[YeGoblynQueenne]

Thank you, that's a good explanation- in the sense that I understand now what the previous comment, by Koshkin meant in responding to mine that there is no "wrong" frame of reference.

>> The location, and speed with which you are travelling is what general relativity calls a "frame of reference", and none of them are "correct" or "incorrect", they're just predictors for what observations will be possible from that frame.

OK, I see- "frame of reference" is a technical term, in General Relativity, that refers to your position in space, and determines what you can observe. Instead, I meant "frame of reference" as a more general "point of view" or "frame of mind" - a set of assumptions that give context to any observations and that inform interpretations of them.

Even going by the technical sense of a frame of reference, though, there are frames of reference that will not permit the cocrrect identification of a process that generates a set of observations- or at the very least, they will tend to favour incorrect interpretations of the observations.

I think that is in keeping with what your comment says about a frame of reference in General Relativity allowing a range of physical observations.

[ZenPsycho]

Right, so what was ground breaking about General Relativity, is that it challenged the newtonian axioms (assumptions) that there's a single universal clock, and that all objects within the universe are effectively rigid and exist in something resembling euclidian geometric space, and all move forward through time at the same speed. Newtonian physics explains many things very well, but couldn't explain other phenomenon.

Going from observation, that the speed of light is constant, regardless of how fast the light emitter is travelling relative to you, he made that the unbreakable assumption, and made the shape of spacetime flexible to always satisfy a constant speed of light. This theory was then confirmed when the light of a distant star was observed to bend when travelling through the strong gravitational field of our sun during a total solar eclipse.

Therefore the physics described by General Relativity have greater predictive power.

Quantum physics, can also predict everything in general relativity, but doing so is a lot more complicated than using general relativity. However, Quantum Physics can explain things that happen on small scales that General Relativity cannot. Quantum Physics has greater predictive power, but it's more convoluted. Like Epicycles. Einstein didn't like quantum physics and spent a great deal of time trying to debunk it, but, well, he couldn't.

This is all to point out that one should not confuse predictive power with complexity. Ockham's Razor is a rule of thumb that prefers "simpler" explanations for things. But the predictive power of the two competing theories must be equal for that to apply.

[YeGoblynQueenne]

Thanks, I didn't kow about Einstein and quantum physics. I'll have to read a bit about that, it sounds interesing.

My original comment is grounded in an assumption that predictive power is not enough to identify a theory as correct, and neither is simplicity. There's nothing to stop any number of theories to have the same predictive power and the same kind of complexity. Sometimes, it's just very difficult to choose one, above the others.

Did I come across as confusing predictive power with complexity?

EDIT: it's interesting you bring Occam's razor up. It's part of what I'm studying, in the context of identifying relevant information in (machine) learning. There are mathematical results (in the framework of PAC-learning) that say that, basically, the more complex your training data, the more likely you are to overfit to irrelevant details. At that point, you have a model that explains observations perfectly well, but is useless to explain unseen observations (the really unseen ones- not those pretending to be unseen for the puprose of cross-validation).

...iiish. The result is that large hypothesis spaces tend to produce higher error. But, the size of the hypothesis space in statistical machine learning depends on the complexity of the data, as in the number of features. Anyway, I'm fudging it some. I'm still reading up on that stuff.

[Koshkin]

> Quantum physics, can also predict everything in general relativity

Unfortunately, the two theories, while both being extremely successful and accurate in their predictions, are incompatible with one another. Quantum Field Theory has successfully combined Quantum Mechanics with Special Relativity, but that is all.

[XorNot]

We need to to be specific here though: they are compatible at low energies. They only become incompatible at very high energy states like those shortly after the big bang, and those we can't produce easily in particle accelerators.

Which is to say: they break under conditions very unlike the every-day universe, which is important but also indicative that they are not that broken.

The incompatibility is important though, because if there's any more card tricks we can do with physics so we can do interesting things, somewhere in that bit of incompatibility is where we must find it.

[ZenPsycho]

thanks for letting me know- I’m not a physicist so I knew I was probably putting my foot in my mouth somewhere.

maybe some day we’ll find the grand unifying theory of the universe.