Recreating Our Galaxy in a Supercomputer
caltech.edu
Recreating Our Galaxy in a Supercomputer
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Re: Recreating Our Galaxy in a Supercomputer
#2For context, this question of whether vanilla dark matter models are in conflict with galactic observations has been raging for many years. (It includes both the dwarf galaxy problem mentioned in the article, and things like the "core-cusp" problem concerning the radial dark matter density distribution.) These numerical simulations are fiendishly complicated, and there's always a risk that you just keep adding new tweaks or effects until you get the results you're looking for. I'd be interested in reading a skeptical assessment from the folks on the other side of this question.
Re: Recreating Our Galaxy in a Supercomputer
#3Can somebody who knows about this tell me how much of the novelty in this is CS and how much physics? For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better. Is this the case here? Or is it adding new models?
Re: Recreating Our Galaxy in a Supercomputer
#4Nice, you can't model a worm, but you can model a galaxy.
Re: Recreating Our Galaxy in a Supercomputer
#5Apropos, the Gaia space telescope's first data release is next week. It's an extremely large dataset of the kinematics (3d position + velocity) of Milky Way stars.
Re: Recreating Our Galaxy in a Supercomputer
#6Can somebody who knows about this tell me how much of the novelty in this is CS and how much physics? For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better. Is this the case here? Or is it adding new models?
For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better.
Nitpick: The physics of light is understood. Human vision is also understood. But critically, human vision is completely overlooked in most graphical applications. It's not accurate to say that "the path toward making a computer-generated video indistinguishable from a camcorder recording is just a matter of sampling better." There will need to be a fundamental shift in the industry's thinking before realism will be achieved.
It's a fascinating topic that occupied many years of my life, though this is a bit off-topic.
Re: Recreating Our Galaxy in a Supercomputer
#7Can somebody who knows about this tell me how much of the novelty in this is CS and how much physics? For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better. Is this the case here? Or is it adding new models?
> Can somebody who knows about this tell me how much of the novelty in this is CS and how much physics?
It's a little bit of both. Over the past 5–8 years, some new numerical techniques ("moving mesh") have been developed (or at least first applied in astronomy) for hydrodynamic simulations[0,1]. These new techniques do a much better job of handling fluid instabilities, which can be important for properly simulating the gas in galaxies (which can have a huge range in densities and temperatures).
Also, people have developed what they call "cosmological zoom" simulations. In these simulations, you run a low-resolution (sometimes dark-matter only) simulation of a fairly large volume of the universe. Then you identify a particular dark matter halo at the end, that you think matches the type of galaxy you're interested in (say, a Milky Way type galaxy). Then you go back to the initial conditions, re-initialize it at very high resolution and include "normal matter" (baryons) and re-simulate the whole thing to study the formation of that particular dark matter halo and its associated galaxy.
Finally, the general increase in computing speed has allowed people to add in more physics to the simulations and run higher-resolution simulations. In this case, it is the addition of a physically-motivated model for energy injection into the gas in galaxies, from the ongoing star formation. This means energy from supernovae explosions and associated shocks, stellar winds, and momentum from scattering/absorption of photons by dust grains[2,3]. This more realistic set of models manages to reproduce the overall efficiency of star formation (what fraction of the gas gets turned into stars over some period of time) _and_ create a realistic temperature-density structure for the gas.
Now that people seem confident that these models can reproduce the overall star formation properties in galaxies, they are starting to see what this type of star formation / feedback model implies for the properties of galaxies. Of course, there's still lots of work to be done in making detailed tests of these models. While they reproduce the overall efficiency of star formation, we aren't yet sure if they can reproduce the shapes and sizes of galaxies. But people are working on that and we should know before too long...
[0] https://arxiv.org/abs/0901.4107
[1] https://arxiv.org/abs/1409.7395
Re: Recreating Our Galaxy in a Supercomputer
#8Can somebody who knows about this tell me how much of the novelty in this is CS and how much physics? For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better. Is this the case here? Or is it adding new models?
And if these image comes from the simulation... Where is the stars bar around the core ??
Re: Recreating Our Galaxy in a Supercomputer
#9Can somebody who knows about this tell me how much of the novelty in this is CS and how much physics? For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better. Is this the case here? Or is it adding new models?
For example in graphics all the physics of light is well understood - it's just infeasible to compute - so all advances are in CS and how to sample better. Nitpick: The physics of light is understood. Human vision is also understood. But critically, human vision is completely overlooked in most graphical applications. It's not accurate to say that "the path toward making a computer-generated video indistinguishable f…
I'm curious. What do you mean by "Human vision is completely overlooked"? Are you talking about color perception? 3d rendering?
Thanks :)
Re: Recreating Our Galaxy in a Supercomputer
#10Nice, you can't model a worm, but you can model a galaxy.