
Why not string theory? Because enough is enough - Santosh83
https://backreaction.blogspot.com/2016/06/dear-dr-b-why-not-string-theory.html
======
Steuard
Speaking as a professor specializing in string theory, I'd say, "More power to
her." I have no idea whether string theory gets too much attention relative to
its actual value in modeling the real world, but I think one essential part of
finding the right amount of attention for any physical theory is for theorists
to make their best judgement about what's worth their time to study.

In fact, it's quite comforting to me to see people deciding to focus in other
directions: to my eye, that means the system is working (though perhaps the
author would argue it's not working efficiently), and I'd hate to see other
worthwhile angles of attack wither away purely due to lack of attention. For
myself, I got excited about string theory in grad school and decided to go
that route, and I'm still finding it fascinating today. (And it still feels
worthwhile to keep studying it, though perhaps I'm not quite as optimistic
about its ultimate success as I was 15 years ago.)

~~~
tamana
So you feel strong theory connects to reality, and is falsifiable and avoids
"piling on epicycles"?

Will string theory be more parsimonious than the the more concrete model of
physics it tries to model?

~~~
4ad
Of course string theory is falsifiable. String theory reduces to quantum field
theory in some limit and to general relativity in some other limit. Unlike all
the other previous theories, string theory is the theory that has resisted all
efforts to falsify it yet.

It's a ridiculous misconception floating around that string theory can't make
predictions, when in fact string theory is the only theory we have so far that
predicts all known observed phenomena.

~~~
cygx
_String theory reduces to quantum field theory in some limit and to general
relativity in some other limit._

That's nice and clearly shows why string theory research is a worthwhile
endeavor, but you only get a gold star once you make an experimentally
verified _new_ prediction. There is a reason why people were excited about the
discovery of the Higgs boson.

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dnautics
"[A]cademia is currently organized so that it invites communal reinforcement,
prevents researchers from leaving fields whose promise is dwindling, and
supports a rich-get-richer trend."

A really awesome quote there. (Perhaps a bit self-serving for me).

~~~
ellyagg

        (Perhaps a bit self-serving for me).
    

So you think she's biased in pointing out that academia has systemic biases?

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dnautics
sorry, that parsed poorly.

It's a bit self serving for _me_. I operate a science nonprofit outside of
traditional academia.

~~~
ellyagg
Yeah, I realized later it was possible to interpret that sentence another way.
I think my downvoter thought I was making a dumb throwaway snark, but I was
actually just confused.

~~~
dnautics
well it's not an expected situation that anyone runs a science nonprofit, so
your confusion is understandable.

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tim333
I've got a theory that string theory is more of a sociological phenomena than
real science. It started as a genuine attempt to model how the nucleus was
held together and then continued because it's a good area to do maths and
write papers rather than because it models reality.

One thing I don't get, which may be down to my own stupidity - take maybe the
simplest interaction in physics - you have two electrons in space a few cm
apart and the accelerate away from each other due to the charges repelling.
I'm not sure how that is supposed to happen if everything is strings. Do they
ping tiny strings at each other and how do they know which way to aim? Maybe
some string person can enlighten me.

~~~
TheOtherHobbes
>I've got a theory that string theory is more of a sociological phenomena than
real science.

Yes. I have a friend with a PhD in physics, and he says that a generation of
string theory people basically just shouted everyone else down in a rather
obnoxious way. Other critics (e.g. Lee Smolin) have said similar things,
albeit slightly more politely.

At some point it stopped being science and became more about careers,
reputations, funding, and paper mills. Which, given the way that academia
works at the moment, became self-sustaining.

Some interesting math has fallen out of string theory, but it should never
have been allowed to hold back other approaches to quantum gravity to the
extent that it has.

Considering the amount of time and paper involved, there's a huge wall of
maybe-perhaps-if but very little solid physics to show for the effort.

Incidentally, that blog is a real find - some of the clearest explanations of
hard concepts I've seen anywhere.

~~~
tim333
It reminds me a little of the phenomena of efficient market theory in
economics / finance. Academics were drawn to it partly because it enables them
to do a lot of fancy mathematics whereas if you look at inefficiencies like
the stuff that went on in the movie The Big Short then the academics don't
really have much of an edge against people working in the field. So much
academic stuff goes 'assuming efficient markets', blah blah... which is not
actually wrong but maybe a misallocation of resources from looking at bubbles
and crashes which could have helped avoid the whole 2006 episode.

I agree the blog seems very good.

~~~
eru
It gets more complicated, because there are various `strengths' of efficient
market hypotheses around. The weaker ones are obviously true, but the stronger
ones are more suspect.

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colordrops
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.

~~~
throwaway43
It's called adding epicycles :
[http://rationalwiki.org/wiki/Adding_epicycles](http://rationalwiki.org/wiki/Adding_epicycles)

~~~
yoha
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](http://rationalwiki.org/wiki/The_Dragon_in_My_Garage)

~~~
jerf
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](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?

~~~
Gibbon1
Whack realization of the day for me at least.

Epicycles --> Taylor series.

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

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visarga
This is probably a naive question: can we input a bunch of particle
interactions into a deep learning system and train it to predict the
probability of future interactions? It would be like a "black box version" of
physics. If we can predict, then we can find a more elegant mathematical
notation and a more intuitive physical interpretation.

Machine learning can observe and learn patterns that are more complex than
humans can grasp. What if the perfect Physics theory is more complex than
humans can understand and possibly quite unintuitive in meaning? Then we won't
like it and steer away from it, and that would be a bad thing in the end.

~~~
espadrine
> _Machine learning can observe and learn patterns that are more complex than
> humans can grasp._

That is a common misconception. ML cannot do anything beyond our modeling
ability because it is designed with it. Deep learning is simply a method to
approximate a function with a nonlinear formula. Something that cannot be
easily approximated this way may require too much memory and power to be
practical.

It is fundamentally similar to how JPEG is not a good fit for storing text:
glyphs are hard to approximate with Fourier transforms.

The edge that ML has against humans is not in the learning part, it is in the
machine part. Human memory is volatile, while we have grown exceedingly good
at making machines retain memory.

~~~
return0
That is not a valid argument. You need to provide a reason why the patterns
that machine learning grasps are all graspable by humans, or that humans grasp
something that machine learning never will. Multilayer neural networks can
capture very interesting (from a human perspective) patterns and concepts, but
also many others that seem garbage to us (perhaps because we dont grasp their
significance).

~~~
espadrine
Give me a ML system, and I can give you a problem it cannot solve. I am
guaranteed success thanks to the No Free Lunch theorem:
[https://en.wikipedia.org/wiki/No_free_lunch_theorem](https://en.wikipedia.org/wiki/No_free_lunch_theorem).

In the case of deep learning, I can point to the task of determining values
above 0.5 on an infinite Perlin-noise-derived 2D space fed by Mersenne Twister
with seed 0, with an infinite number of octaves. Deep learning does not deal
well with infinite spaces to begin with, and the pseudo-random generator
cannot be easily encoded with common neural network nonlinear functions.

On the other hand, while we cannot compute an infinite number of octaves, and
while places extremely far or extremely small details will run into IEEE754
limitations, we will get a good approximation by writing the program that
computes the texture.

And that is just with only two numbers as input and one number as output.

~~~
j-pb
Sure, I choose... "Exhaustive Search in the space of programs". (maybe with
some genetic algorithm heuristics to shave of a couple billion years on each
query)

It's a ML system that can solve any decidable and even some semi decidable
problems. Which is (if the church turing thesis holds) everything that can be
understood by humans or other.

You might not be able to wait around long enough to see it give you a result
though, but hey at least _it_ got an answer.

~~~
espadrine
If you allow impractical ML systems, you might as well pick a dice. Sure, the
answer is inaccurate, but there's a non-zero probability that it is correct!

But, realistically, the ML system you devise cannot learn about features that
require knowledge outside of the observable universe.

~~~
j-pb
How does a static dice model computational processes?

What does the universe have to do with the set of computable functions?

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woodandsteel
The author is taking a different approach called phenomenological quantum
gravity that has some promise to be more productive in the long term.

[http://backreaction.blogspot.com/2013/06/phenomenological-
qu...](http://backreaction.blogspot.com/2013/06/phenomenological-quantum-
gravity.html)

From what I understand, she and others are trying to understand what empirical
differences a quantum gravity theory of any sort would have, and hopefully
will come up with one that can be experimentally observed, which in turn would
help people figure out what is the correct quantum gravity theory.

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kordless
> Even with that problem fixed, however, it was quickly noticed that moving
> the superpartners out of direct reach would still induce flavor changing
> neutral currents that, among other things, would lead to proton decay and so
> be in conflict with observation.

Dissonance strikes again!

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cygnus_a
i vote we change the name. "generalized quantum mechanical phenomena maybe"
... and we can rename quantum gravity to "generalized macroscopic versions of
quantum phenomena maybe"

then we can add the "maybe" suffix to all the rest of our theories

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stesch
Article isn't about TCL.

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spectrum1234
This ties in with my thinking that there is just too much funding to do
research for the sake of research. Let the private sector work on moonshots if
they want but more realistically no one should be researching super far out
problems. Instead the agile "just in time" approach needs to be used in
academia as well as private companies.

A good analogy is no one was trying to build electric cars fifty years ago but
now they are. But they only are because progress has been made indirectly in
other fields to make it worth it now.

~~~
MawNicker
Babbage designed a computer almost 200 years ago. We need people to be working
on moonshots. A lot of them will fail. When one finally succeeds it pierces
the veil of "just in time" capitalistic motivation. The financial incentive is
certainly perverse in this case. Everyone sells their ideas up front in a
frenzied competition to _exist_. We need a lot _more_ research for the sake of
research. More varied and more useless. We need to find a way for people like
Babbage to exist, at scale, while seeking whatever intrinsic motivations drive
them. We likely won't be able to know if they're doing anything useful until
they're done. Academia needs the ivory tower.

