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Comment by colordrops | Hacker News Reader

The author says that he "became more convinced [string theorists] are merely building a mathematical toy universe." The explanation for his conclusion was that they kept revising string theory in order to fit observations. I know little of string theory, so I am probably misreading his meaning, but isn't that how all science works? Create a model, then revise it when you get more data.

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True, of course. But at some indeterminate point theories start seeming awfully ad-hoc even if they still retain other properties.

Let's say I propose that no existing solar panel designs respond to artificial light. Easily falsifiable. Say you perform the experiment and find that panels from First Solar do respond to artificial light. I refine my hypothesis to "no existing solar panel designs respond to artificial light except for First Solar". You find that SunEdison panels do, by testing at your lab in SF. I refine my hypothesis to "no existing solar panel designs respond to artificial light when tested outside San Francisco except for First Solar". You repeat the experiment in San Jose, and I refine my hypothesis again.

We're revising the model, keeping it falsifiable, and keeping it consistent with existing evidence. It would not be without merit to claim that this is something of a toy hypothesis, however, and that our time would be better served otherwise.

This sounds like the scientific equivalent of "overfitting" in machine learning. The point of a theory is not to predict the training set well, but to generalize well to new cases. This is what string theory fails at.

NNs are modeled after the human brain. It's not an immensely crazy to point out that we could be overfitting ourselves by continuously exposing ourselves to a single theory.

The successful backpropagation algorithm works completely different from anything that has been observed in the human brain up to now.

You misunderstand, first: it is not the case that new observations about the world forced the changes. Instead, it is mostly observations about the internal properties of string theory which has forced modifications.

After it was proposed as a self-consistent theory of quantum gravity it was realized it wasn't self-consisten because it had ghosts, which was then fixed by adding 22 dimensions. But this is a problem because that's not how many dimensions the world has so they solved it by compactification that folds all the extra dimensions tiny so they don't bother us. But then it turns out that there is no particular reason to fold just so so that we get the world we live in. And now they are trying to find a way to make it so its natural that the folding happens just so that we get the world we live in.

Secondly, and most importantly, while it is true that some models get revised whenever there is more data, those are poor models. Good models agree with all the data and don't need modification. (The best models agree with most of the data, but sometimes don't so that the scientist gets a mystery to solve!) Realistically this stage takes a while to happen, and proponents of string theory argue that they right now have a models that is going to be great one day, but right now needs a bit of tinkering. What critics say is that string theory has been in the "tinkering" stage for around 50 years now and maybe we should try other ideas a bit more.

Finally, I don't think Sabine likes being refereed to as a "he" and rather have that pronoun used to describe the father of her children rather than herself.

Don't the "best" models make surprising predictions that we go out of our way to design experiments to collect data for - and find that they are, in fact, accurate?

Has string theory made a single prediction anyone went out of their way to test, finding it accurate?

I don't have a problem with shoveling in a bunch of dimensions. If it's shovelled in carefully so as not to predict anything that can be tested, I can get that entertainment from watching flat Earth videos though.

> Don't the "best" models make surprising predictions that we go out of our way to design experiments to collect data for - and find that they are, in fact, accurate?

Models like e.g. the heliocentric solar system, or even relativity, weren't developed that way - they were developed by noticing flaws or incompatibilities in existing models, and proposing a better explanation for them. (The much-touted "experimental verification" of relativity in an eclipse was a nonsense - the errors were as large as the measurements - but it didn't matter; the theory was elegant enough to be obviously correct).

String theory is mostly still at the fiddling-with-the-epicycles-and-thought-experiments stage. But at least it has a model that contains a) standard QM and b) a graviton. None of the competition has even got that far (and there's little reason to think they ever will in most cases).

Well, nothing describes how "all science works", but ideally you don't revise your model based on new data. Instead, you take all of the data you have, both old and new, start over from scratch and try to find the simplest model that would account for it. What your old favorite model used to be, before you obtained the new data, should not play any role in your evaluation of competing models.

Given how real people and organizations work, psychology, resource limitations, incentives, etc., this is VERY idealistic, but still, imagine that you had found your data in a different order, so you ended up with the same data you have now, but had a different subset previously. With two different subsets in the past, your best past models might have been different from each other, but your best choice now should be the same now that both paths have converged on the same data. So why should your choice in the past have a "vote" in your choice now?

So (again, ideally), don't "revise" your old model; take the data you have now, old and new, pretend you are starting from scratch, and choose the best model. If a theory such as String Theory keeps failing to account for new data and is repeatedly modified to keep it from being disqualified, a reasonable question would be whether, if we started from scratch knowing what we know now, we would come up with this repeatedly patched String Theory version as our first choice.

(And, yes, I know that from a Bayesian perspective you can't literally start "from scratch", but that doesn't mean you have to use your most recent model as your prior).

It's called adding epicycles : http://rationalwiki.org/wiki/Adding_epicycles

I mostly agree, but I'd argue that epicycles actually made useful and testable predictions, although we found a simpler description later on. The article underlines a lack of refutable theories. Thus, I think [1] is a better analogy.

[1] http://rationalwiki.org/wiki/The_Dragon_in_My_Garage

The characteristic of metaphorical epicycles is that the make simple, testable predictions that are then wrong, which are fixed with another epicycle.

Another more subtle aspect of epicycles, real ones this time, is that they are too powerful and can be used to prove anything. You can predict the motion of the planets with epicycles, it's just that the required series is very long or infinite. And with very long series of cycles, you can "predict" anything: https://youtu.be/QVuU2YCwHjw?t=25s Thus, one of the problems with epicycles both real and metaphorical is that they are indeed not refutable. Because epicycles can predict anything, they aren't that useful; they exclude far less than meets the eye at first.

It isn't hard to see that characterist showing up in string theory. The theory has for a very long time had problems with excluding possibilities, and each new metaphorical "epicycle" seems to come with more parameters than the last, rather than fewer. Now, this isn't unique to string theory since all the current theories seem to have that problem, but then, the point is, why does this problematic theory have so much more support and money than the other problematic theories?

>Another more subtle aspect of epicycles, real ones this time, is that they are too powerful and can be used to prove anything.

String theorists talk about how rich and complex the mathematics is, but maybe that just means it has so many possibilities you can always come up with an explanation to overcome newly-discovered difficulties.

Whack realization of the day for me at least.

Epicycles --> Taylor series.

They're more closely related to the Fourier transforms. That's how somebody calculated the actual values that would yield Homer.

Perhaps off-topic, but I really like the classification of that article:

This might be Skepticism but we're not sure

What's wrong with that? Epicycles are a good testable model. They were discarded when a better one was developed.

Well that's really all that is wrong with it: you are adding epicycles instead of working on a better theory. In analogy: once a language is turing complete you can do anything in it, so you can keep using brainfuck to make a gui, but probably it would be easier in java...

What's wrong is that you're trying to make a round peg fit a square role.

The problem was not that it was discarded, but what happened between new data and getting discarded and how long it took.

You don't want Epicycles because theories should be "simple" and Epicycles are added exceptions

The revision in the face of observations relies on them being new observations. You can make an almost infinite number of models that fit existing knowledge; the way you figure out which one to go with is by having the model make testable (falsifiable) predictions, and then test those predictions. The string theory revisions, however, seem to fall out of conflicts between the theory and existing observations (like, say, that the dimensionality of our physical space is 3, or that the cosmological constant is non-positive).

For example, general relativity could make Newtonian mechanics fall out as a low-mass, low-velocity special case, and solved the already-known theoretical problem of the constant speed of light, but there a lot of conceivable models that could solve that. To be accepted, its predictions needed to be tested (starting with gravitational lensing in the 1919, and going through higher-precision tests later).

This is related to the problem of overfitting in machine learning. You can get a system to be very very familiar with your training data, so it can predict the things it has already seen. However, until you have validated it on data it wasn't trained on, you don't know if the model reflects any of the underlying properties of the system it's observing.

Theories serve multiple purposes. A theory can be useful to make calculations about things you already know. Or to make predictions about things you don't yet know. String theory has been adapted over time to be able to calculate things we already know. But we already had that without string theory. But the predictive part is where string theory really falls down. It's track record there is abysmal.

On the other end of the predictive spectrum there's Einstein. Somebody fiddles with the equations and says, "if this is right then there could be black holes!" And then... they find black holes. It seems that every few years there's some confirmation of an odd corner case that shows the predictive power of Einstein's theories.

That string theory can calculate the known might still be useful, if it's a more convenient way to get the results than other theories. Plain old Newtonian physics is still hella useful today, for instance, even for space missions. AFAIK, string theory is not more convenient.

Take this with a grain of salt, because I haven't kept up on what string theory has been doing lately. As a matter of personal triage I stopped following it until such time as I heard that someone predicted something interesting with it, and it was confirmed in observation or experiment. If that happened then I missed it, and would love to hear about it.

The author is a she.

The point is that a theory is only scientific it if it's falsifiable. That is, it makes a prediction, you go into the lab and do an experiment, and if the experiment comes out differently than the prediction, you know the theory was wrong.

The author and I got the impression that string "theory" (let's call it "string hypothesis" instead?) has so many degrees of freedom that it can predict basically anything you throw at it, even things we now know aren't physical, so its predictive value is zero.

Think of it this way :

"I have solved all of math, physics, and everything else ! Look ! My theory is simply the assembly programming language. Any problem can be expressed in it and anything that we can predict we can predict using some assembly language".

You wouldn't consider this to actually predict anything, right ? Despite the statement being perfectly true. Change any prediction into the assembly program printing it out. Done/done. So the critique of string theory is that it is such a form of assembly language. It is a general principle, that can express nearly any algorithm.

So generally one considers that any theory, for it to be a theory, has to predict things unrelated to why it was originally designed, with no changes (or at the very least, very minimal changes). Quantum theory, for instance, was designed to solve a particular problem relating to electrons, but turned out to solve the ultraviolet catastrophe (and dozens of other problems).

It is not obvious that the Universe is computable. https://en.wikipedia.org/wiki/Digital_physics

Think flat world, and the plethora of adjustments that astronomers introduced to it when observations conflicted with theory. As some point you have to throw the towel and come up with a completely different explanation of whatever you're observing.

Maybe you meant the geocentric model of the cosmos developed by Apollonius, Hipparchus, and Ptolemy, full of epicycles and so on? (As contrasted with the heliocentric “Copernican” model.)

Every serious astronomer in the West (indeed, every educated person) has known that the earth is round for about 2500 years. The idea that medieval Europeans believed in a flat Earth is largely a modern myth. See https://en.wikipedia.org/wiki/Myth_of_the_flat_Earth

Science also prescribes that you use the smallest (simplest) model that fits the data. String theory arguably does not adhere to that.

Yes. But you must generally increase the predictive power of the theory for it to makes sense - otherwise you are creating a religion or mythos. After all - that was how the ancients explained the world - this rock is here because Hercules was mad and threw it all the way from the Danube.

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