So is holographic universe theory expected to work without qualification (thus being indistinguishable), or is it more of a temporary patch that nobody believes is correct, but works better for one area, and worse for others?
Newton's model of gravity works well enough for approximation at human scales, but is flawed enough that you don't use it for astrophysics or microscopic realms.
No model accurately represents reality. I think people have this idea that if I have 2 different theories that predict exactly the same thing, that one of them is right and another is wrong. This is exacerbated by a misunderstanding with Occam's razor. It is popular to believe that given those 2 theories, the simpler one is correct. This is not necessarily the case. The simpler one is simpler and therefore a better model to use (being simpler ;-) ).
If it walks like a duck and quacks like a duck, is it a duck? What if it's really something indistinguishable from a duck, but not actually a duck? What does that even mean? Our concept of "duck" is inextricably connected to our perception of it. A "duck" does not exist in the way we envision it, if we do not envision it.
So backing up to your question again, does this theory (or any other theory) explain everything about the universe, or is it more of a temporary patch that nobody believes is correct, but works better for one area, and worse for others? The latter. All models are the latter. The truth is unknowable.
As the parent says, to the extent that the model predicts our observations, it is consistent with reality. Many other models are also consistent with reality. This model may be simpler in some ways and less simple in others. If it is simpler in all ways and has predictions that are consistent with reality, we will use it in preference to other models.
Having said all that, I have no idea in which areas it is simpler, in which areas it is more complex and in which areas it conflicts with our observations.
Which is why I grabbed Newton's gravity model as an example. It's known to be a flawed model, only useful as a simplified approximation method that's "good enough" for many purposes.
It's like having a model that says "quack-like sound == duck". It's wrong. We know it's wrong. It may be useful when looking at birds, but it's 100% wrong when your hard drive produces the noise.
Of course it's a spectrum, but some of the things we hang on to and use are known to be false in a large way but still useful.
We could, one day, wake up to discover that we are actually living in the matrix. The rules of physics were only added by the machines to keep us amused so that we don't discover the true nature of our beings (batteries for the machines). Yeah... I don't believe it either :-)
But the key is that we can't know. Maybe "God did it" is the truth and the rest is just appearances. Maybe our mathematical constructs do represent reality closely. Even if we build models that are isomorphic to our perception of reality, there is still no way to tell if they are in any way similar to the actual workings of reality. The FSM can certainly alter our brains so that we just believe we see things happening in a consistent way, even though they are not.
Like I said, it is tempting to believe that the simplest solution that we can imagine is close to reality. This is very unlikely to be the case, IMHO. It's fine to believe it is, but that is not science any more. You are entering into religion.
Newton's laws are not known to be "more wrong" than relativity. Relativity matches our observations more closely and is simpler in some respects, but it could be just as wrong. Or more wrong. We have no way of measuring how close to reality our models are. We can only measure how closely they match our observations. As one of the other posters quoted: All models are wrong. Some of the are useful.
Even when you have a model that is completely consistent with observations it does not make it more likely to be correct. Imagine creating some byzantine model with a myriad of exceptions to explain away any discrepancy. Obviously as long as we accept complexity, we can model anything. These models are not usually useful though.
So as much as I understand that you want to ask, "Is this model more likely to be closer to the truth than other models", it isn't a question we can answer in science. We can only answer the questions, "Is this model consistent with our observations?", and "Is this model simpler than another model?"
The article claims that the model is at least as consistent as other models while being simpler in some instances. I think work needs to be done to verify those claims.
Yes, but now we're getting so metaphysical that all usefulness has evaporated. "Nothing is knowable" and all. I can agree, but it's a stance which provides no course of action.
We have a current best, or at least competing current bests. These may later be invalidated - that's fine, that's learning new things. It doesn't mean that everything we know now is indistinguishably-wrong as everything we thought we knew in the past. We can predict things now that we couldn't before.
We also have approximations that don't attempt to predict the system, they just produce useful results often enough to be retained - are these indistinguishable from all other attempts at describing reality?
How far do we take it? If Pi is 3, it may actually be true! It'd just invalidate a ridiculous amount of what we think we know. That's equal to quantum mechanics, which appears to have concrete applications.
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Perfect is the enemy of good.
> The article claims that the model is at least as consistent as other models while being simpler in some instances. I think work needs to be done to verify those claims.
I don't think anyone working in science believes any model they investigate is going to work without qualification for all time (for a limited time, with current ability to verify, sure; Newtonian gravity worked that way for a long time, too.)
Science approaches the underlying reality asymptotically.
Newton's model of gravity works well enough for approximation at human scales, but is flawed enough that you don't use it for astrophysics or microscopic realms.