text: 255,58,971754575349932032,610427323,Desika Narayanan,"New paper! <LINK> . We postprocess massive zooms with RT to make 'observables' -- Non-parametric merger indicators G-M20 and C-A work super well at low-z, but the complex morphology from highly clustered evirons makes measures fail at high-z 4 massive gals. So for things that might end up as centrals in z=0 groups/clusters, our current non-parametric methods don't perform much better than randomly guessing. Extra fun fact: paper is my first-ever student led one, and by a super awesome former @haverfordedu undergraduate! @conselice Thanks for the comments Chris! The replies are somewhat multifaceted. First, these simulations are cosmological zooms, which means we follow individual galaxies at high-res, but don't have statistics. So we can't generate statistics for merger rates. @conselice Second, part of the point of the paper is that G-M20 and C-A may not have success at determining merger rates, at least for very massive systems at high-z.  Of course there are other methods for determining merger rates, though I can't speak to their accuracy in this regime. @conselice The point being -- it's not clear that we can compare the rates from the simulations to the observations when the false positive rate from observations may be significant. @conselice Finally, a bit of a philosophical point: should it matter what the rate normalization is? Ideally, a merger identifier should identify mergers regardless of the rate, with a minimal false positive rate. @conselice On the Petrosian radii, I'll point you to the 7 pages of methods! Not to defer, but it's nontrivial to summarize in N characters or less :)  But will be very happy to hear your comments on them.",https://arxiv.org/abs/1803.02374,"Non-parametric morphology measures are a powerful tool for identifying galaxy mergers at low redshifts. We employ cosmological zoom simulations using Gizmo with the Mufasa feedback scheme, post-processed using 3D dust radiative transfer into mock observations, to study whether common morphological measures Gini G, M20, concentration C, and asymmetry A are effective at identifying major galaxy mergers at z ~ 2 - 4, i.e. ""Cosmic Noon"". Our zoom suite covers galaxies with 10^8.6 < M_* < 10^11 M_sun at z ~ 2, and broadly reproduces key global galaxy observations. Our primary result is that these morphological measures are unable to robustly pick out galaxies currently undergoing mergers during Cosmic Noon, typically performing no better than a random guess. This improves only marginally if we consider whether galaxies have undergone a merger within the last Gyr. When also considering minor mergers, galaxies display no trend of moving towards the merger regime with increasing merger ratio. From z = 4 -> 2, galaxies move from the non-merger towards the merger regime in all statistics, but this is primarily an effect of mass: Above a given noise level, higher mass galaxies display a more complex outer morphology induced by their clustered environment. We conclude that during Cosmic Noon, these morphological statistics are of limited value in identifying galaxy mergers. ","Identifying Mergers Using Quantitative Morphologies in Zoom Simulations