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Giare, W., Renzi, F., Melchiorri, A., Mena, O., & Di Valentino, E. (2022). Cosmological forecasts on thermal axions, relic neutrinos, and light elements. Mon. Not. Roy. Astron. Soc., 511(1), 1373–1382.
Abstract: One of the targets of future cosmic microwave background (CMB) and baryon acoustic oscillation measurements is to improve the current accuracy in the neutrino sector and reach a much better sensitivity on extra dark radiation in the early Universe. In this paper, we study how these improvements can be translated into constraining power for well-motivated extensions of the standard model of elementary particles that involve axions thermalized before the quantum chromodynamics (QCD) phase transition by scatterings with gluons. Assuming a fiducial Lambda cold dark matter cosmological model, we simulate future data for Stage-IV CMB-like and Dark Energy Spectroscopic Instrument (DESI)-like surveys and analyse a mixed scenario of axion and neutrino hot dark matter. We further account also for the effects of these QCD axions on the light element abundances predicted by big bang nucleosynthesis. The most constraining forecasted limits on the hot relic masses are m(a) less than or similar to 0.92 eV and n-ary sumation m(nu) less than or similar to 0.12 eV at 95 per cent Confidence Level, showing that future cosmic observations can substantially improve the current bounds, supporting multimessenger analyses of axion, neutrino, and primordial light element properties.
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Cranmer, K. et al, & Sanz, V. (2022). Publishing statistical models: Getting the most out of particle physics experiments. SciPost Phys., 12(1), 037–55pp.
Abstract: The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases – including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits – we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.
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Aarrestad, T. et al, Mamuzic, J., & Ruiz de Austri, R. (2022). Benchmark data and model independent event classification for the large hadron collider. SciPost Phys., 12(1), 043–57pp.
Abstract: We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of > 1 billion simulated LHC events corresponding to 10 fb(-1) of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge.
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Study of the doubly charmed tetraquark T-cc(+). Nat. Commun., 13(1), 3351–19pp.
Abstract: Quantum chromodynamics, the theory of the strong force, describes interactions of coloured quarks and gluons and the formation of hadronic matter. Conventional hadronic matter consists of baryons and mesons made of three quarks and quark-antiquark pairs, respectively. Particles with an alternative quark content are known as exotic states. Here a study is reported of an exotic narrow state in the (DD0)-D-0 pi(+) mass spectrum just below the D*+D-0 mass threshold produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The state is consistent with the ground isoscalar T-cc(+), tetraquark with a quark content of cc (u) over bar(d) over bar and spin-parity quantum numbers J(P) =1(+). Study of the DD mass spectra disfavours interpretation of the resonance as the isovector state. The decay structure via intermediate off-shell D*(+) mesons is consistent with the observed D-0 pi(+) mass distribution. To analyse the mass of the resonance and its coupling to the DID system, a dedicated model is developed under the assumption of an isoscalar axial-vector T-cc(+), state decaying to the D*D channel. Using this model, resonance parameters including the pole position, scattering length, effective range and compositeness are determined to reveal important information about the nature of the T-cc(+), state. In addition, an unexpected dependence of the production rate on track multiplicity is observed.
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Albiol, A., Albiol, F., Paredes, R., Plasencia-Martinez, J. M., Blanco Barrio, A., Garcia Santos, J. M., et al. (2022). A comparison of Covid-19 early detection between convolutional neural networks and radiologists. Insights Imaging, 13(1), 122–12pp.
Abstract: Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19.
Keywords: Deep learning; Covid-19; Radiology
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Guadilla, V. et al, Algora, A., Tain, J. L., Agramunt, J., Jordan, D., Monserrate, M., et al. (2022). Total absorption gamma-ray spectroscopy of the ss decays of Y-96gs,Y-m. Phys. Rev. C, 106(1), 014306–14pp.
Abstract: The ss decays of the ground state (gs) and isomeric state (m) of Y-96 have been studied with the total absorption gamma-ray spectroscopy technique at the Ion Guide Isotope Separator On-Line facility. The separation of the 8(+) isomeric state from the 0(-) ground state was achieved thanks to the purification capabilities of the JYFLTRAP double Penning trap system. The ss-intensity distributions of both decays have been independently determined. In the analyses the deexcitation of the 1581.6 keV level in Zr-96, in which conversion electron emission competes with pair production, has been carefully considered and found to have significant impact on the ss-detector efficiency, influencing the ss-intensity distribution obtained. Our results for Y-96gs (0(-)) confirm the large ground state to ground state ss-intensity probability, although a slightly larger value than reported in previous studies was obtained, amounting to 96.6(-2.1)(+0.3) % of the total ss intensity. Given that the decay of Y-96gs is the second most important contributor to the reactor antineutrino spectrum between 5 and 7 MeV, the impact of the present results on reactor antineutrino summation calculations has been evaluated. In the decay of Y-96m (8(+)), previously undetected ss intensity in transitions to states above 6 MeV has been observed. This shows the importance of total absorption gamma-ray spectroscopy measurements of ss decays with highly fragmented deexcitation patterns. Y-96m (8(+)) is a major contributor to reactor decay heat in uranium-plutonium and thorium-uranium fuels around 10 s after fission pulses, and the newly measured average ss and gamma energies differ significantly from the previous values in evaluated databases. The discrepancy is far above the previously quoted uncertainties. Finally, we also report on the successful implementation of an innovative total absorption gamma-ray spectroscopy analysis of the module-multiplicity gated spectra, as a first proof of principle to distinguish between decaying states with very different spin-parity values.
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Angles-Alcazar, D., Genel, S., Marinacci, F., Spergel, D. N., et al. (2022). Inferring Halo Masses with Graph Neural Networks. Astrophys. J., 935(1), 30–15pp.
Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).
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AGATA Collaboration(Rezynkina, K. et al), Gadea, A., & Perez-Vidal, R. M. (2022). Structure of As-83, As- 85, and As-87: From semimagicity to gamma softness. Phys. Rev. C, 106(1), 014320–14pp.
Abstract: The structure of As-83,As- 85, and As-87 have been studied in fusion-fission reaction( 238)U+9Be. Fission fragments were identified in mass and atomic number using the VAMOS++ spectrometer and the coincident gamma rays were detected in the gamma-ray tracking array AGATA. New transitions in 83As and 85As are reported and placed in the level schemes. A level scheme of the excited states in 87As is proposed for the first time. The data are interpreted in frame of large-scale shell-model calculations, SU3 symmetries, and beyond mean-field frameworks. A spherical regime at magic number N = 50 is predicted and the location of the proton g9/2 orbital is proposed for the first time. Development of collectivity in a prolate deformed, gamma-soft regime in the open shell cases 85As and 87As, most neutron-rich isotopes beyond N = 50, is concluded. Data and theoretical calculations give confidence to a relatively high extrapolated excitation energy about 4 MeV of the 9/2+ state in 79Cu, one proton above 78Ni.
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Alonso, I. et al, & Bernabeu, J. (2022). Cold atoms in space: community workshop summary and proposed road-map. EPJ Quantum Technol., 9(1), 30–55pp.
Abstract: We summarise the discussions at a virtual Community Workshop on Cold Atoms in Space concerning the status of cold atom technologies, the prospective scientific and societal opportunities offered by their deployment in space, and the developments needed before cold atoms could be operated in space. The cold atom technologies discussed include atomic clocks, quantum gravimeters and accelerometers, and atom interferometers. Prospective applications include metrology, geodesy and measurement of terrestrial mass change due to, e.g., climate change, and fundamental science experiments such as tests of the equivalence principle, searches for dark matter, measurements of gravitational waves and tests of quantum mechanics. We review the current status of cold atom technologies and outline the requirements for their space qualification, including the development paths and the corresponding technical milestones, and identifying possible pathfinder missions to pave the way for missions to exploit the full potential of cold atoms in space. Finally, we present a first draft of a possible road-map for achieving these goals, that we propose for discussion by the interested cold atom, Earth Observation, fundamental physics and other prospective scientific user communities, together with the European Space Agency (ESA) and national space and research funding agencies.
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Morales, A. I., & Tuzon, P. (2022). Misconceptions, Knowledge, and Attitudes Towards the Phenomenon of Radioactivity. Sci. Educ., 31, 405–426.
Abstract: The teaching of the phenomenon of radioactivity is considered a key ingredient in the path towards developing critical thinking skills in many secondary science education curricula. Despite being one of the basic concepts in general physics courses, the scientific teaching literature of the last 40 years reports a great deal of misconceptions and conceptual errors related to radioactivity that seemingly appear regardless of the educational level and context. This study reports the first cross-sectional diagnostic study in Spain to secondary education students and pre-service teachers. Data were collected in the year 2019 through a questionnaire adapted from a previously validated one to explore the main misconceptions, attitudes, and knowledge status on the topic on a sample of 191 secondary school students and 29 Physics-and-Chemistry trainee teachers in the Spanish region of Valencia. Open and closed questions were used to categorize the entity itself, its properties, and the main misconceptions related to radioactivity. The responses were analysed using conventional statistical methods. The results indicate an evolution from a widespread dissenting notion on the phenomenon, which is staunchly related to danger, hazard, and destruction in the lowest educational levels, towards a more rational, relative, and multidimensional perspective in the highest ones. On the other hand, the ideas, emotions, and attitudes of the inquired individuals are in good agreement with the main misconceptions reported in the literature.
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