CWRU PAT Coffee Agenda

Tuesdays 10:30 - 11:30 | Fridays 11:30 - 12:30

+2 Why Boltzmann Brains Are Bad.

oxg34 +1 gds6 +1

+1 Understanding the non-linear clustering of high redshift galaxies.

mro28 +1

+1 Does a generalized Chaplygin gas correctly describe the cosmological dark sector?.

sxk1031 +1

Showing votes from 2017-02-03 12:30 to 2017-02-07 11:30 | Next meeting is Friday May 22nd, 11:30 am.

users

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astro-ph.CO

  • Why Boltzmann Brains Are Bad.- [PDF] - [Article]

    Sean M. Carroll
     

    Some modern cosmological models predict the appearance of Boltzmann Brains: observers who randomly fluctuate out of a thermal bath rather than naturally evolving from a low-entropy Big Bang. A theory in which most observers are of the Boltzmann Brain type is generally thought to be unacceptable, although opinions differ. I argue that such theories are indeed unacceptable: the real problem is with fluctuations into observers who are locally identical to ordinary observers, and their existence cannot be swept under the rug by a choice of probability distributions over observers. The issue is not that the existence of such observers is ruled out by data, but that the theories that predict them are cognitively unstable: they cannot simultaneously be true and justifiably believed.

  • Understanding the non-linear clustering of high redshift galaxies.- [PDF] - [Article]

    Charles Jose, Carlton M. Baugh, Cedric G. Lacey, Kandaswamy Subramanian
     

    We incorporate the non-linear clustering of dark matter halos, as modelled by Jose et al. (2016) into the halo model to better understand the clustering of Lyman break galaxies (LBGs) in the redshift range $z=3-5$. We find that, with this change, the predicted LBG clustering increases significantly on quasi-linear scales ($0.1 \leq r\,/\,h^{-1} \,{\rm Mpc} \leq 10$) compared to that in the linear halo bias model. This in turn results in an increase in the clustering of LBGs by an order of magnitude on angular scales $5" \leq \theta \leq 100"$. Remarkably, the predictions of our new model remove completely the systematic discrepancy between the linear halo bias predictions and the observations. The correlation length and large scale galaxy bias of LBGs are found to be significantly higher in the non-linear halo bias model than in the linear halo bias model. The resulting two-point correlation function retains an approximate power-law form in contrast with that computed using the linear halo bias theory. We also find that the non-linear clustering of LBGs increases with increasing luminosity and redshift. Our work emphasizes the importance of using non-linear halo bias in order to model the clustering of high-z galaxies to probe the physics of galaxy formation and extract cosmological parameters reliably.

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