They would be deterministic. But they are unpredictable. Minuscule fluctuations (coming from influence of some much smaller bodies, that are not in the model, or approximations in calculations) can lead to dramatic differences in the outcome.

So theoretically speaking, they are deterministic, but practically they are unpredictable.

It's got nothing to do with perturbations from additional small bodies, the problem is exactly mathematically calculating the outcome for exactly three bodies within reasonable time frames even if you assume perfect ideal knowledge about the system. It turns out this is excruciatingly hard.

The n-body problem where you add further bodies, even very small ones, is even harder.

Huh? If this is the case, wouldn’t a 2 body problem also be practically impossible to calculate?

I mean, you can certainly still predict to a certain (probably high) level of accuracy, but ultimately that motion is also influenced by factors outside your model.

The question is what happens with a small perturbation and how does it "grow".

For a two body problem, you nudge one of the bodies and it is forever off by a small amount, but your predictions into infinity require only a small adjustment to compensate.

For a three body problem you nudge one of the bodies and only for a very short time do your previous predictions stay true, the change amplifies until nothing you thought might happen before the nudge means anything at all, and a common occurrence is one of the bodies being ejected.

This is sometimes called "infinite sensitivity to initial conditions" or "deterministic chaos".

> a common occurrence is one of the bodies being ejected.

So the problem eventually solves itself?

Well, not if the ejected body contains you.

Being ejected from your model is unquestionably a solution of sorts, although it does Raise Questions.

Yes, but but also the problem really is: "given some initial condition space, can we estimate the likelihood of ejection (how many conditions in the condition space eject) in X timeframe"?

> For a two body problem, you nudge one of the bodies and it is forever off by a small amount, but your predictions into infinity require only a small adjustment to compensate.

How does this even work? Where is a place in the universe where there are only two bodies?? Where would the nudge come from if not from a third body?! A ghost?

You do an accounting of the nearby massive objects and their distances from each other, pairs of objects within certain bounds of mass and distance can be treated like there are only those two objects in the universe with the understanding that there will be a small error because of outside influences. It’s an approximation, but in the right circumstances a very good one.

Each planet and the sun can be done like this, ignoring all of the other planets. Each moon and its planet can be considered a two body system ignoring the rest of the moons.

If you just randomly generated a bunch of massive bodies and pressed play, you would have few 2 body systems and a lot of chaos, but that’s a problem that solves itself as the chaos results in either collisions or ejections.

You're taking it too literally. The 'nudge' means a change in initial conditions, and could result e.g. from measurement uncertainty, not necessarily a literal nudge.

It also doesn't necessarily matter that much if there are more than two bodies, if the gravitational influence of other bodies is small enough, then you can model as a two body problem.

The “nudge” can also come up even with exact starting information. When you calculate the next step and round it to the nearest nanometer, you’ve just nudged the system by enough to eventually make your prediction worthless in the 3-body case.

The relative magnitude of interactions is important. The article specifically mentioned triple star system as an example. Solar system is of course many body, but (a) it has already settled into (sort of) stable configuration (b) there is one massive body and everything else revolves around it. Yes, massive bodies like gas giants have noticeable affect on other bodies, but due to the distances they tend to be in the stable territory.

No. A small error in the initial conditions of a 2-body system produces a small error in the result. In case of a 3-body system, a small error will result in drastically different outcomes. The phase space of a 2-body system is nice and smooth, but a 3-body system’s is more like a fractal.

For a two-body problem the discrepancies between your model and reality increase gradually with time, but it's still possible to predict eclipses decades in advance with a precise albeit imperfect measurement of initial conditions.

With a three-body problem any slight shift causes a wildly different trajectory, bearing no resemblance to the original so your measurements of the initial condition have to be perfect.

No that's not it. The two body problem has a closed, analytical solution, the three body one doesn't, so you need to simulate it. It's a fundamentally different approach.

That's not really the issue. The three body problem does have an analytical solution in the form of a power series, but the problem is that it converges so slowly to be of any practical use.

It is though, if you don’t have a closed form solution you need to use an iterative process to calculate the positions, meaning errors will accrue over time. For a closed form solution that wouldn’t be the case.

Thanks for mentioning the existence of an analytical solution at all though, I wasn't aware of that.

> meaning errors will accrue over time

This is not universally true. Error behavior is a function of the particular problem, the algorithm used to approximate its solution, and the properties of input data. A large subtopic of numerical analysis is concerned with this kind of stuff. See [1] or [2] to get a flavor.

[1]: https://en.wikipedia.org/wiki/Numerical_stability

[2]: https://en.wikipedia.org/wiki/Lax_equivalence_theorem

There are iterative methods/systems that stabilize over time. For example, symplectic integrators on tame problems oscillate lightly around the true energy of the system over time. The issue here is the properties of the underlying problem, not the set of solution methods.

Both of you are correct.

arent eclipses three body problems?

For all practical purposes eclipses are two two-body problems ... Sun vs Earth-Moon pair, and Earth vs Moon. The scale of the Sun is so vastly larger and distances so great from sun to earth there's no need to do 3-body.

If the three had roughly the same mass would be different story.

Better stated, the 2-body problem can be solved with a finite number of standard operations, i.e. a closed-form expression. This solution does not exist for the 3-body problem.

This is not a requirement for a system to lack chaos, nor is it a metric by which we can judge if a system DOES have chaos.

In principle - yes. Except that we can change our frame of reference, and treat the two body problem as a pseudo one body problem (the lab frame becomes the center of mass of one of the bodies). One cannot do this for the three body problem, which gives us at best a pseudo two body problem.

No, the fundamental difference is that the two-body problem can be solved analytically, you can write down a formula. For three bodies and up you only have numerical solutions, simulations, and they will break down over time.

The problem is that a three-body system is inherently unstable/chaotic. So even if you run a numerical simulation with the same granularity for a two-body and a three-body system, the three-body simulation will degrade much faster than the two-body system. This is unrelated to the fact that there is a closed form solution, there are many stable, non-chaotic dynamical systems that don't have a closed form solution.

Well sure. But my point was that for two bodies you don’t need to simulate at all, you can just get the answer for any point in time.

The need for numerical simulations is completely unrelated to the predictability and/or stability of the system. If you have a Lyapunov exponent smaller than 0 everywhere, errors don't accumulate and you can simulate numerically for as long as you like.

It's not unrelated, but the implication only goes in one direction. If you have a closed form solution, that implies that you can model it completely forever, but sure the opposite is not true.

Conversely, there are also extremely simple closed-form recurrence relations that exhibit chaotic behavior, e.g. the logistic map.

True but a recurrence relationship is not the same as a closed form solution. The differential equation for a three body problem is also very simple.

Of course. My point was just that you can evaluate a recurrence relation exactly (i.e. with zero numerical error) and still get chaotic behavior. OP’s mistaken point was that the three body problem’s chaos arises solely from numerical error during simulation, which is untrue.

Would a linear-feedback shift register be an example of a recurrence relation that exhibits chaotic behavior?

That is not the issue. There are many problems that do not have analytical solutions, but can be approximated numerically to any precision you would like.

The issue with the three-body problem is that it is chaotic, meaning any error will eventually grow to take over the entire solution, making prediction impossible, even in theory. Every chaotic system lacks an analytical solution, but not every system without an analytical solution is chaotic.

I think this is accurate and I don’t understand why you are being downvoted.

I think the issue was more with “random” than with “unpredictable”.

Random doesnt mean non-deterministic anyway.

X is random with respect to Y, if knowing Y makes no difference to your predicting that X.

QM systems are indeterminate, they are random in the above sense /because/ they are indeterminate. But that isnt what random means.

What you're describing is not randomness, it's independence.

It's hard to define randomness. I think non-determinism is better than your definition.

It isn't hard to define randomness. It's an epistemic condition on the knowability of Y given X.

Non-determinism is an incoherent definition of randomness; classical physical processes are entirely deterministic.

The point of a coinflip being random is that it is random with respect to the information both observers of the coinflip have. It isnt random with respect to /any/ piece of information.

There are almost no processes which are non-deterministic in this sense. Not enough to bother calling them random; and in physics we do not: the word is indeterminate. Randomness has nothing to do with quantum mechanics; it wasn't invented in the 1920s. It's an epistemic condition.

The RANDOM variable X, st. X ~ N(mean, std) provides a random number x -- x isnt random with repect to the outcome which produced x; nor is it random with respect to an index of a vector in which it is contained.

This does not match the intuitive notion of randomness though.

I would say for a given variable to be random, it must not be predictible, given any other variables that humans can know.

I don't think it makes sense to say that X is random "with respect to Y", that's just the definition of independence.

And a constant variable is independent from all other variables, but it's definitely not random.

Then only quantum indeterminate phenomenon is random, and nothing else.

I dont think many people have thought enough about the world to appeal to their intuitions.

Randomness isnt quantum indeterminacy.

The motion isn’t deterministic if free will exists. Launching a rocket into space decreases earth’s rotation speed ever so slightly, which will have a small impact on the moon’s trajectory due to tidal interactions, and so on.

Please define 'free will' before using it in a sentence about determinism.

If that was a requirement, discussions of determinism would sound awfully one-sided. ;p

There are those who believe determinism is not only compatible with free will, but required for free will.

https://en.wikipedia.org/wiki/Compatibilism

that case is beyond scope of the three body problem

Edward Lorenz summarized chaotic behavior as: "When the present determines the future, but the approximate present does not approximately determine the future."

So yes, you could predict the locations computationally to an arbitrary point in the future if you knew their starting locations and velocities with perfect precision; but in practice of course you cannot know anything's position with perfect precision, so your simulation would become inaccurate relatively quickly.

edit to add: and I believe that what this paper discusses is not a solution to the above, but rather a way of getting around it by modeling some types of three-body behavior as if it were truly random, rather than chaotically deterministic.

While we can simulate three (or more) bodies' gravitational interaction, the chaoticness means that any error in initial state, no matter how small, will be hugely amplified. This makes long-term predictions untractable

As I understand it, "random and unpredictable" means impossible to measure the initial state in sufficient precision and/or computationally impossible to calculate in a reasonable amount of time.

The actual underlying math is deterministic.

It seems the problem is often mis-stated - there is no calculation problem, the problem is in adequately defining/sampling the initial data.

It's maybe similar to predicting the weather - we can have all the perfect equations in the world for fluid dynamics and heat flow etc, but until we have system-invisible temperature and humidity sensors for every square millimetre of atmosphere and earth volume, we won't be able to predict the weather very accurately or very far ahead.

There are cases in classical mechanics that fail to be deterministic.

https://physics.stackexchange.com/questions/403574/what-situ...

Chaos is the extreme dependence on initial conditions. The three body problem is significantly more chaotic than a two body problem. Welcome to chaos theory!

The initial conditions are usually known up to a small epsilon in practice. I guess this initial error grows exponentially with time, hence "unpredictability".

This exponential increase in error is described by the Lyapunov exponent of the system: https://en.wikipedia.org/wiki/Lyapunov_exponent

You can only do that with some error, e.g. your simulation needs some time step that controls the tradeoff between computational resources used and accuracy of the results. For any fixed time step, after enough time your simulation will completely diverge from reality.

On top of theoretically computable, but highly divergent / unstable functions mentioned nearby, there are fully deterministic (non-random, pure) but non-computable functions. The simplest example is a function that answers whether a given Turing machine would stop.

If you freeze each point in time , isn’t the next minute step deterministic? Every time you freeze, you would have all the motion vectors to calculate the next moment, if you expand that using a lot of computation power, ca you solve it that way?

there is no closed form, like you say, and the additional complexity is around ergodicity, i.e. solutions that start close to each other might end up very far from each other after a certain point. this is also an issue with computer simulations as the error might accumulate and push solutions away. in practice, given the amount of cosmological computations people do on a daily basis, including those for satellites and rockets, this might not necessarily be that big of an issue, but i don't work with that stuff on a daily basis.