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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset. Eur. Phys. J. C, 83(7), 681–37pp.
Abstract: The flavour-tagging algorithms developed by the AvTLAS Collaboration and used to analyse its dataset of root s = 13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model t (t) over bar events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.
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Stoppa, F., Bhattacharyya, S., Ruiz de Austri, R., Vreeswijk, P., Caron, S., Zaharijas, G., et al. (2023). AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information. Astron. Astrophys., 680, A109–16pp.
Abstract: 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.
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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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Heavy Flavor Averaging Group(Amhis, Y. et al), & Oyanguren, A. (2023). Averages of b-hadron, c-handron, and t-lepton properties as of 2021. Phys. Rev. D, 107(5), 052008–365pp.
Abstract: This paper reports world averages of measurements of b-hadron, c-hadron, and τ-lepton properties obtained by the Heavy Flavor Averaging Group using results available before April 2021. In rare cases, significant results obtained several months later are also used. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, CP violation parameters, parameters of semileptonic decays, and Cabibbo-Kobayashi-Maskawa matrix elements.
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Brandao, P. C. S., Song, J., Abreu, L. M., & Oset, E. (2023). B+ decay to K+ ηη with (ηη) from the D bar-D(3720) bound state. Phys. Rev. D, 108(5), 054004–6pp.
Abstract: We search for a B decay mode where one can find a peak for a DD bound state predicted in effective theories and in lattice QCD calculations, which has also been claimed from some reactions that show an accumulated strength in D D over bar production at threshold. We find a good candidate in the B+-> K+eta eta reaction, by looking at the eta eta mass distribution. The reaction proceeds via a first step in which one has the B+-> D*+ D-0 reaction followed by D*(+) (s) decay to (DK+)-K-0 and a posterior fusion of D-0 over bar D-0 to eta eta, implemented through a triangle diagram that allows the D-0 over bar D-0 to be virtual and to produce the bound state. The choice of eta eta to see the peak is based on results of calculations that find the eta eta among the light pseudoscalar channels with stronger coupling to the D D over bar bound state. We find a neat peak around the predicted mass of that state in the eta eta mass distribution, with an integrated branching ratio for B+-> K+ (D D, bound); (D D, bound) -> eta eta of the order of 1.5 x 10(-4), a large number for hadronic B decays, which should motivate its experimental search.
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Oliver, S., Gimenez-Alventosa, V., Berumen, F., Gimenez, V., Beaulieu, L., Ballester, F., et al. (2023). Benchmark of the PenRed Monte Carlo framework for HDR brachytherapy. Z. Med. Phys., 33(4), 511–528.
Abstract: Purpose: The purpose of this study is to validate the PenRed Monte Carlo framework for clinical applications in brachytherapy. PenRed is a C++ version of Penelope Monte Carlo code with additional tallies and utilities. Methods and materials: Six benchmarking scenarios are explored to validate the use of PenRed and its improved bachytherapy-oriented capabilities for HDR brachytherapy. A new tally allowing the evaluation of collisional kerma for any material using the track length kerma estimator and the possibility to obtain the seed positions, weights and directions processing directly the DICOM file are now implemented in the PenRed distribution. The four non-clinical test cases developed by the Joint AAPM-ESTRO-ABG-ABS WG-DCAB were evaluated by comparing local and global absorbed dose differences with respect to established reference datasets. A prostate and a palliative lung cases, were also studied. For them, absorbed dose ratios, global absorbed dose differences, and cumulative dose-volume histograms were obtained and discussed. Results: The air-kerma strength and the dose rate constant corresponding to the two sources agree with the reference datatests within 0.3% (Sk) and 0.1% (K). With respect to the first three WG-DCAB test cases, more than 99.8% of the voxels present local (global) differences within +/- 1%(+/- 0.1%) of the reference datasets. For test Case 4 reference dataset, more than 94.9%(97.5%) of voxels show an agreement within +/- 1%(+/- 0.1%), better than similar benchmarking calculations in the literature. The track length kerma estimator scorer implemented increases the numerical efficiency of brachytherapy calculations two orders of magnitude, while the specific brachytherapy source allows the user to avoid the use of error-prone intermediate steps to translate the DICOM information into the simulation. In both clinical cases, only minor absorbed dose differences arise in the low-dose isodoses. 99.8% and 100% of the voxels have a global absorbed dose difference ratio within +/- 0.2%for the prostate and lung cases, respectively. The role played by the different segmentation and composition material in the bone structures was discussed, obtaining negligible absorbed dose differ-ences. Dose-volume histograms were in agreement with the reference data.Conclusions: PenRed incorporates new tallies and utilities and has been validated for its use for detailed and precise high-dose-rate brachytherapy simulations.
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Xu, Z. Y. et al, Algora, A., & Morales, A. I. (2023). Beta-delayed neutron spectroscopy of 133In. Phys. Rev. C, 108(1), 014314–9pp.
Abstract: The decay properties of 133In were studied in detail at the ISOLDE Decay Station. The implementation of the Resonance Ionization Laser Ion Source allowed separate measurements of its 9/2+ ground state (133gIn) and 1/2- isomer (133mIn). With the use of & beta;-delayed neutron and & gamma; spectroscopy, the decay strengths above the neutron separation energy were quantified in this neutron-rich nucleus for the first time. The allowed Gamow-Teller transition 9/2+ & RARR; 7/2+ was located at 5.93 MeV in the 133gIn decay with a log ft = 4.7(1). In addition, several neutron-unbound states were populated at lower excitation energies by the first-forbidden decays of 133g,mIn. We assigned spins and parities to those neutron-unbound states based on the & beta;-decay selection rules, the log ft values, and systematics.
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Fernandez Casani, A., Garcia Montoro, C., Gonzalez de la Hoz, S., Salt, J., Sanchez, J., & Villaplana Perez, M. (2023). Big Data Analytics for the ATLAS EventIndex Project with Apache Spark. Comput. Math. Methods, 2023, 6900908–19pp.
Abstract: The ATLAS EventIndex was designed to provide a global event catalogue and limited event-level metadata for ATLAS experiment of the Large Hadron Collider (LHC) and their analysis groups and users during Run 2 (2015-2018) and has been running in production since. The LHC Run 3, started in 2022, has seen increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. A new core storage service is being developed in HBase/Phoenix, and there is work in progress to provide at least the same functionality as the current one for increased data ingestion and search rates and with increasing volumes of stored data. In addition, new tools are being developed for solving the needed access cases within the new storage. This paper describes a new tool using Spark and implemented in Scala for accessing the big data quantities of the EventIndex project stored in HBase/Phoenix. With this tool, we can offer data discovery capabilities at different granularities, providing Spark Dataframes that can be used or refined within the same framework. Data analytic cases of the EventIndex project are implemented, like the search for duplicates of events from the same or different datasets. An algorithm and implementation for the calculation of overlap matrices of events across different datasets are presented. Our approach can be used by other higher-level tools and users, to ease access to the data in a performant and standard way using Spark abstractions. The provided tools decouple data access from the actual data schema, which makes it convenient to hide complexity and possible changes on the backed storage.
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Maso-Ferrando, A., Sanchis-Gual, N., Font, J. A., & Olmo, G. J. (2023). Birth of baby universes from gravitational collapse in a modified-gravity scenario. J. Cosmol. Astropart. Phys., 06(6), 028–19pp.
Abstract: We consider equilibrium models of spherical boson stars in Palatini f (R) = R + CR2 gravity and study their collapse when perturbed. The Einstein-Klein-Gordon system is solved using a recently established correspondence in an Einstein frame representation. We find that, in that frame, the endpoint is a nonrotating black hole surrounded by a quasi -stationary cloud of scalar field. However, the dynamics in the f (R) frame is dramatically different. The innermost region of the collapsing object exhibits the formation of a finite -size, exponentially-expanding baby universe connected with the outer (parent) universe via a minimal area surface (a throat or umbilical cord). Our simulations indicate that this surface is at all times hidden inside a horizon, causally disconnecting the baby universe from observers above the horizon. The implications of our findings in other areas of gravitational physics are also discussed.
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Blennow, M., Fernandez-Martinez, E., Hernandez-Garcia, J., Lopez-Pavon, J., Marcano, X., & Naredo-Tuero, D. (2023). Bounds on lepton non-unitarity and heavy neutrino mixing. J. High Energy Phys., 08(8), 030–41pp.
Abstract: We present an updated and improved global fit analysis of current flavour and electroweak precision observables to derive bounds on unitarity deviations of the leptonic mixing matrix and on the mixing of heavy neutrinos with the active flavours. This new analysis is motivated by new and updated experimental results on key observables such as V-ud, the invisible decay width of the Z boson and the W boson mass. It also improves upon previous studies by considering the full correlations among the different observables and explicitly calibrating the test statistic, which may present significant deviations from a & chi;(2) distribution. The results are provided for three different Type-I seesaw scenarios: the minimal scenario with only two additional right-handed neutrinos, the next to minimal one with three extra neutrinos, and the most general one with an arbitrary number of heavy neutrinos that we parametrise via a generic deviation from a unitary leptonic mixing matrix. Additionally, we also analyze the case of generic deviations from unitarity of the leptonic mixing matrix, not necessarily induced by the presence of additional neutrinos. This last case relaxes some correlations among the parameters and is able to provide a better fit to the data. Nevertheless, inducing only leptonic unitarity deviations avoiding both the correlations implied by the right-handed neutrino extension as well as more strongly constrained operators is challenging and would imply significantly more complex UV completions.
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