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Comment by amelius | Hacker News Reader

Perhaps a stupid question, but why can't the whole experiment be run as a simulation?

Even if this would be the dream of a lot of theoretical physicists to replace experiments with simulations, this must not happen! Ever! Even if every complex system in the world could be simulated in reasonable time it would still require experiments to verify or falsify the simulation results. A simulation is essentially just a calculation from a model someone came up with to describe a system. In order to check how good the model is one has to check it against experimental data. Just expanding the models without experimental verification will not necessarily result in a good theoretical description. It would be like writing software without testing the components and expecting it to work correctly when you're done. There was recently an article on HN where economists were described as the astrologers of our time [1] since they do not verify their mathematical models to an extent where they can predict economical systems. This is another example where more experimental data should be considered in order to falsify certain theories.

Those are the reasons why string-theorist will not (and should not) get any Nobel price in the next decades. Since its predictions are hard to measure on those small scales there's no way of telling if the model is any good until it is compared against suitable experimental data.

[1] https://aeon.co/essays/how-economists-rode-maths-to-become-o...

Agreed. My background is philosophy, and while i rarely get into the STEM arguments. This has everything to do with inductive learning vs deductive learning. Any simulation will be run with the premises already built in, but cutting edge science is always about learning what those premises are. If we knew what they were, it'd be trivial to set up the reactor. Here we need inductive experimentation to learn how to simulate it trivially.

I believe this is more about solving an engineering/mathematics problem, than about fundamental physics and the scientific process.

Physics is a lot more than just fundamental physics. H-Bomb designs for example get hundreds of hours of super computer time to simulate a few pounds of stuff for 1/1,000th of a second and even then they are approximations which need to be validated.

Thanks, this is the best HN 'rant for the common sense' in a long time :)

If you're doing science, experiments are hugely important. If you're doing engineering and you're reasonably sure that the physics guys came up with a good model, having everything in a computer would make development a lot cheaper.

Because fusion simulations are really hard. This simulation[1] took 15 million hours of CPU time to model a cubic cm of plasma. The results were used to update 5 scalar parameters in a model.

[1] http://news.mit.edu/2016/heat-loss-fusion-reactors-0121

Does anyone have an idea about what software they use to simulate this stuff?

I'm wondering if they can even make use of the newfound GPU power or are just going ahead with ancient CPU based software because too much work has already been put in.

SpaceX is doing the best work on simulation. The adaptive multiscale work is a million times more important this moving to GPU, but of course they did that too:

https://www.nextplatform.com/2015/03/27/rockets-shake-and-ra...

Looks interesting. It looks like they are creating the CFD software for their own specific application. While that's cool and all, I doubt any other companies have the resources/motivation to write complex software from scratch, let alone underfunded postdocs.

I'm wondering about all the research that goes on in all the universities where large investments have been made on CPU based clusters. The simulation in the article you linked was run on NERSC servers, which are Cray supercomputers[1], which pretty much are Intel Xeon class servers with fancy interconnects.

So looks like it is CPU based, but I'm still interested in the software they use.

[1]: https://my.nersc.gov/nowcomputing-cs.php

It's usually highly-parallelized Fortran ran on the world's largest supercomputers, utilizing thousands of CPU cores. There are several codes like the ones in the study above (google "gyrokinetic equation solver"), and somehow more pop up year by year. So it's not a matter of sunk costs.

And yes, GPUs are increasingly being utilized, depending on the algorithm. But, GPUs aren't magic; they don't speed up every kind of problem.

The numbers are too big, and nature is hiding stuff from us.

So we can't simulate it because we don't know enough to simulate it. And even if we did know there's not enough computing power to do so.

The system is fundamentally 6^N dimensional with N~10^23.

Yeah, 6^N dimensions are fun! ;)

I suppose you meant 6*N? Which is a lot better, but still intractable. And anyway, we don't exactly resolve molecules in e.g. turbulent flow simulations, yet they still take tens, even hundreds of millions of CPU-hours.

6*N, yes. Pretty bad mistake there. But yes, even if you don't model every particle and restrict yourself to "parcels" of fluid like in most simulations, you still have a very difficult problem.

Okay, this is really showing my ignorance but why 6?

You start off with 4 (3 space plus one time (ignoring 11-dimensional space-time)) and add which dimensions exactly? Can the individual interactions between wave/particles be reduced to 2 dimensions? Aren't they going to interact along the whole range of forces they exert: gravitational, weak, electromagnetic, strong?

3 dimensions for position + 3 dimensions for speed

3 dimensions for momentum in other words? Surely it cannot be that simple. That's astounding.

Unless you consider quantum effects, which are probably relevant in this situation, then it's an exponentially larger problem space.

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