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Register a new userAction-based distribution function modelling for constraining the shape of the Galactic dark matter halo
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We estimate the 3D density profile of the Galactic dark matter (DM) halo within $r lesssim 30$ kpc from the Galactic centre by using the astrometric data for halo RR Lyrae stars from Gaia DR2. We model both the stellar halo distribution function and the Galactic potential, fully taking into account the survey selection function, the observational errors, and the missing line-of-sight velocity data for RR Lyrae stars. With a Bayesian MCMC method, we infer the model parameters, including the density flattening of the DM halo $q$, which is assumed to be constant as a function of radius. We find that 99% of the posterior distribution of $q$ is located at $q>0.963$, which strongly disfavours a flattened DM halo. We cannot draw any conclusions as to whether the Galactic DM halo at $r lesssim 30$ kpc is prolate, because we restrict ourselves to axisymmetric oblate halo models with $qleq1$. Our result is inconsistent with predictions from cosmological hydrodynamical simulations that advocate more oblate ($langle{q}rangle sim0.8 pm 0.15$) DM halos within $sim 15%$ of the virial radius for Milky-Way-sized galaxies. An alternative possibility, based on our validation tests with a cosmological simulation, is that the true value $q$ of the Galactic halo could be consistent with cosmological simulations but that disequilibrium in the Milky Way potential is inflating our measurement of $q$ by 0.1-0.2. As a by-product of our analysis, our model constrains the DM density in the Solar neighbourhood to be $rho_{mathrm{DM},odot} = (9.01^{+0.18}_{-0.20})times10^{-3}M_odot mathrm{pc}^{-3} = 0.342^{+0.007}_{-0.007}$ $;mathrm{GeV} mathrm{cm}^{-3}$.
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A recently discovered young, high-velocity giant star J01020100-7122208 is a good candidate of hypervelocity star ejected from the Galactic center, although it has a bound orbit. If we assume that this star was ejected from the Galactic center, it can be used to constrain the Galactic potential, because the deviation of its orbit from a purely radial orbit informs us of the torque that this star has received after its ejection. Based on this assumption, we estimate the flattening of the dark matter halo of the Milky Way by using the Gaia DR2 data and the circular velocity data from Eilers et al. (2019). Our Bayesian analysis shows that the orbit of J01020100-7122208 favors a prolate dark matter halo within $sim$ 10 kpc from the Galactic center. The posterior distribution of the density flattening $q$ shows a broad distribution at $q gtrsim1$ and peaks at $q simeq 1.5$. Also, 98.5% of the posterior distribution is located at $q>1$, highly disfavoring an oblate halo.
The dark matter spike induced by the adiabatic growth of a massive black hole in a cuspy environment, may explain the thermal dark matter density required to fit the cut-off in the HESSJ1745-290 gamma-ray spectra as TeV dark matter signal with a background component. The spike extension appears comparable with the HESS angular resolution.
We use the kinematics of $sim200,000$ giant stars that lie within $sim 1.5$ kpc of the plane to measure the vertical profile of mass density near the Sun. We find that the dark mass contained within the isodensity surface of the dark halo that passes through the Sun ($(6pm0.9)times10^{10},mathrm{M_odot}$), and the surface density within $0.9$ kpc of the plane ($(69pm10),mathrm{M_odot,pc^{-2}}$) are almost independent of the (oblate) halos axis ratio $q$. If the halo is spherical, 46 per cent of the radial force on the Sun is provided by baryons, and only 4.3 per cent of the Galaxys mass is baryonic. If the halo is flattened, the baryons contribute even less strongly to the local radial force and to the Galaxys mass. The dark-matter density at the location of the Sun is $0.0126,q^{-0.89},mathrm{M_odot,pc^{-3}}=0.48,q^{-0.89},mathrm{GeV,cm^{-3}}$. When combined with other literature results we find hints for a mildly oblate dark halo with $q simeq 0.8$. Our value for the dark mass within the solar radius is larger than that predicted by cosmological dark-matter-only simulations but in good agreement with simulations once the effects of baryonic infall are taken into account. Our mass models consist of three double-exponential discs, an oblate bulge and a Navarro-Frenk-White dark-matter halo, and we model the dynamics of the RAVE stars in the corresponding gravitational fields by finding distribution functions $f(mathbf{J})$ that depend on three action integrals. Statistical errors are completely swamped by systematic uncertainties, the most important of which are the distance to the stars in the photometric and spectroscopic samples and the solar distance to the Galactic centre. Systematics other than the flattening of the dark halo yield overall uncertainties $sim 15$ per cent.
The High Altitude Water Cherenkov (HAWC) gamma-ray observatory is a wide field-of-view observatory sensitive to 500 GeV - 100 TeV gamma rays and cosmic rays. With its observations over 2/3 of the sky every day, the HAWC observatory is sensitive to a wide variety of astrophysical sources, including possible gamma rays from dark matter. Dark matter annihilation and decay in the Milky Way Galaxy should produce gamma-ray signals across many degrees on the sky. The HAWC instantaneous field-of-view of 2 sr enables observations of extended regions on the sky, such as those from dark matter in the Galactic halo. Here we show limits on the dark matter annihilation cross-section and decay lifetime from HAWC observations of the Galactic halo with 15 months of data. These are some of the most robust limits on TeV and PeV dark matter, largely insensitive to the dark matter morphology. These limits begin to constrain models in which PeV IceCube neutrinos are explained by dark matter which primarily decays into hadrons.
A statistical analysis of the observed perturbations in the density of stellar streams can in principle set stringent contraints on the mass function of dark matter subhaloes, which in turn can be used to constrain the mass of the dark matter particle. However, the likelihood of a stellar density with respect to the stream and subhaloes parameters involves solving an intractable inverse problem which rests on the integration of all possible forward realisations implicitly defined by the simulation model. In order to infer the subhalo abundance, previous analyses have relied on Approximate Bayesian Computation (ABC) together with domain-motivated but handcrafted summary statistics. Here, we introduce a likelihood-free Bayesian inference pipeline based on Amortised Approximate Likelihood Ratios (AALR), which automatically learns a mapping between the data and the simulator parameters and obviates the need to handcraft a possibly insufficient summary statistic. We apply the method to the simplified case where stellar streams are only perturbed by dark matter subhaloes, thus neglecting baryonic substructures, and describe several diagnostics that demonstrate the effectiveness of the new method and the statistical quality of the learned estimator.
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