eachus said:
Lol! And definitely not disagreeing. You did see my comment about choosing inputs to a simulation? Without real hard numbers about what dark matter is, slight changes in the model inputs result in outputs that support just about any model.
That's not true, though. As I said earlier, the simulations are only unreliable on small scales. On large scales, the results are highly robust, and match with observation very well.
eachus said:
If the simulation says, "No, you are wrong!" great. Falsifying models is the goal. But you learn nothing from simulations, if the best you can say is "I think the initial conditions required to get this result are extreme and unlikely."
Also false, because our models of the universe also set the initial conditions.
The main problem with simulations is resolution. While in principle we know most of the physics that goes into the simulations, it's generally not feasible to simulate things all the way down to the level of stars, which is actually necessary to get the right answer from first principles (supernova explosions have large, far-reaching effects on galactic evolution, for instance). So it's not so much a problem of initial conditions as it is a problem that there are a number of complex phenomena going on which are, in principle, known, but we can't actually simulate them. What we need to do, then, is formulate some fudge factors that sort of sweep the underlying complexities under the rug, and then estimate those fudge factors either by observation or with small-scale simulations.
So really, the problem with simulations is
not an initial conditions problem. It's a computational problem. It's a problem of finding the right approximations to the physics we know so that the answer is still reliable.
But, at the very least, the large-scale results are independent of these small-scale complexities, and so there is no problem at large scales.