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Garcia Navarro, J. E., Fernandez-Prieto, L. M., Villaseñor, A., Sanz, V., Ammirati, J. B., Diaz Suarez, E. A., et al. (2022). Performance of Deep Learning Pickers in Routine Network Processing Applications. Seismol. Res. Lett., 93, 2529–2542.
Abstract: Picking arrival times of P and S phases is a fundamental and time‐consuming task for the routine processing of seismic data acquired by permanent and temporary networks. A large number of automatic pickers have been developed, but to perform well they often require the tuning of multiple parameters to adapt them to each dataset. Despite the great advance in techniques, some problems remain, such as the difficulty to accurately pick S waves and earthquake recordings with a low signal‐to‐noise ratio. Recently, phase pickers based on deep learning (DL) have shown great potential for event identification and arrival‐time picking. However, the general adoption of these methods for the routine processing of monitoring networks has been held back by factors such as the availability of well‐documented software, computational resources, and a gap in knowledge of these methods. In this study, we evaluate recent available DL pickers for earthquake data, comparing the performance of several neural network architectures. We test the selected pickers using three datasets with different characteristics. We found that the analyzed DL pickers (generalized phase detection, PhaseNet, and EQTransformer) perform well in the three tested cases. They are very efficient at ignoring large‐amplitude transient noise and at picking S waves, a task that is often difficult even for experienced analysts. Nevertheless, the performance of the analyzed DL pickers varies widely in terms of sensitivity and false discovery rate, with some pickers missing a significant percentage of true picks and others producing a large number of false positives. There are also variations in run time between DL pickers, with some of them requiring significant resources to process large datasets. In spite of these drawbacks, we show that DL pickers can be used efficiently to process large seismic datasets and obtain results comparable or better than current standard procedures.
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Parashar, S., Karan, A., Avnish, Bandyopadhyay, P., & Ghosh, K. (2022). Phenomenology of scalar leptoquarks at the LHC in explaining the radiative neutrino masses, muon g-2, and lepton flavor violating observables. Phys. Rev. D, 106(9), 095040–34pp.
Abstract: We study the phenomenology of a particular leptoquark extension of the Standard Model (SM), namely the doublet-singlet scalar leptoquark extension of the SM (DSL-SM). Besides generating Majorana mass for neutrinos, these leptoquarks contribute to muon and electron (g – 2) and various lepton flavor violating processes. Collider signatures of the benchmark points (BPs), consistent with the neutrino oscillation data, anomalous muon/electron magnetic moments, experimental bounds on the charged lepton flavor violation observables, etc., are studied at the LHC/FCC with center-of-mass energies of 14, 27 and 100 TeV. While the two -1=3 charged colored scalars from the singlet and the doublet leptoquark mix with each other, the charge 2=3 colored scalar from the doublet leptoquark remains pure. With a near-degenerate mass spectrum, the pure and mixed leptoquark states are shown to be distinguishable from multiple final states, while discerning between the two mixed states remains very challenging.
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ATLAS Collaboration. (2022). A detailed map of Higgs boson interactions by the ATLAS experiment ten years after the discovery. Nature, 607(7917), 52–59.
Abstract: The standard model of particle physics(1-4) describes the known fundamental particles and forces that make up our Universe, with the exception of gravity. One of the central features of the standard model is a field that permeates all of space and interacts with fundamental particles(5-9). The quantum excitation of this field, known as the Higgs field, manifests itself as the Higgs boson, the only fundamental particle with no spin. In 2012, a particle with properties consistent with the Higgs boson of the standard model was observed by the ATLAS and CMS experiments at the Large Hadron Collider at CERN10,11. Since then, more than 30 times as many Higgs bosons have been recorded by the ATLAS experiment, enabling much more precise measurements and new tests of the theory. Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons-the carriers of the strong, electromagnetic and weak forces-are studied in detail. Interactions with three third-generation matter particles (bottom (b) and top (t) quarks, and tau leptons (tau)) are well measured and indications of interactions with a second-generation particle (muons, mu) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model.
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Gariazzo, S., Di Valentino, E., Mena, O., & Nunes, R. C. (2022). Late-time interacting cosmologies and the Hubble constant tension. Phys. Rev. D, 106(2), 023530–12pp.
Abstract: In this manuscript we reassess the potential of interacting dark matter-dark energy models in solving the Hubble constant tension. These models have been proposed but also questioned as possible solutions to the H0 problem. Here we examine several interacting scenarios against cosmological observations, focusing on the important role played by the calibration of supernovae data. In order to reassess the ability of interacting dark matter-dark energy scenarios in easing the Hubble constant tension, we systematically confront their theoretical predictions using a prior on the supernovae Ia absolute magnitude MB, which has been argued to be more robust and certainly less controversial than using a prior on the Hubble constant H0. While some data combinations do not show any preference for interacting dark sectors and in some of these scenarios the clustering sigma 8 tension worsens, interacting cosmologies with a dark energy equation of state w < -1 are preferred over the canonical lambda CDM picture even with cosmic microwave background data alone and also provide values of sigma 8 in perfect agreement with those from weak lensing surveys. Future cosmological surveys will test these exotic dark energy cosmologies by accurately measuring the dark energy equation of state and its putative redshift evolution.
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SCiMMA and SNEWS Collaborations(Baxter, A. L. et al), & Colomer, M. (2022). Collaborative experience between scientific software projects using Agile Scrum development. Softw.-Pract. Exp., 52, 2077–2096.
Abstract: Developing sustainable software for the scientific community requires expertise in software engineering and domain science. This can be challenging due to the unique needs of scientific software, the insufficient resources for software engineering practices in the scientific community, and the complexity of developing for evolving scientific contexts. While open-source software can partially address these concerns, it can introduce complicating dependencies and delay development. These issues can be reduced if scientists and software developers collaborate. We present a case study wherein scientists from the SuperNova Early Warning System collaborated with software developers from the Scalable Cyberinfrastructure for Multi-Messenger Astrophysics project. The collaboration addressed the difficulties of open-source software development, but presented additional risks to each team. For the scientists, there was a concern of relying on external systems and lacking control in the development process. For the developers, there was a risk in supporting a user-group while maintaining core development. These issues were mitigated by creating a second Agile Scrum framework in parallel with the developers' ongoing Agile Scrum process. This Agile collaboration promoted communication, ensured that the scientists had an active role in development, and allowed the developers to evaluate and implement the scientists' software requirements. The collaboration provided benefits for each group: the scientists actuated their development by using an existing platform, and the developers utilized the scientists' use-case to improve their systems. This case study suggests that scientists and software developers can avoid scientific computing issues by collaborating and that Agile Scrum methods can address emergent concerns.
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