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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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ATLAS Tile Calorimeter Community(Abdallah, J. et al), Castillo Gimenez, V., Costelo, J., Ferrer, A., Fullana, E., Gonzalez, V., et al. (2013). The optical instrumentation of the ATLAS Tile Calorimeter. J. Instrum., 8, P01005–21pp.
Abstract: The Tile Calorimeter, covering the central region of the ATLAS experiment up to pseudorapidities of +/-1.7, is a sampling device built with scintillating tiles that alternate with iron plates. The light is collected in wave-length shifting (WLS) fibers and is read out with photomultipliers. In the characteristic geometry of this calorimeter the tiles lie in planes perpendicular to the beams, resulting in a very simple and modular mechanical and optical layout. This paper focuses on the procedures applied in the optical instrumentation of the calorimeter, which involved the assembly of about 460,000 scintillator tiles and 550,000 WLS fibers. The outcome is a hadronic calorimeter that meets the ATLAS performance requirements, as shown in this paper.
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Agaras, M. N. et al, & Fiorini, L. (2023). Laser calibration of the ATLAS Tile Calorimeter during LHC Run 2. J. Instrum., 18(6), P06023–35pp.
Abstract: This article reports the laser calibration of the hadronic Tile Calorimeter of the ATLAS experiment in the LHC Run 2 data campaign. The upgraded Laser II calibration system is described. The system was commissioned during the first LHC Long Shutdown, exhibiting a stability better than 0.8% for the laser light monitoring. The methods employed to derive the detector calibration factors with data from the laser calibration runs are also detailed. These allowed to correct for the response fluctuations of the 9852 photomultiplier tubes of the Tile Calorimeter with a total uncertainty of 0.5% plus a luminosity-dependent sub-dominant term. Finally, we report the regular monitoring and performance studies using laser events in both standalone runs and during proton collisions. These studies include channel timing and quality inspection, and photomultiplier linearity and response dependence on anode current.
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Bazeia, D., Losano, L., Olmo, G. J., & Rubiera-Garcia, D. (2017). Geodesically complete BTZ-type solutions of 2+1 Born-Infeld gravity. Class. Quantum Gravity, 34(4), 045006–21pp.
Abstract: We study Born-Infeld gravity coupled to a static, non-rotating electric field in 2 + 1 dimensions and find exact analytical solutions. Two families of such solutions represent geodesically complete, and hence nonsingular, spacetimes. Another family represents a point-like charge with a singularity at the center. Despite the absence of rotation, these solutions resemble the charged, rotating BTZ solution of general relativity but with a richer structure in terms of horizons. The nonsingular character of the first two families turn out to be attached to the emergence of a wormhole structure on their innermost region. This seems to be a generic prediction of extensions of general relativity formulated in metric-affine (or Palatini) spaces, where metric and connection are regarded as independent degrees of freedom.
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Hall, O. et al, Agramunt, J., Algora, A., Domingo-Pardo, C., Morales, A. I., Rubio, B., et al. (2021). beta-delayed neutron emission of r-process nuclei at the N=82 shell closure. Phys. Lett. B, 816, 136266–7pp.
Abstract: Theoretical models of beta-delayed neutron emission are used as crucial inputs in r-process calculations. Benchmarking the predictions of these models is a challenge due to a lack of currently available experimental data. In this work the beta-delayed neutron emission probabilities of 33 nuclides in the important mass regions south and south-west of Sn-132 are presented, 16 for the first time. The measurements were performed at RIKEN using the Advanced Implantation Detector Array (AIDA) and the BRIKEN neutron detector array. The P-1n values presented constrain the predictions of theoretical models in the region, affecting the final abundance distribution of the second r-process peak at A approximate to 130.
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Marco-Hernandez, R., Alves, D., Angoletta, M. E., Marqversen, O., Molendijk, J., Oponowicz, E., et al. (2017). The AD and ELENA orbit, trajectory and intensity measurement systems. J. Instrum., 12, P07024–24pp.
Abstract: This paper describes the new Antiproton Decelerator (AD) orbit measurement system and the Extra Low ENergy Antiproton ring (ELENA) orbit, trajectory and intensity measurement system. The AD machine at European Organization for Nuclear Research (CERN) is presently being used to decelerate antiprotons from 3.57 GeV/c to 100 MeV/c for matter vs anti-matter comparative studies. The ELENA machine, presently under commissioning, has been designed to provide an extra deceleration stage down to 13.7 MeV/c. The AD orbit system is based on 32 horizontal and 27 vertical electrostatic Beam Position Monitor (BPM) fitted with existing low noise front-end amplifiers while the ELENA system consists of 24 BPMs equipped with new low-noise head amplifiers. In both systems the front-end amplifiers generate a difference (delta) and a sum (sigma) signal which are sent to the digital acquisition system, placed tens of meters away from the AD or ELENA rings, where they are digitized and further processed. The beam position is calculated by dividing the difference signal by the sum signal either using directly the raw digitized data for measuring the turn-by-turn trajectory in the ELENA system or after down-mixing the signals to baseband for the orbit measurement in both machines. The digitized sigma signal will be used in the ELENA system to calculate the bunched beam intensity and the Schottky parameters with coasting beam after passing through different signal processing chain. The digital acquisition arrangement for both systems is based on the same hardware, also used in the ELENA Low Level Radio Frequency (LLRF) system, which follows the VME Switched Serial (VXS) enhancement of the Versa Module Eurocard 64x extension (VME64x) standard and includes VITA 57 standard Field Programmable Gate Array Mezzanine Card (FMC). The digital acquisition Field Programmable Gate Array (FPGA) andDigital Signal Processor (DSP) firmware sharesmany common functionalities with the LLRF system but has been tailored for this measurement application in particular. Specific control and acquisition software has been developed for these systems. Both systems are installed in AD and ELENA. The AD orbit system currently measures the orbit in AD while the ELENA system is being used in the commissioning of the ELENA ring.
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ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Escobar, C., et al. (2011). Search for quark contact interactions in dijet angular distributions in pp collisions at sqrt(s)=7 TeV measured with the ATLAS detector. Phys. Lett. B, 694(4-5), 327–345.
Abstract: Dijet angular distributions from the first LHC pp collisions at center-of-mass energy root s = 7 TeV have been measured with the ATLAS detector. The dataset used for this analysis represents an integrated luminosity of 3.1 pb(-1). Dijet chi distributions and centrality ratios have been measured up to dijet masses of 2.8 TeV, and found to be in good agreement with Standard Model predictions. Analysis of the chi distributions excludes quark contact interactions with a compositeness scale Lambda below 3.4 TeV, at 95% confidence level, significantly exceeding previous limits.
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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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Aliaga, R. J., Herrero-Bosch, V., Capra, S., Pullia, A., Duenas, J. A., Grassi, L., et al. (2015). Conceptual design of the TRACE detector readout using a compact, dead time-less analog memory ASIC. Nucl. Instrum. Methods Phys. Res. A, 800, 34–39.
Abstract: The new TRacking Array for light Charged particle Ejectiles (TRACE) detector system requires monitorization and sampling of all pulses in a large number of channels with very strict space and power consumption restrictions for the front-end electronics and cabling, Its readout system is to be based on analog memory ASICs with 64 channels each that sample a 1 μs window of the waveform of any valid pulses at 200 MHz while discarding any other signals and are read out at 50 MHz with external ADC digitization. For this purpose, a new, compact analog memory architecture is described that allows pulse capture with zero dead time in any channel while vastly reducing the total number of storage cells, particularly for large amounts of input channels. This is accomplished by partitioning the typical Switched Capacitor Array structure into two pipelined, asymmetric stages and introducing FIFO queue-like control circuitry for captured data, achieving total independence between the capture and readout operations.
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