Hi all, I recently attempted to reproduce fig 3 of Hallman et al. ApJ 671:27 (2007) using HaloProfiler. I've attached a png of the plot for those of you unfamiliar with it. It was made on three of the L7 datasteps, z=0.1, 1.0 and 2.0. After some trials and tribulations (of my own creation), I was able to pretty closely reproduce the z=0.1 results using yt. However, the z=1.0 and 2.0 lines are quite a bit different. I have a very ugly plot which I could share, but the punchline is my two lines are quite a bit lower in overall count to the Hallman fig. I am trying to figure out the source of this difference. I have access to Brian's L7 directories on gpfswan where he ran HOP for these datasets. With ythop I can create the exact same halo lists. Well, actually, there is a small deviation in particle counts for a small subset of the haloes, but they're all well less than 1% of the total number of particles in that halo. Of course, the halo centers and radii are what's important, and the centers are nearly identical to Brian's data. I also found the files that list the virial quantities for these datasets that made the Hallman figure, and I confirmed it by overplotting the data on top of the Hallman figure. I can't quote specifics because Kraken's scratch is stuck right now, but comparing the old data to the HaloProfiler data for z=2.0 I saw that the old data had nearly twice as many virial mass values, and those virial masses were roughly twice what HaloProfiler gives. The old virial radius was also roughly twice the HaloProfiler value. In order to try to understand this differences, I've inspected the code that calculated the old virial stats. I've put a quick summary below of how it was done. It appears to be different than how yt does it, but I still haven't figured out where a factor of roughly two can come from. There are those on this list who can better summarize how yt does it. I know I haven't fully investigated this, but I'd like to start the discussion anyway. I need to ask Rick what he used for the input halo radii below. I ran a quick test using HaloProfiler with double the input radius for each halo and it didn't change the virial radius or number of haloes very much, so for HaloProfiler (at least) it's not a very sensitive variable in that direction. # read in the enzo data grids, for an input halo define a sphere for each grid quick check to see if the left and right edges of grid are inside the sphere compute some physical constants (like densityconversion) for each grid cell compute the distance from the *center* of the cell to the center of the sphere, with periodic boundary conditions considered if that distance is less than the full sphere for n in bins (equally logarithmically spaced) if that distance is less than the radius of the bin gas_mass=cell_dens * cellvolume * densityconversion profile_gas[n] += gas_mass break for each particle compute distance from each particle to the center of the sphere if that distance is less than the size of the sphere for n in bins if that distance is less than the radius of the bin part_mass = particlemass * cellvolume * densityconversion profile_dm[n] += part_mass break # now calculate the virial stuff, first some constants Esquared = OmegaMatterNow * POW(1.0+CurrentRedshift, 3) + OmegaCurvatureNow * POW(1.0+CurrentRedshift, 2) + OmegaLambdaNow; critical_dens = 2.78e11*POW(HubbleConstantNow, 2) * Esquared; for n in bins annulus[n] = profile_gas[n]+profile_dm[n] if n>0 total[n] += annulus[n1] overdensity[n] = total[n] / (POW((radius of bin n+1)*BoxSize, 3) * 4.0*pi/3.0) / critical_dens for n in bins if overdensity[n] <= virial_overdensity rvir = (radius of bin n1) + (size of bin n) * (virial_overdensity  overdensity[n1]) / (overdensity[n]  overdensity[n1] + tiny_number) break mvir = POW(rvir*BoxSize, 3)*4.0/3.0*pi*critical_dens*virial_overdensity _______________________________________________________ sskory@physics.ucsd.edu o__ Stephen Skory http://physics.ucsd.edu/~sskory/ _.>/ _Graduate Student ________________________________(_)_\(_)_______________
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Stephen Skory