ABSTRACT
Indirect detection strategies of particle dark matter (DM) in Dwarf spheroidal satellite galaxies (dSphs) typically entail searching for annihilation signals above the astrophysical ...background. To robustly compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data – which are generally frequentist – rely on estimating the abundance of DM by calculating the so-called J factor. This quantity is usually inferred from the kinematic properties of the stellar population of a dSph using the Jeans equation, commonly by means of Bayesian techniques that entail the presence (and additional systematic uncertainty) of prior choice. Here, extending earlier work, we develop a scheme to derive the profile likelihood for J factors of dwarf spheroidals for models with five or more free parameters. We validate our method on a publicly available simulation suite, released by the Gaia Challenge, finding satisfactory statistical properties for bias and probability coverage. We present the profile likelihood function and maximum likelihood estimates for the J-factor of 10 dSphs. As an illustration, we apply these profile likelihoods to recently published analyses of γ-ray data with the Fermi Large Area Telescope to derive new, consistent upper limits on the DM annihilation cross-section. We do this for a subset of systems, generally referred to as classical dwarfs. The implications of these findings for DM searches are discussed, together with future improvements and extensions of this technique.
The region around the Galactic Center (GC) is now well established to be brighter at energies of a few GeV than what is expected from conventional models of diffuse gamma-ray emission and catalogs of ...known gamma-ray sources. We study the GeV excess using 6.5 yr of data from the Fermi Large Area Telescope. We characterize the uncertainty of the GC excess spectrum and morphology due to uncertainties in cosmic-ray source distributions and propagation, uncertainties in the distribution of interstellar gas in the Milky Way, and uncertainties due to a potential contribution from the Fermi bubbles. We also evaluate uncertainties in the excess properties due to resolved point sources of gamma rays. The GC is of particular interest, as it would be expected to have the brightest signal from annihilation of weakly interacting massive dark matter (DM) particles. However, control regions along the Galactic plane, where a DM signal is not expected, show excesses of similar amplitude relative to the local background. Based on the magnitude of the systematic uncertainties, we conservatively report upper limits for the annihilation cross-section as a function of particle mass and annihilation channel.
Abstract
Line-of-sight integrals of the squared density, commonly called the J-factor, are essential for inferring dark matter (DM) annihilation signals. The J-factors of DM-dominated dwarf ...spheroidal satellite galaxies (dSphs) have typically been derived using Bayesian techniques, which for small data samples implies that a choice of priors constitutes a non-negligible systematic uncertainty. Here we report the development of a new fully frequentist approach to construct the profile likelihood of the J-factor. Using stellar kinematic data from several classical and ultra-faint dSphs, we derive the maximum likelihood value for the J-factor and its confidence intervals. We validate this method, in particular its bias and coverage, using simulated data from the Gaia Challenge. We find that the method possesses good statistical properties. The J-factors and their uncertainties are generally in good agreement with the Bayesian-derived values, with the largest deviations restricted to the systems with the smallest kinematic data sets. We discuss improvements, extensions, and future applications of this technique.
ABSTRACT Indirect detection strategies of particle dark matter (DM) in Dwarf spheroidal satellite galaxies (dSphs) typically entail searching for annihilation signals above the astrophysical ...background. To robustly compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data – which are generally frequentist – rely on estimating the abundance of DM by calculating the so-called J factor. This quantity is usually inferred from the kinematic properties of the stellar population of a dSph using the Jeans equation, commonly by means of Bayesian techniques that entail the presence (and additional systematic uncertainty) of prior choice. Here, extending earlier work, we develop a scheme to derive the profile likelihood for J factors of dwarf spheroidals for models with five or more free parameters. We validate our method on a publicly available simulation suite, released by the Gaia Challenge, finding satisfactory statistical properties for bias and probability coverage. We present the profile likelihood function and maximum likelihood estimates for the J-factor of 10 dSphs. As an illustration, we apply these profile likelihoods to recently published analyses of γ-ray data with the Fermi Large Area Telescope to derive new, consistent upper limits on the DM annihilation cross-section. We do this for a subset of systems, generally referred to as classical dwarfs. The implications of these findings for DM searches are discussed, together with future improvements and extensions of this technique.
Dwarf spheroidal galaxies are among the most promising targets for indirect dark matter (DM) searches in γ rays. The γ-ray flux from DM annihilation in a dwarf spheroidal galaxy is proportional to ...the J-factor of the source. The J-factor of a dwarf spheroidal galaxy is the line-of-sight integral of the DM mass density squared times ⟨σannvrel⟩/(σannvrel)0, where σannvrel is the DM annihilation cross-section times relative velocity vrel=|vrel|, angle brackets denote average over vrel, and (σannvrel)0 is the vrel-independent part of σannvrel. If σannvrel is constant in vrel, J-factors only depend on the DM space distribution in the source. However, if σannvrel varies with vrel, as in the presence of DM self-interactions, J-factors also depend on the DM velocity distribution, and on the strength and range of the DM self-interaction. Models for self-interacting DM are increasingly important in the study of the small scale clustering of DM, and are compatible with current astronomical and cosmological observations. Here we derive the J-factor of 20 dwarf spheroidal galaxies from stellar kinematic data under the assumption of Yukawa DM self-interactions. J-factors are derived through a profile likelihood approach, assuming either Navarro-Frenk-White (NFW) or cored DM profiles. We also compare our results with J-factors derived assuming the same velocity for all DM particles in the target galaxy. We find that this common approximation overestimates the J-factors by up to 1 order of magnitude. J-factors for a sample of DM particle masses and self-interaction coupling constants, as well as for NFW and cored density profiles, are provided electronically, ready to be used in other projects.
MNRAS, Vol 488, 2, 2616-2628, (2019) Indirect detection strategies of particle Dark Matter (DM) in Dwarf
spheroidal satellite galaxies (dSphs) typically entail searching for
annihilation signals ...above the astrophysical background. To robustly compare
model predictions with the observed fluxes of product particles, most analyses
of astrophysical data -- which are generally frequentist -- rely on estimating
the abundance of DM by calculating the so-called $\textit{J-factor}$. This
quantity is usually inferred from the kinematic properties of the stellar
population of a dSph using Jeans equation, commonly by means of Bayesian
techniques which entail the presence (and additional systematic uncertainty) of
prior choice. Here, extending earlier work, we develop a scheme to derive the
profile likelihood for $J$-factors of dwarf spheroidals for models with five or
more free parameters. We validate our method on a publicly available simulation
suite, released by the Gaia Challenge, finding satisfactory statistical
properties for coverage and bias. We present the profile likelihood function
and maximum likelihood estimates for the $J$-factor of ten dSphs . As an
illustration, we apply these profiles likelihood to recently published analyses
of gamma-ray data with the Fermi Large Area Telescope to derive new, consistent
upper limits on the DM annihilation cross-section. We do this for a subset of
systems, generally referred to as $\textit{classical dwarfs}$. The implications
of these findings for DM searches are discussed, together with future
improvements and extensions of this technique.
Indirect detection strategies of particle Dark Matter (DM) in Dwarf spheroidal satellite galaxies (dSphs) typically entail searching for annihilation signals above the astrophysical background. To ...robustly compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data -- which are generally frequentist -- rely on estimating the abundance of DM by calculating the so-called \(\textit{J-factor}\). This quantity is usually inferred from the kinematic properties of the stellar population of a dSph using Jeans equation, commonly by means of Bayesian techniques which entail the presence (and additional systematic uncertainty) of prior choice. Here, extending earlier work, we develop a scheme to derive the profile likelihood for \(J\)-factors of dwarf spheroidals for models with five or more free parameters. We validate our method on a publicly available simulation suite, released by the Gaia Challenge, finding satisfactory statistical properties for coverage and bias. We present the profile likelihood function and maximum likelihood estimates for the \(J\)-factor of ten dSphs . As an illustration, we apply these profiles likelihood to recently published analyses of gamma-ray data with the Fermi Large Area Telescope to derive new, consistent upper limits on the DM annihilation cross-section. We do this for a subset of systems, generally referred to as \(\textit{classical dwarfs}\). The implications of these findings for DM searches are discussed, together with future improvements and extensions of this technique.
Line-of-sight integrals of the squared density, commonly called the J-factor, are essential for inferring dark matter annihilation signals. The J-factors of dark matter-dominated dwarf spheroidal ...satellite galaxies (dSphs) have typically been derived using Bayesian techniques, which for small data samples implies that a choice of priors constitutes a non-negligible systematic uncertainty. Here we report the development of a new fully frequentist approach to construct the profile likelihood of the J-factor. Using stellar kinematic data from several classical and ultra-faint dSphs, we derive the maximum likelihood value for the J-factor and its confidence intervals. We validate this method, in particular its bias and coverage, using simulated data from the Gaia Challenge. We find that the method possesses good statistical properties. The J-factors and their uncertainties are generally in good agreement with the Bayesian-derived values, with the largest deviations restricted to the systems with the smallest kinematic datasets. We discuss improvements, extensions, and future applications of this technique.
The region around the Galactic Center (GC) is now well established to be brighter at energies of a few GeV than what is expected from conventional models of diffuse gamma-ray emission and catalogs of ...known gamma-ray sources. We study the GeV excess using 6.5 yr of data from the Fermi Large Area Telescope. We characterize the uncertainty of the GC excess spectrum and morphology due to uncertainties in cosmic-ray source distributions and propagation, uncertainties in the distribution of interstellar gas in the Milky Way, and uncertainties due to a potential contribution from the Fermi bubbles. We also evaluate uncertainties in the excess properties due to resolved point sources of gamma rays. The GC is of particular interest, as it would be expected to have the brightest signal from annihilation of weakly interacting massive dark matter (DM) particles. However, control regions along the Galactic plane, where a DM signal is not expected, show excesses of similar amplitude relative to the local background. Based on the magnitude of the systematic uncertainties, we conservatively report upper limits for the annihilation cross-section as a function of particle mass and annihilation channel.
Abstract
Objectives
The pro-inflammatory activities of the calgranulins and HMGB1 can be counteracted by sRAGE, the soluble form of their shared receptor. To understand the role of these molecules in ...AAV and their potential as therapeutic targets we have studied (i) the relationship between these DAMPS and disease activity; (ii) the expression of RAGE and sRAGE in biopsy tissue and peripheral blood; and (iii) the effect of these molecules on ANCA-mediated cytokine production.
Methods
We examined circulating levels of calgranulins (S100A8/A9 and S100A12), HMGB1 and sRAGE by ELISA. RAGE was examined in AAV kidney and lung biopsies by immunohistochemistry and RAGE expression was monitored in peripheral blood by qPCR. In vitro, the effect of co-stimulating PBMC with ANCA and S100A8/A9 on cytokine production was studied by ELISA.
Results
We found significantly raised levels of calgranulins and HMGB1 in active AAV regardless of clinical phenotype (PR3+/MPO+ AAV). Levels of calgranulins showed significant correlations with each other. RAGE protein and message was raised in peripheral blood and in cells infiltrating kidney and lung biopsy tissue, while sRAGE was lowered. Furthermore, ANCA-mediated production of IL-8 from PBMC was significantly enhanced by the presence of S100A8/A9 in a RAGE/TLR4-dependent manner.
Conclusions
Raised circulating calgranulins provide a good marker of disease activity in AAV and are unlikely to be counteracted by sRAGE. Increased RAGE expression in AAV indicates receptor stimulation in active disease that may exacerbate ANCA-induced cytokine production. Targeting the RAGE pathway may provide a useful therapeutic approach in AAV.
PDF
