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> MOND can make many successful a priori predictions about observations that LCDM needs to fit a posteriori using a "tuned" distribution of dark matter. those
by Avshalom 4y ago
> MOND can make many successful a priori predictions about observations that LCDM needs to fit a posteriori using a "tuned" distribution of dark matter.
those are the same predictions you'd get if you just set dark matter at a single uniform universal distribution. which is again, exactly what every attempt at explaining mond just ends up doing anyway... but then there's also those things that disagree with mond rendering the need for introducing a bunch of new stuff on top of it anyway.
and that's the thing mond leads us to dark matter plus extra stuff. Occam's razor is hardly an absolute truth but we like it and we can explain things without the extra stuff.
it's also like a real fucking brain worm to call "matter follows a statistical distribution": tuning or more parameters like the sibling post does. "Matter follows a statistical distribution" is what we already see in all the matter we see.
- throwawaymaths 4y agoWrong. Those models require tuning for every observation with extremely fragile parameters to get correct with LCDM, if you assume that LCDM particles are particulate and have individual momenta; in other words given the variation in momentum and density that we see in galaxies as a whole the odds that every single galaxy have exactly the right parameters to make the basic galactic curves work out is extremely low, and it's worse once you take into account stuff EFE
- simonh 4y agoNot every galaxy does follow the behaviour that indicates a “standard” distribution of dark matter though, some seem to have a lot less, or straightforwardly behave as expected without it. Often these are galaxies that have undergone collisions and the theory is that the dark matter was stripped away in the collision. MOND can’t account for these galaxies at all, hence MOND theories end up introducing ad hoc fields or versions of dark matter anyway. Personally, the way I think about dark matter is that it’s a map of the variances we see between the expected behaviour and actual behaviour of galaxies. That’s it. That’s it’s a distribution of gravitating matter is one possibility. That would fit the observations, so it’s a reasonable working hypothesis, that’s all. MOND simply doesn’t describe the distribution of the effects we see. It does in many common cases, but not all by a long way and the variance is different from case to case, so it still leaves a gap we’d need to fill with something else.
- throwawaymaths 4y agoThere's an n of 1 that is unexplainable by MOND, and that's the bullet cluster. Pretty much every other Galaxy is explainable using mond, the udgs for example are likely to be errors in distance to them, a lot of other errors due to being oriented face towards us, etc. Iirc, LCDM has trouble explaining satellite galaxies. They're traveling through the halo, which should create drag on them. They shouldn't last long enough to exist at all.
- simonh 4y agoFor individual galaxies yes the bullet cluster is the main problem, but MOND can’t explain the motion of galaxy clusters at all.
- throwawaymaths 4y ago> MOND can’t explain the motion of galaxy clusters at all Yes that's fine, but it also doesn't necessarily try to [1]. LCDM can't explain linear Tully-fisher, can't explain external field effect, can't explain why satellite galaxies are long lived, can't explain why bullet cluster even exists (galaxies shouldn't be going that fast), can't explain early galaxies, etc. [1] so maybe it shouldn't. There's a lot of systematic uncertainty in some of those really large scale movements. For example suppose our standard candle was off by half an order of magnitude at the largest scales. For LCDM, not a problem. Reparametrize the distribution and ratios of dark matter. Presto chango theory still works. That this should be possible should scare you.
- naasking 4y ago> but then there's also those things that disagree with mond rendering the need for introducing a bunch of new stuff on top of it anyway. And LCDM does this too. If you want a comprehensive survey of the tuning done by each model to fit observations, see: https://arxiv.org/abs/2110.06936v3 https://arxiv.org/abs/2110.06936v3 It seems clear that neither approach is satisfactory as they stand, but the resistance to recognizing the significant flaws in LCDM is frankly puzzling.