No Arabic abstract
Detection of point sources in images is a fundamental operation in astrophysics, and is crucial for constraining population models of the underlying point sources or characterizing the background emission. Standard techniques fall short in the crowded-field limit, losing sensitivity to faint sources and failing to track their covariance with close neighbors. We construct a Bayesian framework to perform inference of faint or overlapping point sources. The method involves probabilistic cataloging, where samples are taken from the posterior probability distribution of catalogs consistent with an observed photon count map. In order to validate our method we sample random catalogs of the gamma-ray sky in the direction of the North Galactic Pole (NGP) by binning the data in energy and Point Spread Function (PSF) classes. Using three energy bins spanning $0.3 - 1$, $1 - 3$ and $3 - 10$ GeV, we identify $270substack{+30 -10}$ point sources inside a $40^circ times 40^circ$ region around the NGP above our point-source inclusion limit of $3 times 10^{-11}$/cm$^2$/s/sr/GeV at the $1-3$ GeV energy bin. Modeling the flux distribution as a power law, we infer the slope to be $-1.92substack{+0.07 -0.05}$ and estimate the contribution of point sources to the total emission as $18substack{+2 -2}$%. These uncertainties in the flux distribution are fully marginalized over the number as well as the spatial and spectral properties of the unresolved point sources. This marginalization allows a robust test of whether the apparently isotropic emission in an image is due to unresolved point sources or of truly diffuse origin.
We describe a simple probabilistic method to cross-identify astrophysical sources from different catalogs and provide the probability that a source is associated with a source from another catalog or that it has no counterpart. When the positional uncertainty in one of the catalog is unknown, this method may be used to derive its typical value and even to study its dependence on the size of objects. It may also be applied when the true centers of a source and of its counterpart at another wavelength do not coincide. We extend this method to the case when there are only one-to-one associations between the catalogs.
The Galactic Center Excess (GCE) of GeV gamma rays can be explained as a signal of annihilating dark matter or of emission from unresolved astrophysical sources, such as millisecond pulsars. Evidence for the latter is provided by a statistical procedure---referred to as Non-Poissonian Template Fitting (NPTF)---that distinguishes the smooth distribution of photons expected for dark matter annihilation from a clumpy photon distribution expected for point sources. In this paper, we perform an extensive study of the NPTF on simulated data, exploring its ability to recover the flux and luminosity function of unresolved sources at the Galactic Center. When astrophysical background emission is perfectly modeled, we find that the NPTF successfully distinguishes between the dark matter and point source hypotheses when either component makes up the entirety of the GCE. When the GCE is a mixture of dark matter and point sources, the NPTF may fail to reconstruct the correct contribution of each component. We further study the impact of mismodeling the Galactic diffuse backgrounds, finding that while a dark matter signal could be attributed to point sources in some outlying cases for the scenarios we consider, the significance of a true point source signal remains robust. Our work enables us to comment on a recent study by Leane and Slatyer (2019) that questions prior NPTF conclusions because the method does not recover an artificial dark matter signal injected on actual Fermi data. We demonstrate that the failure of the NPTF to extract an artificial dark matter signal can be natural when point sources are present in the data---with the effect further exacerbated by the presence of diffuse mismodeling---and does not on its own invalidate the conclusions of the NPTF analysis in the Inner Galaxy.
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from their positions and positional uncertainties. The probability that an object is associated with a source from the other catalog, or that it has no counterpart, is derived under two exclusive assumptions: first, the classical case of several-to-one associations, and then the more realistic but more difficult problem of one-to-one associations. In either case, the likelihood of observing the objects in the two catalogs at their effective positions is computed and a maximum likelihood estimator of the fraction of sources with a counterpart -- a quantity needed to compute the probabilities of association -- is built. When the positional uncertainty in one or both catalogs is unknown, this method may be used to estimate its typical value and even to study its dependence on the size of objects. It may also be applied when the true centers of a source and of its counterpart at another wavelength do not coincide. To compute the likelihood and association probabilities under the different assumptions, we developed a Fortran 95 code called Aspects ([asp{epsilon}], ASsociation PositionnellE/ProbabilistE de CaTalogues de Sources in French); its source files are made freely available. To test Aspects, all-sky mock catalogs containing up to 10^5 objects were created, forcing either several-to-one or one-to-one associations. The analysis of these simulations confirms that, in both cases, the assumption with the highest likelihood is the right one and that estimators of unknown parameters built for the appropriate association model are reliable.
Using all-sky maps obtained from COBE/DIRBE at 3.5 and 4.9 um, we present a reanalysis of diffuse sky emissions such as zodiacal light (ZL), diffuse Galactic light (DGL), integrated starlight (ISL), and isotropic residual emission including the extragalactic background light (EBL). Our new analysis, which includes an improved estimate of ISL using the Wide-field Infrared Survey Explorer (WISE) data, enabled us to find the DGL signal in a direct linear correlation between diffuse near-infrared and 100 um emission at high Galactic latitudes (|b| > 35 degree). At 3.5um, the high-latitude DGL result is comparable to the low-latitude value derived from the previous DIRBE analysis. In comparison with models of the DGL spectrum assuming a size distribution of dust grains composed of amorphous silicate, graphite, and polycyclic aromatic hydrocarbon (PAH), the measured DGL values at 3.5 and 4.9 um constrain the mass fraction of PAH particles in the total dust species to be more than ~ 2%. This was consistent with the results of Spitzer/IRAC toward the lower Galactic latitude regions. The derived residual emission of 8.9 +/- 3.4 nW m^{-2} sr^{-1} at 3.5 um is marginally consistent with the level of integrated galaxy light and the EBL constraints from the gamma-ray observations. The residual emission at 4.9 um is not significantly detected due to the large uncertainty in the ZL subtraction, same as previous studies. Combined with our reanalysis of the DIRBE data at 1.25 and 2.2 um, the residual emission in the near-infrared exhibits the Rayleigh-Jeans spectrum.
The Sloan Digital Sky Survey (SDSS) has been in operation since 2000 April. This paper presents the tenth public data release (DR10) from its current incarnation, SDSS-III. This data release includes the first spectroscopic data from the Apache Point Observatory Galaxy Evolution Experiment (APOGEE), along with spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS) taken through 2012 July. The APOGEE instrument is a near-infrared R~22,500 300-fiber spectrograph covering 1.514--1.696 microns. The APOGEE survey is studying the chemical abundances and radial velocities of roughly 100,000 red giant star candidates in the bulge, bar, disk, and halo of the Milky Way. DR10 includes 178,397 spectra of 57,454 stars, each typically observed three or more times, from APOGEE. Derived quantities from these spectra (radial velocities, effective temperatures, surface gravities, and metallicities) are also included.DR10 also roughly doubles the number of BOSS spectra over those included in the ninth data release. DR10 includes a total of 1,507,954 BOSS spectra, comprising 927,844 galaxy spectra; 182,009 quasar spectra; and 159,327 stellar spectra, selected over 6373.2 square degrees.