Conde, D., Castillo, F. L., Escobar, C., García, C., Garcia Navarro, J. E., Sanz, V., et al. (2023). Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning. Space Weather, 21(11), e2023SW003474–27pp.
Abstract: Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests.
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Real, D., & Calvo, D. (2024). Low-Resource Time-to-Digital Converters for Field Programmable Gate Arrays: A Review. Sensors, 24(17), 5512–15pp.
Abstract: A fundamental aspect in the evolution of Time-to-Digital Converters (TDCs) implemented within Field-Programmable Gate Arrays (FPGAs), given the increasing demand for detection channels, is the optimization of resource utilization. This study reviews the principal methodologies employed for implementing low-resource TDCs in FPGAs. It outlines the foundational architectures and interpolation techniques utilized to bolster TDC performances without unduly burdening resource consumption. Low-resource Tapped Delay Line, Vernier Ring Oscillator, and Multi-Phase Shift Counter TDCs, including the use of SerDes, are reviewed. Additionally, novel low-resource architectures are scrutinized, including Counter Gray Oscillator TDCs and interpolation expansions using Process-Voltage-Temperature stable IODELAYs. Furthermore, the advantages and limitations of each approach are critically assessed, with particular emphasis on resolution, precision, non-linearities, and especially resource utilization. A comprehensive summary table encapsulating existing works on low-resource TDCs is provided, offering a comprehensive overview of the advancements in the field.
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Pino, F., Roe, N., Orero, A., Falcon, C., Rojas, S., Benlloch, J. M., et al. (2011). Development of a variable-radius pinhole SPECT system with a portable gamma camera. Rev. Esp. Med. Nucl., 30(5), 286–291.
Abstract: Objective: To develop a small-animal SPECT system using a low cost commercial portable gamma camera equipped with a pinhole collimator, a continuous scintillation crystal and a position-sensitive photomultiplier tube. Material and methods: The gamma camera was attached to a variable radius system, which enabled us to optimize sensitivity and resolution by adjusting the radius of rotation to the size of the object. To investigate the capability of the SPECT system for small animal imaging, the dependence of resolution and calibration parameters on radius was assessed and acquisitions of small phantoms and mice were carried out. Results: Resolution values, ranging from 1.0 mm for a radius of 21.4 mm and 1.4 mm for a radius of 37.2 mm were obtained, thereby justifying the interest of a variable radius SPECT system. Conclusions: The image quality of phantoms and animals were satisfactory, thus confirming the usefulness of the system for small animal SPECT imaging.
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Figueroa, D. G., Florio, A., & Torrenti, F. (2024). Present and future of Cosmo Lattice. Rep. Prog. Phys., 87(9), 094901–20pp.
Abstract: We discuss the present state and planned updates of Cosmo Lattice, a cutting-edge code for lattice simulations of non-linear dynamics of scalar-gauge field theories in an expanding background. We first review the current capabilities of the code, including the simulation of interacting singlet scalars and of Abelian and non-Abelian scalar-gauge theories. We also comment on new features recently implemented, such as the simulation of gravitational waves from scalar and gauge fields. Secondly, we discuss new extensions of C osmo L attice that we plan to release publicly. We comment on new physics modules, which include axion-gauge interactions phi FF , non-minimal gravitational couplings phi R-2 , creation and evolution of cosmic-defect networks, and magnetohydrodynamics. We also discuss new technical features, including evolvers for non-canonical interactions, arbitrary initial conditions, simulations in 2+1 dimensions, and higher-accuracy spatial derivatives.
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ATLAS Collaboration(Aad, G. et al), Aikot, A., Amos, K. R., Bouchhar, N., Cabrera Urban, S., Cantero, J., et al. (2025). Measurement of off-shell Higgs boson production in the H*→ZZ→4l decay channel using a neural simulation-based inference technique in 13 TeV pp collisions with the ATLAS detector. Rep. Prog. Phys., 88(5), 057803–38pp.
Abstract: A measurement of off-shell Higgs boson production in the H*-> ZZ -> 4l decay channel is presented. The measurement uses 140 fb-1 of proton-proton collisions at s=13 TeV collected by the ATLAS detector at the Large Hadron Collider and supersedes the previous result in this decay channel using the same dataset. The data analysis is performed using a neural simulation-based inference method, which builds per-event likelihood ratios using neural networks. The observed (expected) off-shell Higgs boson production signal strength in the ZZ -> 4l decay channel at 68% CL is 0.87-0.54+0.75 ( 1.00-0.95+1.04). The evidence for off-shell Higgs boson production using the ZZ -> 4l decay channel has an observed (expected) significance of 2.5 sigma (1.3 sigma). The expected result represents a significant improvement relative to that of the previous analysis of the same dataset, which obtained an expected significance of 0.5 sigma. When combined with the most recent ATLAS measurement in the ZZ -> 2l2 nu decay channel, the evidence for off-shell Higgs boson production has an observed (expected) significance of 3.7 sigma (2.4 sigma). The off-shell measurements are combined with the measurement of on-shell Higgs boson production to obtain constraints on the Higgs boson total width. The observed (expected) value of the Higgs boson width at 68% CL is 4.3-1.9+2.7 ( 4.1-3.4+3.5) MeV.
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