We investigate the build-up of the halo profile out to large scale in a cosmological simulation, focusing on the roles played by the recently proposed depletion radii. We explicitly show that halo growth is accompanied by the depletion of the environment, with the inner depletion radius demarcating the two. This evolution process is also observed via the formation of a trough in the bias profile, with the two depletion radii identifying key scales in the evolution. The ratio between the inner depletion radius and the virial radius is approximately a constant factor of 2 across redshifts and halo masses. The ratio between their enclosed densities is also close to a constant of 0.18. These simple scaling relations reflect the largely universal scaled mass profile on these scales, which only evolves weakly with redshift. The overall picture of the boundary evolution can be broadly divided into three stages according to the maturity of the depletion process, with cluster halos lagging behind low mass ones in the evolution. We also show that the traditional slow and fast accretion dichotomy of halo growth can be identified as accelerated and decelerated depletion phases respectively.
Mock member stars for 28 dwarf galaxies are constructed from the cosmological Auriga simulation, which reflect the dynamical status of realistic stellar tracers. The axis-symmetric Jeans Anisotropic Multi-Gaussian Expansion (JAM) modeling is applied to 6,000 star particles for each system, to recover the underlying matter distribution. The stellar or dark matter component individually is poorly recovered, but the total profile is constrained more reasonably. The mass within the half-mass radius of tracers is recovered the tightest, and the mass between 200 and 300 pc, $M(200-300\mathrm{pc})$, is constrained ensemble unbiasedly, with a scatter of 0.167 dex. If using 2,000 particles and only line-of-sight velocities with typical errors, the scatter in $M(200-300\mathrm{pc})$ is increased by $\sim$50%. Quiescent Sagittarius dSph-like systems and star-forming systems with strong outflows show distinct features, with $M(200-300\mathrm{pc})$ mostly under-estimated for the former, and likely over-estimated for the latter. The biases correlate with the dynamical status, which is a result of contraction motions due to tidal effects in quiescent systems or galactic winds in star-forming systems, driving them out of equilibrium. After including Gaia DR3 proper motion errors, we find proper motions can be as useful as line-of-sight velocities for nearby systems at $<\sim$60 kpc. By extrapolating the actual density profiles and the dynamical constraints down to scales below the resolution, we find the mass within 150 pc can be constrained ensemble unbiasedly, with a scatter of $\sim$0.255 dex. In the end, we show that the contraction of member stars in nearby systems is detectable based on Gaia DR3 proper motion errors.
We propose a random forest (RF) machine learning approach to determine the accreted stellar mass fractions ($f_\mathrm{acc}$) of central galaxies, based on various dark matter halo and galaxy features. The RF is trained and tested using 2,710 galaxies with stellar mass $\log_{10}M_\ast/M_\odot>10.16$ from the TNG100 simulation. For galaxies with $\log_{10}M_\ast/M_\odot>10.6$, global features such as halo mass, size and stellar mass are more important in determining $f_\mathrm{acc}$, whereas for galaxies with $\log_{10}M_\ast/M_\odot \leqslant 10.6$, features related to merger histories have higher predictive power. Galaxy size is the most important when calculated in 3-dimensions, which becomes less important after accounting for observational effects. In contrast, the stellar age, galaxy colour and star formation rate carry very limited information about $f_\mathrm{acc}$. When an entire set of halo and galaxy features are used, the prediction is almost unbiased, with root-mean-square error (RMSE) of $\sim$0.068. If only using observable features, the RMSE increases to $\sim$0.104. Nevertheless, compared with the case when only stellar mass is used, the inclusion of other observable features does help to decrease the RMSE by $\sim$20%. Lastly, when using galaxy density, velocity and velocity dispersion profiles as features, which represent approximately the maximum amount of information one can extract from galaxy images and velocity maps, the prediction is only slightly improved. Hence, with observable features, the limiting precision of predicting $f_\mathrm{acc}$ is $\sim$0.1, and the multi-component decomposition of galaxy images should have similar or larger uncertainties. If the central black hole mass and the spin parameter of galaxies can be accurately measured in future observations, the RMSE is promising to be further decreased by $\sim$20%.
We combine constraints from linear and nonlinear scales, for the first time, to study the interaction between dark matter and dark energy. We devise a novel N-body simulation pipeline for cosmological models beyond $\Lambda$CDM. This pipeline is fully self-consistent and opens a new window to study the nonlinear structure formation in general phenomenological interacting dark energy models. By comparing our simulation results with the SDSS galaxy-galaxy weak lensing measurements, we are able to constrain the strength of interaction between dark energy and dark matter. Compared with the previous studies using linear examinations, we point to plausible improvements on the constraints of interaction strength by using small scale information from weak lensing. This improvement is mostly due to the sensitivity of weak lensing measurements on nonlinear structure formation at low redshift. With this new pipeline, it is possible to look for smoking gun signatures of dark matter-dark energy interaction.
ABSTRACT Recently, a new population of circular radio (∼GHz) objects has been discovered at high Galactic latitudes, called the odd radio circles (ORCs). A fraction of the ORCs encircles massive galaxies in the sky with stellar mass ∼1011 M⊙ situated at z = 0.2–0.6, suggesting a possible physical connection. In this paper, we explore the possibility that these radio circles originate from the accretion shocks/virial shocks around massive (${\gtrsim} 10^{13}\, \ {\rm M}_\odot$) dark matter halo at z ∼ 0.5. We found that the radio flux density of the emitting shell is marginally consistent with the ORCs. We also find that pure advection of electrons from the shock results in a radio-emitting shell that is considerably narrower than the observed one due to strong inverse-Compton cooling of electrons. Instead, we show that the diffusion of cosmic-ray (CR) electrons plays a significant role in increasing the width of the shell. We infer a diffusion coefficient, $D_{\rm cr} \sim 10^{30}\ {\rm cm^2\, s^{-1}}$, consistent with the values expected for low-density circumgalactic medium (CGM). If ORCs indeed trace virial shocks, then our derived CR diffusion coefficient represents one of the few estimations available for the low-density CGM. Finally, we show that the apparent discrepancy between ORC and halo number density can be mitigated by considering an incomplete halo virialization and the limited radiation efficiency of shocks. This study therefore opens up new avenues to study such shocks and non-thermal particle acceleration within them. Furthermore, our results suggest that low-mass galaxies (≲1013 M⊙) may not show ORCs due to their significantly lower radio surface brightness.
We propose a random forest (RF) machine learning approach to determine the accreted stellar mass fractions ($f_\mathrm{acc}$) of central galaxies, based on various dark matter halo and galaxy features. The RF is trained and tested using 2,710 galaxies with stellar mass $\log_{10}M_\ast/M_\odot>10.16$ from the TNG100 simulation. For galaxies with $\log_{10}M_\ast/M_\odot>10.6$, global features such as halo mass, size and stellar mass are more important in determining $f_\mathrm{acc}$, whereas for galaxies with $\log_{10}M_\ast/M_\odot \leqslant 10.6$, features related to merger histories have higher predictive power. Galaxy size is the most important when calculated in 3-dimensions, which becomes less important after accounting for observational effects. In contrast, the stellar age, galaxy colour and star formation rate carry very limited information about $f_\mathrm{acc}$. When an entire set of halo and galaxy features are used, the prediction is almost unbiased, with root-mean-square error (RMSE) of $\sim$0.068. If only using observable features, the RMSE increases to $\sim$0.104. Nevertheless, compared with the case when only stellar mass is used, the inclusion of other observable features does help to decrease the RMSE by $\sim$20%. Lastly, when using galaxy density, velocity and velocity dispersion profiles as features, which represent approximately the maximum amount of information one can extract from galaxy images and velocity maps, the prediction is only slightly improved. Hence, with observable features, the limiting precision of predicting $f_\mathrm{acc}$ is $\sim$0.1, and the multi-component decomposition of galaxy images should have similar or larger uncertainties. If the central black hole mass and the spin parameter of galaxies can be accurately measured in future observations, the RMSE is promising to be further decreased by $\sim$20%.
JWST observations indicate a surprising excess of luminous galaxies at $z\sim 10$ and above, consistent with efficient conversion of the accreted gas into stars, unlike the suppression of star formation by feedback at later times. We show that the high densities and low metallicities at this epoch {\it guarantee} a high star-formation efficiency (SFE) in the most massive dark-matter haloes. Feedback-free starbursts (FFBs) occur when the free-fall time is shorter than $\sim 1$ Myr, below the time for low-metallicity massive stars to develop winds and supernovae. This corresponds to a characteristic density of $\sim 3\times 10^3$cm$^{-3}$. A comparable threshold density permits a starburst by allowing cooling to star-forming temperatures in a free-fall time. The galaxies within $\sim 10^{11} M_\odot$ haloes at $z \sim 10$ are expected to have FFB densities. The halo masses allow efficient gas supply by cold streams in a halo crossing time $\sim 80$ Myr. The FFBs gradually turn all the accreted gas into stars in clusters of $\sim 10^{4-7} M_\odot$ within galaxies that are rotating discs or shells. The starbursting clouds are insensitive to radiative feedback and are shielded against feedback from earlier stars. We predict high SFE above thresholds in redshift and halo mass, where the density is $10^{3-4}$cm$^{-3}$. The $z\sim 10$ haloes of $\sim 10^{10.8} M_\odot$ are predicted to host galaxies of $\sim 10^{10} M_\odot$ with SFR $\sim 65 M_\odot$ yr$^{-1}$ and sub-kpc sizes. The metallicity is $\leq 0.1 Z_\odot$ with little gas, dust, outflows and hot circumgalactic gas, allowing a top-heavy IMF but not requiring it. The compact galaxies with thousands of young FFB clusters may have implications on reionization, black-hole growth and globular clusters.
Abstract We investigate the mass ( M 200 ) and concentration ( c 200 ) dependencies of the velocity anisotropy ( β ) profiles for different components in the dark matter halo—including halo stars, dark matter, and subhalos—using systems from the IllustrisTNG simulations. Beyond a critical radius, β becomes more radial with the increase of M 200 , reflecting more prominent radial accretion around massive halos. The critical radius is r ∼ r s , 0.3 r s , and r s for halo stars, dark matter, and subhalos, with r s being the scale radius of the host halos. This dependence on M 200 is the strongest for subhalos and the weakest for halo stars. In central regions, the β of halo stars and dark matter particles get more isotropic with the increase of M 200 in TNG300 due to baryons. By contrast, the β of dark matter from the dark-matter-only TNG300-Dark run shows much weaker dependence on M 200 within r s . Dark matter in TNG300 is slightly more isotropic than in TNG300-Dark at 0.2 r s < r < 10 r s and log10M200/M⊙<13.8 . Halo stars and dark matter also become more radial with the increase in c 200 , at fixed M 200 . Halo stars are more radial than the β profile of dark matter by approximately a constant beyond r s . Dark matter particles are more radial than subhalos. The differences can be understood, as subhalos on more radial orbits are more easily stripped, contributing more stars and dark matter to the diffuse components. We provide the fitting formula for the differences between the β of halo stars and dark matter at r s < r < 3 r s as βstar−βDM=(−0.034±0.012)log10M200/M⊙+(0.772±0.163) for log10M200/M⊙≥13 and as β star − β DM = 0.328 for log10M200/M⊙<13 .
We propose an analytic model, CuspCore II, for the response of dark matter (DM) haloes to central gas ejection, as a mechanism for generating DM-deficient cores in dwarfs and high-z massive galaxies. We test this model and three other methods using idealized N-body simulations. The current model is physically justified and provides more accurate predictions than the earlier version, CuspCore I (Freundlich et al. 2020). The CuspCore model assumes an instantaneous change of potential, followed by a relaxation to a new Jeans equilibrium. The relaxation turns out to be violent relaxation during the first orbital period, followed by phase mixing. By tracing the energy diffusion dE=dU(r) iteratively, the model reproduces the simulated DM profiles with ~10% accuracy or better. A method based on adiabatic invariants shows similar precision for moderate mass change but underestimates the DM expansion for strong gas ejection. A method based on a simple empirical relation between DM and total mass ratios makes slightly inferior predictions. The crude assumption used in CuspCore I, of energy conservation for shells that encompass a fixed DM mass, turns out to underestimate the DM response, which can be partially remedied by introducing an alternative "energy" definition. Our model is being generalized to address the differential response of a multi-component system of stars and DM in the formation of DM-deficient galaxies.
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