisely. Specific implications of this are known. There's no information transfer, there's

Take for example entanglement. The math that describes it is known precisely. Specific implications of this are known. There's no information transfer, there's no time delay, etc. And yet lay people keep incorrectly thinking it can be used for communication. Because lay-audience descriptions by experts keep using words that imply causality and information transfer. This is not a failure of the experts to understand what's going on. It's a failure to translate that understanding to ordinary language. Because ordinary language is not suited for it. > Its “founding fathers” all admitted that it’s a bunch of guesswork and that the models we have are arbitrary and lack something essential needed for proper understanding. We don't have a model of why it works / if there's a more comprehensible layer of reality below it. But it's characterized well enough that we can make practical useful things with it.

zmgsabst 1y ago
> This is not a failure of the experts to understand what's going on. > We don't have a model of why it works / if there's a more comprehensible layer of reality below it. Counterpoint: You’ve just admitted they don’t understand what’s going on — they merely have descriptive statistics. No different than a DNN that spits out incomprehensible but accurate answers. So this is an example affirming that QM isn’t understood.
- tbrownaw 1y ago
  The only descriptive / empirical parts is the particle masses. But it sounds like your objection is that reality isn't allowed to be described by something as weird as complex values that you multiply to get probabilities, so there necessarily must be another layer down that would be more amenable to lay descriptions?
  - zmgsabst 1y ago
    That’s not my point, nor close to what I said. My point is that their models are fitted tensors/probability distributions, often retuned to fit new data (eg, the epicyclic nature of collider correction terms) — the same as fitting a DNN would be. Their inability to describe what is happening is precisely the same as in the DNN case.
    - Dylan16807 1y ago
      If you have a very small neural network, you can fully understand and explain how it works. As you increase the detail of a description, it reaches a point where nothing is missing.
      - zmgsabst 1y ago
        As I pointed out, eg, the high number of correction terms when trying to tune the model to actual particle accelerator data is evidence that our model is missing something. (And some things are plain missing: neutrino behavior, dark matter, dark energy, etc.) In the same way that a high number of epicycles was evidence our theory of geocentrism was wrong — even though adding epicycles did compute increasingly accurate results.
        aleph_minus_one 1y ago
        > As I pointed out, eg, the high number of correction terms when trying to tune the model to actual particle accelerator data is evidence that our model is missing something. (And some things are plain missing: neutrino behavior, dark matter, dark energy, etc.) This is rather a problem of the standard model. Physicists will immediately admit that something is missing there, and they are incredibly eager to find a better model. But basically every good attempt that they could come up with (e.g. supersymmetric extensions of the standard model; but I'm not a physicist) has by now (at least modtly) been falsified by accelerator experiments.
        Dylan16807 1y ago
        The comment you originally replied to was about entanglement, not the entire standard model. The math there is very simple, not built on correction terms.
        deleted 1y ago
        [deleted]
        evanb 1y ago
- teiferer 1y ago
  QM isn't less well understood though than Newton's mechanics. Neither cover the "why". But both provide a model of the world, the model (!) is very precisely understood and it matches observations in certain parts of reality. Like all reasonable scientific theories do. They have limits, and beyond those limits they don't apply, but that doesnt mean they are not understood. It's reality that is not sufficiently well understood and by coming up with more and more refined models/theories, we keep approximating it, likely without ever having a "fully correct" theory encompassing everything without limits. (But that's ok.)

zmgsabst 1y ago

> This is not a failure of the experts to understand what's going on. > We don't have a model of why it works / if there's a more comprehensible layer of reality below it. Counterpoint: You’ve just admitted they don’t understand what’s going on — they merely have descriptive statistics. No different than a DNN that spits out incomprehensible but accurate answers. So this is an example affirming that QM isn’t understood.

tbrownaw 1y ago
The only descriptive / empirical parts is the particle masses. But it sounds like your objection is that reality isn't allowed to be described by something as weird as complex values that you multiply to get probabilities, so there necessarily must be another layer down that would be more amenable to lay descriptions?
- zmgsabst 1y ago
  That’s not my point, nor close to what I said. My point is that their models are fitted tensors/probability distributions, often retuned to fit new data (eg, the epicyclic nature of collider correction terms) — the same as fitting a DNN would be. Their inability to describe what is happening is precisely the same as in the DNN case.
  - Dylan16807 1y ago
    If you have a very small neural network, you can fully understand and explain how it works. As you increase the detail of a description, it reaches a point where nothing is missing.
    - zmgsabst 1y ago
      As I pointed out, eg, the high number of correction terms when trying to tune the model to actual particle accelerator data is evidence that our model is missing something. (And some things are plain missing: neutrino behavior, dark matter, dark energy, etc.) In the same way that a high number of epicycles was evidence our theory of geocentrism was wrong — even though adding epicycles did compute increasingly accurate results.
      - aleph_minus_one 1y ago
        > As I pointed out, eg, the high number of correction terms when trying to tune the model to actual particle accelerator data is evidence that our model is missing something. (And some things are plain missing: neutrino behavior, dark matter, dark energy, etc.) This is rather a problem of the standard model. Physicists will immediately admit that something is missing there, and they are incredibly eager to find a better model. But basically every good attempt that they could come up with (e.g. supersymmetric extensions of the standard model; but I'm not a physicist) has by now (at least modtly) been falsified by accelerator experiments.
      - Dylan16807 1y ago
        The comment you originally replied to was about entanglement, not the entire standard model. The math there is very simple, not built on correction terms.
        deleted 1y ago
        [deleted]
      - evanb 1y ago
teiferer 1y ago
QM isn't less well understood though than Newton's mechanics. Neither cover the "why". But both provide a model of the world, the model (!) is very precisely understood and it matches observations in certain parts of reality. Like all reasonable scientific theories do. They have limits, and beyond those limits they don't apply, but that doesnt mean they are not understood. It's reality that is not sufficiently well understood and by coming up with more and more refined models/theories, we keep approximating it, likely without ever having a "fully correct" theory encompassing everything without limits. (But that's ok.)