ABSTRACT The origin of the extragalactic γ-ray background (EGB) has been debated for some time. The EGB comprises the γ-ray emission from resolved and unresolved extragalactic sources, such as ...blazars, star-forming galaxies, and radio galaxies, as well as radiation from truly diffuse processes. This Letter focuses on the blazar source class, the most numerous detected population, and presents an updated luminosity function and spectral energy distribution model consistent with the blazar observations performed by the Fermi-Large Area Telescope (LAT). We show that blazars account for 50 % of the EGB photons (>0.1 GeV), and that Fermi-LAT has already resolved ∼70% of this contribution. Blazars, and in particular hard-spectrum sources such as BL Lacs, are responsible for most of the EGB emission above 100 GeV. We find that the extragalactic background light, which attenuates blazars' high-energy emission, is responsible for the high-energy cutoff observed in the EGB spectrum. Finally, we show that blazars, star-forming galaxies, and radio galaxies can naturally account for the amplitude and spectral shape of the background in the 0.1-820 GeV range, leaving only modest room for other contributions. This allows us to set competitive constraints on the dark matter annihilation cross section.
ABSTRACT
We revisit the computation of the extragalactic gamma‐ray signal from cosmological dark matter annihilations. The prediction of this signal is notoriously model‐dependent, due to different ...descriptions of the clumpiness of the dark matter distribution at small scales, responsible for an enhancement with respect to the smoothly distributed case. We show how a direct computation of this ‘flux multiplier’ in terms of the non‐linear power spectrum offers a conceptually simpler approach and may ease some problems, such as the extrapolation issue. In fact, very simple analytical recipes to construct the power spectrum yield results similar to the popular Halo Model expectations, with a straightforward alternative estimate of errors. For this specific application, one also obviates the need of identifying (often literature‐dependent) concepts entering the Halo Model, to compare different simulations.
We re-evaluate the extragalactic gamma-ray flux prediction from dark matter annihilation in the approach of integrating over the non-linear matter power spectrum, extrapolated to the free-streaming ...scale. We provide an estimate of the uncertainty based entirely on available N-body simulation results and minimal theoretical assumptions. We illustrate how an improvement in the simulation resolution, exemplified by the comparison between the Millennium and Millennium II simulations, affects our estimate of the flux uncertainty and we provide a ‘best guess’ value for the flux multiplier, based on the assumption of stable clustering for the dark matter perturbations described as a collision-less fluid. We achieve results comparable to traditional halo model calculations, but with a much simpler procedure and a more general approach, as it relies only on one, directly measurable quantity. In addition, we discuss the extension of our calculation to include baryonic effects as modelled in hydrodynamical cosmological simulations and other possible sources of uncertainty that would in turn affect indirect dark matter signals. Upper limits on the integrated power spectrum from supernovae lensing magnification are also derived and compared with theoretical expectations.
Although the emission of radiation from dark matter annihilation is expected to be maximized at the Galactic Center, geometric factors and the presence of point-like and diffuse backgrounds make the ...choice of the angular window size to optimize the chance of a signal detection a non-trivial problem. We find that the best strategy is to focus on an annulus around the Galactic Center of ∼1° to ≳30°, where the optimal size depends on the angular distribution of the signal and the backgrounds. Although our conclusions are general, we illustrate this point in the particular case of annihilation into two monochromatic photons in the phenomenologically most interesting range of energy 45
GeV
≲
E
≲
80
GeV, which is of great interest for the GLAST satellite. We find for example that dark matter models with sufficiently strong line annihilation signals, like the Inert Doublet Model, may be detectable without or with reasonable boost factors.
The nature of dark matter is a longstanding enigma of physics; it may consist of particles beyond the Standard Model that are still elusive to experiments. Among indirect search techniques, which ...look for stable products from the annihilation or decay of dark matter particles, or from axions coupling to high-energy photons, observations of the γ-ray sky have come to prominence over the last few years, because of the excellent sensitivity of the Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope mission. The LAT energy range from 20 meV to above 300 GeV is particularly well suited for searching for products of the interactions of dark matter particles. In this report we describe methods used to search for evidence of dark matter with the LAT, and review the status of searches performed with up to six years of LAT data. We also discuss the factors that determine the sensitivities of these searches, including the magnitudes of the signals and the relevant backgrounds, considering both statistical and systematic uncertainties. We project the expected sensitivities of each search method for 10 and 15 years of LAT data taking. In particular, we find that the sensitivity of searches targeting dwarf galaxies, which provide the best limits currently, will improve faster than the square root of observing time. Current LAT limits for dwarf galaxies using six years of data reach the thermal relic level for masses up to 120 GeV for the bb̄ annihilation channel for reasonable dark matter density profiles. With projected discoveries of additional dwarfs, these limits could extend to about 250 GeV. With as much as 15 years of LAT data these searches would be sensitive to dark matter annihilations at the thermal relic cross section for masses to greater than 400 GeV (200 GeV) in the bb̄(τ+τ−) annihilation channels.
AutoSourceID-FeatureExtractor Stoppa, F.; Ruiz de Austri, R.; Vreeswijk, P. ...
Astronomy and astrophysics (Berlin),
12/2023, Letnik:
680
Journal Article
Recenzirano
Odprti dostop
Aims
. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an ...area with room for improvement. We aim to design a network that can accurately estimate sources’ features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.
Methods
. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.
Results
. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the
Zwicky
Transient Facility (ZTF) to test its transfer learning abilities.
AutoSourceID-Classifier Stoppa, F.; Bhattacharyya, S.; Ruiz de Austri, R. ...
Astronomy and astrophysics (Berlin),
12/2023, Letnik:
680
Journal Article
Recenzirano
Odprti dostop
Aims.
Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the ...classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.
Methods.
The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.
Results.
We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
AutoSourceID-Light Stoppa, F.; Vreeswijk, P.; Bloemen, S. ...
Astronomy and astrophysics (Berlin),
06/2022, Letnik:
662
Journal Article
Recenzirano
Odprti dostop
Aims.
With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is ...paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images.
Methods.
We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location.
Results.
Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.
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