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Register a new userA Halo Merger Tree Generation and Evaluation Framework
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Semi-analytic models are best suited to compare galaxy formation and evolution theories with observations. These models rely heavily on halo merger trees, and their realistic features (i.e., no drastic changes on halo mass or jumps on physical locations). Our aim is to provide a new framework for halo merger tree generation that takes advantage of the results of large volume simulations, with a modest computational cost. We treat halo merger tree construction as a matrix generation problem, and propose a Generative Adversarial Network that learns to generate realistic halo merger trees. We evaluate our proposal on merger trees from the EAGLE simulation suite, and show the quality of the generated trees.
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We examine the effect of using different halo finders and merger tree building algorithms on galaxy properties predicted using the GALFORM semi-analytical model run on a high resolution, large volume dark matter simulation. The halo finders/tree builders HBT, ROCKSTAR, SUBFIND and VELOCIRAPTOR differ in their definitions of halo mass, on whether only spatial or phase-space information is used, and in how they distinguish satellite and main haloes; all of these features have some impact on the model galaxies, even after the trees are post-processed and homogenised by GALFORM. The stellar mass function is insensitive to the halo and merger tree finder adopted. However, we find that the number of central and satellite galaxies in GALFORM does depend slightly on the halo finder/tree builder. The number of galaxies without resolved subhaloes depends strongly on the tree builder, with VELOCIRAPTOR, a phase-space finder, showing the largest population of such galaxies. The distributions of stellar masses, cold and hot gas masses, and star formation rates agree well between different halo finders/tree builders. However, because VELOCIRAPTOR has more early progenitor haloes, with these trees GALFORM produces slightly higher star formation rate densities at high redshift, smaller galaxy sizes, and larger stellar masses for the spheroid component. Since in all cases these differences are small we conclude that, when all of the trees are processed so that the main progenitor mass increases monotonically, the predicted GALFORM galaxy populations are stable and consistent for these four halo finders/tree builders.
Linking the properties of galaxies to the assembly history of their dark matter haloes is a central aim of galaxy evolution theory. This paper introduces a dimensionless parameter $sin[0,1]$, the tree entropy, to parametrise the geometry of a halos entire mass assembly hierarchy, building on a generalisation of Shannons information entropy. By construction, the minimum entropy ($s=0$) corresponds to smoothly assembled haloes without any mergers. In contrast, the highest entropy ($s=1$) represents haloes grown purely by equal-mass binary mergers. Using simulated merger trees extracted from the cosmological $N$-body simulation SURFS, we compute the natural distribution of $s$, a skewed bell curve peaking near $s=0.4$. This distribution exhibits weak dependences on halo mass $M$ and redshift $z$, which can be reduced to a single dependence on the relative peak height $delta_{rm c}/sigma(M,z)$ in the matter perturbation field. By exploring the correlations between $s$ and global galaxy properties generated by the SHARK semi-analytic model, we find that $s$ contains a significant amount of information on the morphology of galaxies $-$ in fact more information than the spin, concentration and assembly time of the halo. Therefore, the tree entropy provides an information-rich link between galaxies and their dark matter haloes.
We present TreeFrog, a massively parallel halo merger tree builder that is capable comparing different halo catalogues and producing halo merger trees. The code is written in c++11, use the MPI and OpenMP APIs for parallelisation, and includes python tools to read/manipulate the data products produced. The code correlates binding energy sorted particle ID lists between halo catalogues, determining optimal descendant/progenitor matches using multiple snapshots, a merit function that maximises the number of shared particles using pseudo-radial moments, and a scheme for correcting halo merger tree pathologies. Focusing on VELOCIraptor catalogues for this work, we demonstrate how searching multiple snapshots spanning a dynamical time significantly reduces the number of stranded halos, those lacking a descendant or a progenitor, critically correcting poorly resolved halos. We present a new merit function that improves the distinction between primary and secondary progenitors, reducing tree pathologies. We find FOF accretion rates and merger rates show similar mass ratio dependence. The model merger rates from Poole et al, (2017) agree with the measured net growth of halos through mergers.
We present a new algorithm for generating merger trees and halo catalogs which explicitly ensures consistency of halo properties (mass, position, and velocity) across timesteps. Our algorithm has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. In addition, our method is able to robustly measure the self-consistency of halo finders; it is the first to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistency between snapshots in cosmological simulations. We use this algorithm to generate merger trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders track halos extremely well; in both, the number of halos which do not have physically consistent progenitors is at the 1-2% level across all halo masses. Our code is publicly available at http://code.google.com/p/consistent-trees . Our trees and catalogs are publicly available at http://hipacc.ucsc.edu/Bolshoi/ .
We present 610 MHz and 2.1 GHz imaging of the massive SZE-selected z=0.870 cluster merger ACT-CL J0102-4915 (El Gordo), obtained with the GMRT and the ATCA, respectively. We detect two complexes of radio relics separated by 3.4 (1.6 Mpc) along the systems NW-to-SE collision axis that have high integrated polarizations (33%) and steep spectral indices, consistent with creation via Fermi acceleration by shocks in the ICM. From the spectral index of the relics, we compute a Mach number of 2.5^{+0.7}_{-0.3} and shock speed of 2500^{+400}_{-300} km/s. With our ATCA data, we compute the Faraday depth across the NW relic and find a mean value of 11 rad/m^2 and standard deviation of 6 rad/m^2. With the integrated line-of-sight gas density derived from new Chandra observations, our Faraday depth measurement implies B_parallel~0.01 mu G in the cluster outskirts. The extremely narrow shock widths in the relics (<23 kpc) prevent us from placing a meaningful constraint on |B| using cooling time arguments. In addition to the relics, we detect a large (1.1 Mpc radius), powerful (log L_1.4[W/Hz]= 25.66+-0.12) radio halo with a Bullet-like morphology. The spectral-index map of the halo shows the synchrotron spectrum is flattest near the relics, along the collision axis, and in regions of high T_gas, all locations associated with recent energy injection. The spatial and spectral correlation between the halo emission and cluster X-ray properties supports primary-electron processes like turbulent reacceleration as the halo production mechanism. The halos integrated 610 MHz to 2.1 GHz spectral index is 1.2+-0.1, consistent with the clusters high T_gas in view of previously established global scaling relations. El Gordo is the highest-redshift cluster known to host a radio halo and/or radio relics, and provides new constraints on the non-thermal physics in clusters at z>0.6. [abridged]
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