Stoppa, F., Vreeswijk, P., Bloemen, S., Bhattacharyya, S., Caron, S., Johannesson, G., et al. (2022). AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian. Astron. Astrophys., 662, A109–8pp.
Abstract: 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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Stoppa, F., Ruiz de Austri, R., Vreeswijk, P., Bhattacharyya, S., Caron, S., Bloemen, S., et al. (2023). AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation. Astron. Astrophys., 680, A108–14pp.
Abstract: 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.
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Trotta, R., Johannesson, G., Moskalenko, I. V., Porter, T. A., Ruiz de Austri, R., & Strong, A. W. (2011). Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis. Astrophys. J., 729(2), 106–16pp.
Abstract: Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.
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ANTARES Collaboration(Albert, A. et al), Barrios-Marti, J., Coleiro, A., Colomer, M., Hernandez-Rey, J. J., Illuminati, G., et al. (2019). The search for high-energy neutrinos coincident with fast radio bursts with the ANTARES neutrino telescope. Mon. Not. Roy. Astron. Soc., 482(1), 184–193.
Abstract: In the past decade, a new class of bright transient radio sources with millisecond duration has been discovered. The origin of these so-called fast radio bursts (FRBs) is still a mystery, despite the growing observational efforts made by various multiwavelength and multimessenger facilities. To date, many models have been proposed to explain FRBs, but neither the progenitors nor the radiative and the particle acceleration processes at work have been clearly identified. In this paper, we assess whether hadronic processes may occur in the vicinity of the FRB source. If they do, FRBs may contribute to the high-energy cosmic-ray and neutrino fluxes. A search for these hadronic signatures was carried out using the ANTARES neutrino telescope. The analysis consists in looking for high-energy neutrinos, in the TeV-PeV regime, that are spatially and temporally coincident with the detected FRBs. Most of the FRBs discovered in the period 2013-2017 were in the field of view of the ANTARES detector, which is sensitive mostly to events originating from the Southern hemisphere. From this period, 12 FRBs were selected and no coincident neutrino candidate was observed. Upper limits on the per-burst neutrino fluence were derived using a power-law spectrum, dN/DE nu proportional to E-nu(-gamma), for the incoming neutrino flux, assuming spectral indexes gamma = 1.0, 2.0, 2.5. Finally, the neutrino energy was constrained by computing the total energy radiated in neutrinos, assuming different distances for the FRBs. Constraints on the neutrino fluence and on the energy released were derived from the associated null results.
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Villanueva-Domingo, P., Gnedin, N. Y., & Mena, O. (2018). Warm Dark Matter and Cosmic Reionization. Astrophys. J., 852(2), 139–7pp.
Abstract: In models with dark matter made of particles with keV masses, such as a sterile neutrino, small-scale density perturbations are suppressed, delaying the period at which the lowest mass galaxies are formed and therefore shifting the reionization processes to later epochs. In this study, focusing on Warm Dark Matter (WDM) with masses close to its present lower bound, i.e., around the 3. keV region, we derive constraints from galaxy luminosity functions, the ionization history and the Gunn-Peterson effect. We show that even if star formation efficiency in the simulations is adjusted to match the observed UV galaxy luminosity functions in both CDM and WDM models, the full distribution of Gunn-Peterson optical depth retains the strong signature of delayed reionization in the WDM model. However, until the star formation and stellar feedback model used in modern galaxy formation simulations is constrained better, any conclusions on the nature of dark matter derived from reionization observables remain model-dependent.
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ATLAS Collaboration(Abat, E. et al), Bernabeu Verdu, J., Castillo Gimenez, V., Costa, M. J., Escobar, C., Ferrer, A., et al. (2011). A layer correlation technique for pion energy calibration at the 2004 ATLAS Combined Beam Test. J. Instrum., 6, P06001–35pp.
Abstract: A new method for calibrating the hadron response of a segmented calorimeter is developed and successfully applied to beam test data. It is based on a principal component analysis of energy deposits in the calorimeter layers, exploiting longitudinal shower development information to improve the measured energy resolution. Corrections for invisible hadronic energy and energy lost in dead material in front of and between the calorimeters of the ATLAS experiment were calculated with simulated Geant4 Monte Carlo events and used to reconstruct the energy of pions impinging on the calorimeters during the 2004 Barrel Combined Beam Test at the CERN H8 area. For pion beams with energies between 20 GeV and 180 GeV, the particle energy is reconstructed within 3% and the energy resolution is improved by between 11% and 25% compared to the resolution at the electromagnetic scale.
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CALICE Collaboration(White, A. et al), & Irles, A. (2023). Design, construction and commissioning of a technological prototype of a highly granular SiPM-on-tile scintillator-steel hadronic calorimeter. J. Instrum., 18(11), P11018–39pp.
Abstract: The CALICE collaboration is developing highly granular electromagnetic and hadronic calorimeters for detectors at future energy frontier electron-positron colliders. After successful tests of a physics prototype, a technological prototype of the Analog Hadron Calorimeter has been built, based on a design and construction techniques scalable to a collider detector. The prototype consists of a steel absorber structure and active layers of small scintillator tiles that are individually read out by directly coupled SiPMs. Each layer has an active area of 72 x 72 cm2 and a tile size of 3 x 3 cm2. With 38 active layers, the prototype has nearly 22, 000 readout channels, and its total thickness amounts to 4.4 nuclear interaction lengths. The dedicated readout electronics provide time stamping of each hit with an expected resolution of about 1 ns. The prototype was constructed in 2017 and commissioned in beam tests at DESY. It recorded muons, hadron showers and electron showers at different energies in test beams at CERN in 2018. In this paper, the design of the prototype, its construction and commissioning are described. The methods used to calibrate the detector are detailed, and the performance achieved in terms of uniformity and stability is presented.
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