Phase-space structure of cold dark matter haloes inside splashback: multistream flows and self-similar solution

Sugiura, Hiromu; Nishimichi, Takahiro; Taruya, Atsushi

doi:10.1093/mnras/staa413

Cited by 24 publications

(28 citation statements)

References 62 publications

(81 reference statements)

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“…It merely reflects the self-similar nature of the dynamics in phase-space (Alard 2013). Such selfsimilarity is also clearly suggested by the direct measurements of the history of orbits of particles in dark matter halos (Sugiura et al 2020). While the logarithmic slope of Q(r) changes little with time, we saw in previous section that the density profile presents some striking transformations during the course of the dynamics.…”

Section: Time Evolution: Pseudo Phase-space Densitysupporting

confidence: 64%

“…It should be noted that the pre-collapse phase (i) of the evolution of the phase-space sheet is well described by perturbation theory; however, the early violent relaxation phase (ii) and the convergence to the universal dynamical attractor (iii) are still poorly understood from the theoretical point of view despite numerous investigations involving maximum of entropy methods (e.g., Lynden-Bell 1967;Hjorth & Williams 2010;Pontzen & Governato 2013;Carron & Szapudi 2013), the Jeans equation (e.g., Taylor & Navarro 2001;Dehnen & McLaughlin 2005;Ogiya & Hahn 2018), post-collapse perturbation theory (e.g., Colombi 2015;Taruya & Colombi 2017;Rampf et al 2019), as well as self-similar solutions and secondary infall models (e.g., Fillmore & Goldreich 1984;Bertschinger 1985;Henriksen & Widrow 1995;Sikivie et al 1997;Zukin & Bertschinger 2010a,b;Alard 2013;Sugiura et al 2020). It is not the goal in the present work to investigate in detail analytical models, but some links between our measurements and predictions from self-similarity and solutions of the Jeans equations are discussed.…”

Section: Introductionmentioning

confidence: 99%

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Phase-space structure of protohalos: Vlasov versus particle-mesh

Colombi

2021

A&A

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The phase-space structure of primordial dark matter halos is revisited using cosmological simulations with three sine waves and cold dark matter (CDM) initial conditions. The simulations are performed with the tessellation based Vlasov solver ColDICE and a particle-mesh (PM) N-body code. The analyses include projected density, phase-space diagrams, radial density ρ(r), and pseudo-phase space density: Q(r) = ρ(r)/σv(r)3 with σv the local velocity dispersion. Particular attention is paid to force and mass resolution. Because the phase-space sheet complexity, estimated in terms of total volume and simplex (tetrahedron) count, increases very quickly, ColDICE can follow only the early violent relaxation phase of halo formation. During the violent relaxation phase, agreement between ColDICE and PM simulations having one particle per cell or more is excellent and halos have a power-law density profile, ρ(r) ∝ r−α, α ∈ [1.5, 1.8]. This slope, measured prior to any merger, is slightly larger than in the literature. The phase-space diagrams evidence complex but coherent patterns with clear signatures of self-similarity in the sine wave simulations, while the CDM halos are somewhat scribbly. After additional mass resolution tests, the PM simulations are used to follow the next stages of evolution. The power law progressively breaks down with a convergence of the density profile to the well-known Navarro–Frenk–White universal attractor, irrespective of initial conditions, that is even in the three-sine-wave simulations. This demonstrates again that mergers do not represent a necessary condition for convergence to the dynamical attractor. Not surprisingly, the measured pseudo phase-space density is a power law Q(r) ∝ r−αQ, with αQ close to the prediction of secondary spherical infall model, αQ ≃ 1.875. However this property is also verified during the early relaxation phase, which is non-trivial.

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Section: Time Evolution: Pseudo Phase-space Densitysupporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Phase-space structure of protohalos: Vlasov versus particle-mesh

Colombi

2021

A&A

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“…4). It would be a challenging undertaking to obtain a numerically reliable, converged distribution of orbit counts at all N orb (see Sugiura et al 2020, for an attempt).…”

Section: Orbit Counting Algorithmmentioning

confidence: 99%

“…The two-scale nature of the orbiting term On a particle level, the orbiting term represents the superposition of the phase space occupied by its constituent orbits (e.g., Lithwick & Dalal 2011;Sugiura et al 2020), much like for stars in a galaxy (Schwarzschild 1979). Assuming that the distribution of total particle energies is limited by some maximum, there must be a corresponding spatial (radial) cutoff roughly at the scale where the halo's potential reaches that maximum (as visualized in Figs.…”

Section: 1mentioning

confidence: 99%

“…A cut in phase space cannot achieve this goal because the two populations overlap in the radial range of interest (see Figs. 2 and 3;Fukushige & Makino 2001;Diemand & Kuhlen 2008;Cuesta et al 2008;Sugiura et al 2020), although approximate cuts are useful when classifying observed satellite distributions (e.g., Tomooka et al 2020;Aung et al 2021).…”

Section: Introductionmentioning

confidence: 99%

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A dynamics-based density profile for dark haloes. I. Algorithm and basic results

Diemer

2021

Preprint

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The density profiles of dark matter haloes can potentially probe dynamics, fundamental physics, and cosmology, but some of the most promising signals reside near or beyond the virial radius. While these scales have recently become observable, the profiles at large radii are still poorly understood theoretically, chiefly because the distribution of orbiting matter (the one-halo term) is partially concealed by particles falling into halos for the first time. We present an algorithm to dynamically disentangle the orbiting and infalling contributions by counting the pericentric passages of billions of simulation particles. We analyse dynamically split profiles out to 10 R 200m across a wide range of halo mass, redshift, and cosmology. We show that the orbiting term experiences a sharp truncation at the edge of the orbit distribution. Its sharpness and position are mostly determined by the mass accretion rate, confirming that the entire profile shape primarily depends on halo dynamics and secondarily on mass, redshift, and cosmology. The infalling term also depends on the accretion rate for fast-accreting haloes but is mostly set by the environment for slowly accreting haloes, leading to a diverse array of shapes that does not conform to simple theoretical models. While the resulting scatter in the infalling term reaches 1 dex, the scatter in the orbiting term is only between 0.1 and 0.4 dex and almost independent of radius. We demonstrate a tight correspondence between the redshift evolution in ΛCDM and the slope of the matter power spectrum.

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Anisotropy and characteristic scales in halo density gradient profiles

Wang

2022

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We use a large N -body simulation to study the characteristic scales in the density gradient profiles in and around halos with masses ranging from 10 12 to 10 15 h −1 M . We investigate the profiles separately along the major (T1) and minor (T3) axes of the local tidal tensor and how the characteristic scales depend on halo mass, formation time, and environment. We find two prominent features in the gradient profiles: a deep "valley" and a prominent "peak". We use the Gaussian process regression to fit the gradient profiles and identify the local extrema in order to determine the scales associated with these features. Around the valley, we identify three types of distinct local minima, corresponding to caustics of particles orbiting around halos. The appearance and depth of the three caustics depend on the direction defined by the local tidal field, formation time, and environment of halos. The first caustic is located at r > 0.8R200, corresponding to the splashback feature, and is dominated by particles at their first apocenter after infall. The second and third caustics, around 0.6R200 and 0.4R200, respectively, can be determined reliably only for old halos. The three caustics are consistent with the prediction of self-similar gravitational collapse. The first caustic is always the most prominent feature along T3, but may not be true along T1 or in azimuthally averaged profiles, suggesting that caution must be taken when using averaged profiles to investigate the splashback radius. We find that the splashback feature is approximately isotropic when proper separations are made between the first and the other caustics. We also identify a peak feature located at ∼ 2.5R200 in the density gradient profile. This feature is the most prominent along T1 and is produced by mass accumulations from the structure outside halos. We also discuss the origins of these features and their observational implications.

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Phase-space structure of cold dark matter haloes inside splashback: multistream flows and self-similar solution

Cited by 24 publications

References 62 publications

Phase-space structure of protohalos: Vlasov versus particle-mesh

Phase-space structure of protohalos: Vlasov versus particle-mesh

A dynamics-based density profile for dark haloes. I. Algorithm and basic results

Anisotropy and characteristic scales in halo density gradient profiles

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