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David W. Hogg

Publications and source records attributed to David W. Hogg.

At least 181 records · Page 10Linked to original sources

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.

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Replacing standard galaxy profiles with mixtures of Gaussians

Exponential, de Vaucouleurs, and Sérsic profiles are simple and successful models for fitting two-dimensional images of galaxies. One numerical issue encountered in this kind of fitting is the pixel rendering and convolution (or correlation) of the models with the telescope point-spread function (PSF); these operations are slow, and easy to get slightly wrong at small radii. Here we exploit the realization that these models can be approximated to arbitrary accuracy with a mixture (linear superposition) of two-dimensional Gaussians (MoGs). MoGs are fast to render and fast to affine-transform. Most importantly, if you have a MoG model for the pixel-convolved PSF, the PSF-convolved, affine-transformed galaxy models are themselves MoGs and therefore very fast to compute, integrate, and render precisely. We present worked examples that can be directly used in image fitting; we are using them ourselves. The MoG profiles we provide can be swapped in to replace the standard models in any image-fitting code; they sped up model fitting in our projects by an order of magnitude; they ought to make any code faster at essentially no cost in precision.

astro-ph.IM↗

Star-Galaxy Classification in Multi-Band Optical Imaging

Ground-based optical surveys such as PanSTARRS, DES, and LSST, will produce large catalogs to limiting magnitudes of r > 24. Star-galaxy separation poses a major challenge to such surveys because galaxies---even very compact galaxies---outnumber halo stars at these depths. We investigate photometric classification techniques on stars and galaxies with intrinsic FWHM < 0.2 arcsec. We consider unsupervised spectral energy distribution template fitting and supervised, data-driven Support Vector Machines (SVM). For template fitting, we use a Maximum Likelihood (ML) method and a new Hierarchical Bayesian (HB) method, which learns the prior distribution of template probabilities from the data. SVM requires training data to classify unknown sources; ML and HB don't. We consider i.) a best-case scenario (SVM_best) where the training data is (unrealistically) a random sampling of the data in both signal-to-noise and demographics, and ii.) a more realistic scenario where training is done on higher signal-to-noise data (SVM_real) at brighter apparent magnitudes. Testing with COSMOS ugriz data we find that HB outperforms ML, delivering ~80% completeness, with purity of ~60-90% for both stars and galaxies, respectively. We find no algorithm delivers perfect performance, and that studies of metal-poor main-sequence turnoff stars may be challenged by poor star-galaxy separation. Using the Receiver Operating Characteristic curve, we find a best-to-worst ranking of SVM_best, HB, ML, and SVM_real. We conclude, therefore, that a well trained SVM will outperform template-fitting methods. However, a normally trained SVM performs worse. Thus, Hierarchical Bayesian template fitting may prove to be the optimal classification method in future surveys.

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The Sloan Digital Sky Survey quasar catalog: ninth data release

We present the Data Release 9 Quasar (DR9Q) catalog from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. The catalog includes all BOSS objects that were targeted as quasar candidates during the survey, are spectrocopically confirmed as quasars via visual inspection, have luminosities Mi[z=2]<-20.5 (in a $Λ$CDM cosmology with H0 = 70 km/s/Mpc, $Ω_{\rm M}$ = 0.3, and $Ω_Λ$ = 0.7) and either display at least one emission line with full width at half maximum (FWHM) larger than 500 km/s or, if not, have interesting/complex absorption features. It includes as well, known quasars (mostly from SDSS-I and II) that were reobserved by BOSS. This catalog contains 87,822 quasars (78,086 are new discoveries) detected over 3,275 deg$^{2}$ with robust identification and redshift measured by a combination of principal component eigenspectra newly derived from a training set of 8,632 spectra from SDSS-DR7. The number of quasars with $z>2.15$ (61,931) is ~2.8 times larger than the number of z>2.15 quasars previously known. Redshifts and FWHMs are provided for the strongest emission lines (CIV, CIII], MgII). The catalog identifies 7,533 broad absorption line quasars and gives their characteristics. For each object the catalog presents five-band (u,g,r,i,z) CCD-based photometry with typical accuracy of 0.03 mag, and information on the morphology and selection method. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys.

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Designing Imaging Surveys for a Retrospective Relative Photometric Calibration

In this paper, we investigate the impact of survey strategy on the performance of self-calibration when the goal is to produce accurate photometric catalogs from wide-field imaging surveys. This self-calibration technique utilizes multiple measurements of sources at different focal-plane positions to constrain instruments' large-scale response (flat-field) from survey science data alone. We create an artificial sky of sources and synthetically observe it under four basic survey strategies, creating an end-to-end simulation of an imaging survey for each. These catalog-level simulations include realistic measurement uncertainties and a complex focal-plane dependence of the instrument response. In the self-calibration step, we simultaneously fit for all the star fluxes and the parameters of a position-dependent flat-field. For realism, we deliberately fit with a wrong noise model and a flat-field functional basis that does not include the model that generated the synthetic data. We demonstrate that with a favorable survey strategy, a complex instrument response can be precisely self-calibrated. We show that returning the same sources to very different focal-plane positions is the key property of any survey strategy designed for accurate retrospective calibration of this type. The results of this work suggest the following advice for those considering the design of large-scale imaging surveys: Do not use a regular, repeated tiling of the sky; instead return the same sources to very different focal-plane positions.

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Galaxy growth by merging in the nearby universe

We measure the mass growth rate by merging for a wide range of galaxy types. We present the small-scale (0.014 < r < 11 h70^{-1} Mpc) projected cross-correlation functions w(rp) of galaxy subsamples from the spectroscopic sample of the NYU VAGC (5 \times 10^5 galaxies of redshifts 0.03 < z < 0.15) with galaxy subsamples from the SDSS imaging (4 \times 10^7 galaxies). We use smooth fits to de-project the two-dimensional functions w(rp) to obtain smooth three-dimensional real-space cross-correlation functions ξ(r) for each of several spectroscopic subsamples with each of several imaging subsamples. Because close pairs are expected to merge, the three-space functions and dynamical evolution time estimates provide galaxy accretion rates. We find that the accretion onto massive blue galaxies and onto red galaxies is dominated by red companions, and that onto small-mass blue galaxies, red and blue galaxies make comparable contributions. We integrate over all types of companions and find that at fixed stellar mass, the total fractional accretion rates onto red galaxies (\sim 1.5 h70 percent per Gyr) is greater than that onto blue galaxies (\sim 0.5 h70 percent per Gyr). Although these rates are very low, they are almost certainly over-estimates because we have assumed that all close pairs merge as quickly as dynamical friction permits.

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The Milky Way's circular velocity curve between 4 and 14 kpc from APOGEE data

We measure the Milky Way's rotation curve over the Galactocentric range 4 kpc <~ R <~ 14 kpc from the first year of data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). We model the line-of-sight velocities of 3,365 stars in fourteen fields with b = 0 deg between 30 deg < l < 210 deg out to distances of 10 kpc using an axisymmetric kinematical model that includes a correction for the asymmetric drift of the warm tracer population (σ_R ~ 35 km/s). We determine the local value of the circular velocity to be V_c(R_0) = 218 +/- 6 km/s and find that the rotation curve is approximately flat with a local derivative between -3.0 km/s/kpc and 0.4 km/s/kpc. We also measure the Sun's position and velocity in the Galactocentric rest frame, finding the distance to the Galactic center to be 8 kpc < R_0 < 9 kpc, radial velocity V_{R,sun} = -10 +/- 1 km/s, and rotational velocity V_{ϕ,sun} = 242^{+10}_{-3} km/s, in good agreement with local measurements of the Sun's radial velocity and with the observed proper motion of Sgr A*. We investigate various systematic uncertainties and find that these are limited to offsets at the percent level, ~2 km/s in V_c. Marginalizing over all the systematics that we consider, we find that V_c(R_0) < 235 km/s at >99% confidence. We find an offset between the Sun's rotational velocity and the local circular velocity of 26 +/- 3 km/s, which is larger than the locally-measured solar motion of 12 km/s. This larger offset reconciles our value for V_c with recent claims that V_c >~ 240 km/s. Combining our results with other data, we find that the Milky Way's dark-halo mass within the virial radius is ~8x10^{11} M_sun.

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The vertical motions of mono-abundance sub-populations in the Milky Way disk

We present the vertical kinematics of stars in the Milky Way's stellar disk inferred from SDSS/SEGUE G-dwarf data, deriving the vertical velocity dispersion, σ_z, as a function of vertical height |z| and Galactocentric radius R for a set of 'mono-abundance' sub-populations of stars with very similar elemental abundances [α/Fe] and [Fe/H]. We find that all components exhibit nearly isothermal kinematics in |z|, and a slow outward decrease of the vertical velocity dispersion: σ_z (z,R|[α/Fe],[Fe/H]) ~ σ_z ([α/Fe],[Fe/H]) x \exp (-(R-R_0)/7 kpc}). The characteristic velocity dispersions of these components vary from ~ 15 km/s for chemically young, metal-rich stars, to >~ 50 km/s for metal poor stars. The mean σ_z gradient away from the mid plane is only 0.3 +/- 0.2 km/s/kpc. We find a continuum of vertical kinetic temperatures (~σ^2_z) as function of ([α/Fe],[Fe/H]), which contribute to the stellar surface mass density as Σ_{R_0}(σ^2_z) ~ \exp(-σ^2_z). The existence of isothermal mono-abundance populations with intermediate dispersions reject the notion of a thin-thick disk dichotomy. This continuum of disks argues against models where the thicker disk portions arise from massive satellite infall or heating; scenarios where either the oldest disk portion was born hot, or where internal evolution plays a major role, seem the most viable. The wide range of σ_z ([α/Fe],[Fe/H]) combined with a constant σ_z(z) for each abundance bin provides an independent check on the precision of the SEGUE abundances: δ_[α/Fe] ~ 0.07 dex and δ_[Fe/H] ~ 0.15 dex. The radial decline of the vertical dispersion presumably reflects the decrease in disk surface-mass density. This measurement constitutes a first step toward a purely dynamical estimate of the mass profile the disk in our Galaxy. [abridged]

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The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.

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Data analysis recipes: Probability calculus for inference

In this pedagogical text aimed at those wanting to start thinking about or brush up on probabilistic inference, I review the rules by which probability distribution functions can (and cannot) be combined. I connect these rules to the operations performed in probabilistic data analysis. Dimensional analysis is emphasized as a valuable tool for helping to construct non-wrong probabilistic statements. The applications of probability calculus in constructing likelihoods, marginalized likelihoods, posterior probabilities, and posterior predictions are all discussed.

physics.data-an↗

The spatial structure of mono-abundance sub-populations of the Milky Way disk

The spatial, kinematic, and elemental-abundance structure of the Milky Way's stellar disk is complex, and has been difficult to dissect with local spectroscopic or global photometric data. Here, we develop and apply a rigorous density modeling approach for Galactic spectroscopic surveys that enables investigation of the global spatial structure of stellar sub-populations in narrow bins of [α/Fe] and [Fe/H], using 23,767 G-type dwarfs from SDSS/SEGUE. We fit models for the number density of each such mono-abundance component, properly accounting for the complex spectroscopic SEGUE sampling of the underlying stellar population. We find that each mono-abundance sub-population has a simple spatial structure that can be described by a single exponential in both the vertical and radial direction, with continuously increasing scale heights (~200 pc to 1 kpc) and decreasing scale lengths (>4.5 kpc to 2 kpc) for increasingly older sub-populations, as indicated by their lower metallicities and [α/Fe] enhancements. That the abundance-selected sub-components with the largest scale heights have the shortest scale lengths is in sharp contrast with purely geometric `thick--thin disk' decompositions. To the extent that [α/Fe] is an adequate proxy for age, our results directly show that older disk sub-populations are more centrally concentrated, which implies inside-out formation of galactic disks. The fact that the largest scale-height sub-components are most centrally concentrated in the Milky Way is an almost inevitable consequence of explaining the vertical structure of the disk through internal evolution. Whether the simple spatial structure of the mono-abundance sub-components, and the striking correlations between age, scale length, and scale height can be plausibly explained by satellite accretion or other external heating remains to be seen.

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A data-driven model for spectra: Finding double redshifts in the Sloan Digital Sky Survey

We present a data-driven method - heteroscedastic matrix factorization, a kind of probabilistic factor analysis - for modeling or performing dimensionality reduction on observed spectra or other high-dimensional data with known but non-uniform observational uncertainties. The method uses an iterative inverse-variance-weighted least-squares minimization procedure to generate a best set of basis functions. The method is similar to principal components analysis, but with the substantial advantage that it uses measurement uncertainties in a responsible way and accounts naturally for poorly measured and missing data; it models the variance in the noise-deconvolved data space. A regularization can be applied, in the form of a smoothness prior (inspired by Gaussian processes) or a non-negative constraint, without making the method prohibitively slow. Because the method optimizes a justified scalar (related to the likelihood), the basis provides a better fit to the data in a probabilistic sense than any PCA basis. We test the method on SDSS spectra, concentrating on spectra known to contain two redshift components: These are spectra of gravitational lens candidates and massive black-hole binaries. We apply a hypothesis test to compare one-redshift and two-redshift models for these spectra, utilizing the data-driven model trained on a random subset of all SDSS spectra. This test confirms 129 of the 131 lens candidates in our sample and all of the known binary candidates, and turns up very few false positives.

astro-ph.CO↗

The Milky Way has no thick disk

Different stellar sub-populations of the Milky Way's stellar disk are known to have different vertical scale heights, their thickness increasing with age. Using SEGUE spectroscopic survey data, we have recently shown that mono-abundance sub-populations, defined in the [α/Fe]-[Fe/H] space, are well described by single exponential spatial-density profiles in both the radial and the vertical direction; therefore any star of a given abundance is clearly associated with a sub-population of scale height h_z. Here, we work out how to determine the stellar surface-mass density contributions at the solar radius R_0 of each such sub-population, accounting for the survey selection function, and for the fraction of the stellar population mass that is reflected in the spectroscopic target stars given populations of different abundances and their presumed age distributions. Taken together, this enables us to derive Σ_{R_0}(h_z), the surface-mass contributions of stellar populations with scale height h_z. Surprisingly, we find no hint of a thin-thick disk bi-modality in this mass-weighted scale-height distribution, but a smoothly decreasing function, approximately Σ_{R_0}(h_z)\propto \exp(-h_z), from h_z ~ 200 pc to h_z ~ 1 kpc. As h_z is ultimately the structurally defining property of a thin or thick disk, this shows clearly that the Milky Way has a continuous and monotonic distribution of disk thicknesses: there is no 'thick disk' sensibly characterized as a distinct component. We discuss how our result is consistent with evidence for seeming bi-modality in purely geometric disk decompositions, or chemical abundances analyses. We constrain the total visible stellar surface-mass density at the Solar radius to be Σ^*_{R_0} = 30 +/- 1 M_\odot pc^{-2}.

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Photometric redshifts and quasar probabilities from a single, data-driven generative model

We describe a technique for simultaneously classifying and estimating the redshift of quasars. It can separate quasars from stars in arbitrary redshift ranges, estimate full posterior distribution functions for the redshift, and naturally incorporate flux uncertainties, missing data, and multi-wavelength photometry. We build models of quasars in flux-redshift space by applying the extreme deconvolution technique to estimate the underlying density. By integrating this density over redshift one can obtain quasar flux-densities in different redshift ranges. This approach allows for efficient, consistent, and fast classification and photometric redshift estimation. This is achieved by combining the speed obtained by choosing simple analytical forms as the basis of our density model with the flexibility of non-parametric models through the use of many simple components with many parameters. We show that this technique is competitive with the best photometric quasar classification techniques---which are limited to fixed, broad redshift ranges and high signal-to-noise ratio data---and with the best photometric redshift techniques when applied to broadband optical data. We demonstrate that the inclusion of UV and NIR data significantly improves photometric quasar--star separation and essentially resolves all of the redshift degeneracies for quasars inherent to the ugriz filter system, even when included data have a low signal-to-noise ratio. For quasars spectroscopically confirmed by the SDSS 84 and 97 percent of the objects with GALEX UV and UKIDSS NIR data have photometric redshifts within 0.1 and 0.3, respectively, of the spectroscopic redshift; this amounts to about a factor of three improvement over ugriz-only photometric redshifts. Our code to calculate quasar probabilities and redshift probability distributions is publicly available.

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The Extreme Small Scales: Do Satellite Galaxies Trace Dark Matter?

We investigate the radial distribution of galaxies within their host dark matter halos by modeling their small-scale clustering, as measured in the Sloan Digital Sky Survey. Specifically, we model the Jiang et al. (2011) measurements of the galaxy two-point correlation function down to very small projected separations (10 < r < 400 kpc/h), in a wide range of luminosity threshold samples (absolute r-band magnitudes of -18 up to -23). We use a halo occupation distribution (HOD) framework with free parameters that specify both the number and spatial distribution of galaxies within their host dark matter halos. We assume that the first galaxy in each halo lives at the halo center and that additional satellite galaxies follow a radial density profile similar to the dark matter Navarro-Frenk-White (NFW) profile, except that the concentration and inner slope are allowed to vary. We find that in low luminosity samples, satellite galaxies have radial profiles that are consistent with NFW. M_r < -20 and brighter satellite galaxies have radial profiles with significantly steeper inner slopes than NFW (we find inner logarithmic slopes ranging from -1.6 to -2.1, as opposed to -1 for NFW). We define a useful metric of concentration, M_(1/10), which is the fraction of satellite galaxies (or mass) that are enclosed within one tenth of the virial radius of a halo. We find that M_(1/10) for low luminosity satellite galaxies agrees with NFW, whereas for luminous galaxies it is 2.5-4 times higher, demonstrating that these galaxies are substantially more centrally concentrated within their dark matter halos than the dark matter itself. Our results therefore suggest that the processes that govern the spatial distribution of galaxies, once they have merged into larger halos, must be luminosity dependent, such that luminous galaxies become poor tracers of the underlying dark matter.

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An Affine-Invariant Sampler for Exoplanet Fitting and Discovery in Radial Velocity Data

Markov Chain Monte Carlo (MCMC) proves to be powerful for Bayesian inference and in particular for exoplanet radial velocity fitting because MCMC provides more statistical information and makes better use of data than common approaches like chi-square fitting. However, the non-linear density functions encountered in these problems can make MCMC time-consuming. In this paper, we apply an ensemble sampler respecting affine invariance to orbital parameter extraction from radial velocity data. This new sampler has only one free parameter, and it does not require much tuning for good performance, which is important for automatization. The autocorrelation time of this sampler is approximately the same for all parameters and far smaller than Metropolis-Hastings, which means it requires many fewer function calls to produce the same number of independent samples. The affine-invariant sampler speeds up MCMC by hundreds of times compared with Metropolis-Hastings in the same computing situation. This novel sampler would be ideal for projects involving large datasets such as statistical investigations of planet distribution. The biggest obstacle to ensemble samplers is the existence of multiple local optima; we present a clustering technique to deal with local optima by clustering based on the likelihood of the walkers in the ensemble. We demonstrate the effectiveness of the sampler on real radial velocity data.

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The Color Variability of Quasars

We quantify quasar color-variability using an unprecedented variability database - ugriz photometry of 9093 quasars from SDSS Stripe 82, observed over 8 years at ~60 epochs each. We confirm previous reports that quasars become bluer when brightening. We find a redshift dependence of this blueing in a given set of bands (e.g. g and r), but show that it is the result of the flux contribution from less-variable or delayed emission lines in the different SDSS bands at different redshifts. After correcting for this effect, quasar color-variability is remarkably uniform, and independent not only of redshift, but also of quasar luminosity and black hole mass. The color variations of individual quasars, as they vary in brightness on year timescales, are much more pronounced than the ranges in color seen in samples of quasars across many orders of magnitude in luminosity. This indicates distinct physical mechanisms behind quasar variability and the observed range of quasar luminosities at a given black hole mass - quasar variations cannot be explained by changes in the mean accretion rate. We do find some dependence of the color variability on the characteristics of the flux variations themselves, with fast, low-amplitude, brightness variations producing more color variability. The observed behavior could arise if quasar variability results from flares or ephemeral hot spots in an accretion disc.

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Statistics of gamma-ray point sources below the Fermi detection limit

An analytic relation between the statistics of photons in pixels and the number counts of multi-photon point sources is used to constrain the distribution of gamma-ray point sources below the Fermi detection limit at energies above 1 GeV and at latitudes below and above 30 degrees. The derived source-count distribution is consistent with the distribution found by the Fermi collaboration based on the first Fermi point source catalogue. In particular, we find that the contribution of resolved and unresolved active galactic nuclei (AGN) to the total gamma-ray flux is below 20% - 25%. In the best fit model, the AGN-like point source fraction is 17% +- 2%. Using the fact that the Galactic emission varies across the sky while the extra-galactic diffuse emission is isotropic, we put a lower limit of 51% on Galactic diffuse emission and an upper limit of 32% on the contribution from extra-galactic weak sources, such as star-forming galaxies. Possible systematic uncertainties are discussed.

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