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Register a new userWhat to expect from dynamical modelling of cluster haloes I. The information content of different dynamical tracers
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Using hydrodynamical simulations, we study how well the underlying gravitational potential of a galaxy cluster can be modelled dynamically with different types of tracers. In order to segregate different systematics and the effects of varying estimator performances, we first focus on applying a generic minimal assumption method (oPDF) to model the simulated haloes using the full 6-D phasespace information. We show that the halo mass and concentration can be recovered in an ensemble unbiased way, with a stochastic bias that varies from halo to halo, mostly reflecting deviations from steady state in the tracer distribution. The typical systematic uncertainty is $sim 0.17$ dex in the virial mass and $sim 0.17$ dex in the concentration as well when dark matter particles are used as tracers. The dynamical state of satellite galaxies are close to that of dark matter particles, while intracluster stars are less in a steady state, resulting in a $sim$ 0.26 dex systematic uncertainty in mass. Compared with galactic haloes hosting Milky-Way-like galaxies, cluster haloes show a larger stochastic bias in the recovered mass profiles. We also test the accuracy of using intracluster gas as a dynamical tracer modelled through a generalised hydrostatic equilibrium equation, and find a comparable systematic uncertainty in the estimated mass to that using dark matter. Lastly, we demonstrate that our conclusions are largely applicable to other steady-state dynamical models including the spherical Jeans equation, by quantitatively segregating their statistical efficiencies and robustness to systematics. We also estimate the limiting number of tracers that leads to the systematics-dominated regime in each case.
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Many dynamical models of the Milky Way halo require assumptions that the distribution function of a tracer population should be independent of time (i.e., a steady state distribution function) and that the underlying potential is spherical. We study the limitations of such modelling by applying a general dynamical model with minimal assumptions to a large sample of galactic haloes from cosmological $N$-body and hydrodynamical simulations. Using dark matter particles as dynamical tracers, we find that the systematic uncertainties in the measured mass and concentration parameters typically have an amplitude of 25% to 40%. When stars are used as tracers, however, the systematic uncertainties can be as large as a factor of $2-3$. The systematic uncertainties are not reduced by increasing the tracer sample size and vary stochastically from halo to halo. These systematic uncertainties are mostly driven by underestimated statistical noise caused by correlated phase-space structures that violate the steady state assumption. The number of independent phase-space structures inferred from the uncertainty level sets a limiting sample size beyond which a further increase no longer significantly improves the accuracy of dynamical inferences. The systematic uncertainty level is determined by the halo merger history, the shape and environment of the halo. Our conclusions apply generally to any spherical steady-state model.
The IceCube Neutrino Observatory instruments about 1 km$^3$ of deep, glacial ice at the geographic South Pole using 5160 photomultipliers to detect Cherenkov light from relativistic, charged particles. Most IceCube science goals rely on precise understanding and modelling of the optical properties of the instrumented ice. A peculiar light propagation effect observed by IceCube is an anisotropic attenuation, which is aligned with the local flow of the ice. Recent efforts have shown this effect is most likely due to curved photon trajectories resulting from the asymmetric light diffusion in the birefringent polycrystalline microstructure of the ice. This new model can be optimized by adjusting the average orientation, size and shape of the ice crystals. We present the parametrization of the birefringence effect in our photon propagation simulation, the fitting procedures and results. The anticipated potential of calibration instrumentation in the upcoming IceCube Upgrade to improve on known shortcomings of the current ice modelling is also discussed.
I review briefly some dynamical models of structures in the outer parts of disc galaxies, including models of polar rings, tidal tails and bridges. I then discuss the density distribution in the outer parts of discs. For this, I compare observations to results of a model in which the disc galaxy is in fact the remnant of a major merger, and find good agreement. This comparison includes radial profiles of the projected surface density and of stellar age, as well as time evolution of the break radius and of the inner and outer disc scale lengths. I also compare the radial projected surface density profiles of dynamically motivated mono-age populations and find that, compared to older populations, younger ones have flatter density profiles in the inner region and steeper in the outer one. The break radius, however, does not vary with stellar age, again in good agreement with observations.
Observations of high-redshift quasars provide information on the massive black holes (MBHs) powering them and the galaxies hosting them. Current observations of $z gtrsim 6$ hosts, at sub-mm wavelengths, trace the properties of cold gas, and these are used to compare with the correlations between MBHs and galaxies characterising the $z=0$ population. The relations at $z=0$, however, rely on stellar-based tracers of the galaxy properties. We perform a very-high resolution cosmological zoom-in simulation of a $z=7$ quasar including state-of-the-art non-equilibrium chemistry, MBH formation, growth and feedback, to assess the evolution of the galaxy host and the central MBH, and compare the results with recent ALMA observations of high-redshift quasars. We measure both the stellar-based quantities used to establish the $z=0$ correlations, as well as the gas-based quantities available in $z gtrsim 6$ observations, adopting the same assumptions and techniques used in observational studies. The high-redshift studies argued that MBHs at high redshift deviate from the local MBH-galaxy correlations. In our analysis of the single galaxy we evolve, we find that the high-redshift population sits on the same correlations as the local one, when using the same tracers used at $z=0$. When using the gas-based tracers, however, MBHs appear to be over-massive. The discrepancy between local and high-redshift MBHs seems caused by the different tracers employed, and necessary assumptions, and not by an intrinsic difference. Better calibration of the tracers, higher resolution data and availability of facilities that can probe the stellar population will be crucial to assess precisely and accurately high-redshift quasar hosts.
The mass of the dark matter halo of the Milky Way can be estimated by fitting analytical models to the phase-space distribution of dynamical tracers. We test this approach using realistic mock stellar halos constructed from the Aquarius N-body simulations of dark matter halos in the $Lambda$CDM cosmology. We extend the standard treatment to include a Navarro-Frenk-White (NFW) potential and use a maximum likelihood method to recover the parameters describing the simulated halos from the positions and velocities of their mock halo stars. We find that the estimate of halo mass is highly correlated with the estimate of halo concentration. The best-fit halo masses within the virial radius, $R_{200}$, are biased, ranging from a 40% underestimate to a 5% overestimate in the best case (when the tangential velocities of the tracers are included). There are several sources of bias. Deviations from dynamical equilibrium can potentially cause significant bias; deviations from spherical symmetry are relatively less important. Fits to stars at different galactocentric radii can give different mass estimates. By contrast, the model gives good constraints on the mass within the half-mass radius of tracers even when restricted to tracers within 60kpc. The recovered velocity anisotropies of tracers, $beta$, are biased systematically, but this does not affect other parameters if tangential velocity data are used as constraints.
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