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Register a new userExtracting galaxy merger timescales I: Tracking haloes with WhereWolf and spinning orbits with OrbWeaver
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Hierarchical models of structure formation predict that dark matter halo assembly histories are characterised by episodic mergers and interactions with other haloes. An accurate description of this process will provide insights into the dynamical evolution of haloes and the galaxies that reside in them. Using large cosmological N-body simulations, we characterise halo orbits to study the interactions between substructure haloes and their hosts, and how different evolutionary histories map to different classes of orbits. We use two new software tools - WhereWolf, which uses halo group catalogues and merger trees to ensure that haloes are tracked accurately in dense environments, and OrbWeaver, which quantifies each halos orbital parameters. We demonstrate how WhereWolf improves the accuracy of halo merger trees, and we use OrbWeaver to quantify orbits of haloes. We assess how well analytical prescriptions for the merger timescale from the literature compare to measured merger timescales from our simulations and find that existing prescriptions perform well, provided the ratio of substructure-to-host mass is not too small. In the limit of small substructure-to-host mass ratio, we find that the prescriptions can overestimate the merger timescales substantially, such that haloes are predicted to survive well beyond the end of the simulation. This work highlights the need for a revised analytical prescription for the merger timescale that more accurately accounts for processes such as catastrophic tidal disruption.
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Predicting the merger timescale ($tau_{rm merge}$) of merging dark matter halos, based on their orbital parameters and the structural properties of their hosts, is a fundamental problem in gravitational dynamics that has important consequences for our understanding of cosmological structure formation and galaxy formation. Previous models predicting $tau_{rm merge}$ have shown varying degrees of success when compared to the results of cosmological $N$-body simulations. We build on this previous work and propose a new model for $tau_{rm merge}$ that draws on insights derived from these simulations. We find that published predictions can provide reasonable estimates for $tau_{rm merge}$ based on orbital properties at infall, but tend to underpredict $tau_{rm merge}$ inside the host virial radius ($R_{200}$) because tidal stripping is neglected, and overpredict it outside $R_{200}$ because the host mass is underestimated. Furthermore, we find that models that account for orbital angular momentum via the circular radius $R_{rm circ}$ underpredict (overpredict) $tau_{rm merge}$ for bound (unbound) systems. By fitting for the dependence of $tau_{rm merge}$ on various orbital and host halo properties,we derive an improved model for $tau_{rm merge}$ that can be applied to a merging halo at any point in its orbit. Finally, we discuss briefly the implications of our new model for $tau_{rm merge}$ for semi-analytical galaxy formation modelling.
The cosmic web plays a major role in the formation and evolution of galaxies and defines, to a large extent, their properties. However, the relation between galaxies and environment is still not well understood. Here we present a machine learning approach to study imprints of environmental effects on the mass assembly of haloes. We present a galaxy-LSS machine learning classifier based on galaxy properties sensitive to the environment. We then use the classifier to assess the relevance of each property. Correlations between galaxy properties and their cosmic environment can be used to predict galaxy membership to void/wall or filament/cluster with an accuracy of $93%$. Our study unveils environmental information encoded in properties of haloes not normally considered directly dependent on the cosmic environment such as merger history and complexity. Understanding the physical mechanism by which the cosmic web is imprinted in a halo can lead to significant improvements in galaxy formation models. This is accomplished by extracting features from galaxy properties and merger trees, computing feature scores for each feature and then applying support vector machine to different feature sets. To this end, we have discovered that the shape and depth of the merger tree, formation time and density of the galaxy are strongly associated with the cosmic environment. We describe a significant improvement in the original classification algorithm by performing LU decomposition of the distance matrix computed by the feature vectors and then using the output of the decomposition as input vectors for support vector machine.
We present a theoretical analysis of some unexplored aspects of relaxed Bose-Einstein condensate dark matter (BECDM) haloes. This type of ultralight bosonic scalar field dark matter is a viable alternative to the standard cold dark matter (CDM) paradigm, as it makes the same large-scale predictions as CDM and potentially overcomes CDMs small-scale problems via a galaxy-scale de Broglie wavelength. We simulate BECDM halo formation through mergers, evolved under the Schrodinger-Poisson equations. The formed haloes consist of a soliton core supported against gravitational collapse by the quantum pressure tensor and an asymptotic $r^{-3}$ NFW-like profile. We find a fundamental relation of the core=to-halo mass with the dimensionless invariant $Xi equiv lvert E rvert/M^3/(Gm/hbar)^2$ or $M_{rm c}/M simeq 2.6 Xi^{1/3}$, linking the soliton to global halo properties. For $r geq 3.5 ,r_{rm c}$ core radii, we find equipartition between potential, classical kinetic, and quantum gradient energies. The haloes also exhibit a conspicuous turbulent behavior driven by the continuous reconnection of vortex lines due to wave interference. We analyse the turbulence 1D velocity power spectrum and find a $k^{-1.1}$ power-law. This suggests the vorticity in BECDM haloes is homogeneous, similar to thermally-driven counterflow BEC systems from condensed matter physics, in contrast to a $k^{-5/3}$ Kolmogorov power-law seen in mechanically-driven quantum systems. The mode where the power spectrum peaks is approximately the soliton width, implying the soliton-sized granules carry most of the turbulent energy in BECDM haloes.
The concentration parameter is a key characteristic of a dark matter halo that conveniently connects the halos present-day structure with its assembly history. Using Dark Sky, a suite of cosmological $N$-body simulations, we investigate how halo concentration evolves with time and emerges from the mass assembly history. We also explore the origin of the scatter in the relation between concentration and assembly history. We show that the evolution of halo concentration has two primary modes: (1) smooth increase due to pseudo-evolution; and (2) intense responses to physical merger events. Merger events induce lasting and substantial changes in halo structures, and we observe a universal response in the concentration parameter. We argue that merger events are a major contributor to the uncertainty in halo concentration at fixed halo mass and formation time. In fact, even haloes that are typically classified as having quiescent formation histories experience multiple minor mergers. These minor mergers drive small deviations from pseudo-evolution, which cause fluctuations in the concentration parameters and result in effectively irreducible scatter in the relation between concentration and assembly history. Hence, caution should be taken when using present-day halo concentration parameter as a proxy for the halo assembly history, especially if the recent merger history is unknown.
We introduce and apply a new approach to probe the response of galactic stellar haloes to the interplay between cosmological merger histories and galaxy formation physics. We perform dark-matter-only, zoomed simulations of two Milky Way-mass hosts and make targeted, controlled changes to their cosmological histories using the genetic modification technique. Populating each historys stellar halo with a semi-empirical, particle-tagging approach then enables a controlled study, with all instances converging to the same large-scale structure, dynamical and stellar mass at $z=0$ as their reference. These related merger scenarios alone generate an extended spread in stellar halo mass fractions (1.5 dex) comparable to the observed population. Largest scatter is achieved by growing late ($zleq1$) major mergers that spread out existing stars to create massive, in-situ dominated stellar haloes. Increasing a last major merger at $zsim2$ brings more accreted stars into the inner regions, resulting in smaller scatter in the outskirts which are predominantly built by subsequent minor events. Exploiting the flexibility of our semi-empirical approach, we show that the diversity of stellar halo masses across scenarios is reduced by allowing shallower slopes in the stellar mass--halo mass relation for dwarf galaxies, while it remains conserved when central stars are born with hotter kinematics across cosmic time. The merger-dependent diversity of stellar haloes thus responds distinctly to assumptions in modelling the central and dwarf galaxies respectively, opening exciting prospects to constrain star formation and feedback at different galactic mass-scales with the coming generation of deep, photometric observatories.
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