Sensitivity of dark matter haloes to their accretion histories

Abstract

We apply our recently proposed "quadratic genetic modification" approach to generating and testing the effects of alternative mass accretion histories for a single $\Lambda$CDM halo. The goal of the technique is to construct different formation histories, varying the overall contribution of mergers to the fixed final mass. This enables targeted studies of galaxy and dark matter halo formation's sensitivity to the smoothness of mass accretion. Here, we focus on two dark matter haloes, each with four different mass accretion histories. We find that the concentration of both haloes systematically decreases as their merger history becomes smoother. This causal trend tracks the known correlation between formation time and concentration parameters in the overall halo population. At fixed formation time, we further establish that halo concentrations are sensitive to the order in which mergers happen. This ability to study an individual halo's response to variations in its history is highly complementary to traditional methods based on emergent correlations from an extended halo population.

Matching accepted version in MNRAS. Results and conclusions unchanged

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Cited by in corpus (24)

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• Caught in the cosmic web: Environmental effect on halo concentrations, shape, and spin
• Cosmology dependency of halo masses and concentrations in hydrodynamic simulations
• GenetIC -- a new initial conditions generator to support genetically modified zoom simulations
• Does Concentration Drive the Scatter in the Stellar-to-Halo Mass Relation of Galaxy Clusters?
• EDGE: What shapes the relationship between HI and stellar observables in faint dwarf galaxies?
• VINTERGATAN-GM: The cosmological imprints of early mergers on Milky-Way-mass galaxies
• How cosmological merger histories shape the diversity of stellar haloes
• EDGE: The emergence of dwarf galaxy scaling relations from cosmological radiation-hydrodynamics simulations
• Insights into the origin of halo mass profiles from machine learning
• Mass accretion rates of clusters of galaxies: CIRS and HeCS
• Explaining dark matter halo density profiles with neural networks
• Mock halo catalogs: assigning unresolved halo properties using correlations with local halo environment
• Exploring the effects of primordial non-Gaussianity at galactic scales
• MultiCAM: A multivariable framework for connecting the mass accretion history of haloes with their properties
• Evaluating the variance of individual halo properties in constrained cosmological simulations
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• The impact of baryons on the sparsity of simulated galaxy clusters from The Three Hundred Project
• Timing the last major merger of galaxy clusters with large halo sparsity