Papoulias, D. K., Kosmas, T. S., Sahu, R., Kota, V. K. B., & Hota, M. (2020). Constraining nuclear physics parameters with current and future COHERENT data. Phys. Lett. B, 800, 135133–9pp.
Abstract: Motivated by the recent observation of coherent elastic neutrino-nucleus scattering (CE nu NS) at the COHERENT experiment, our goal is to explore its potential in probing important nuclear structure parameters. We show that the recent COHERENT data offers unique opportunities to investigate the neutron nuclear form factor. Our present calculations are based on the deformed Shell Model (DSM) method which leads to a better fit of the recent CE nu NS data, as compared to known phenomenological form factors such as the Helm-type, symmetrized Fermi and Klein-Nystrand. The attainable sensitivities and the prospects of improvement during the next phase of the COHERENT experiment are also considered and analyzed in the framework of two upgrade scenarios.
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Papavassiliou, J. (2022). Emergence of mass in the gauge sector of QCD. Chin. Phys. C, 46(11), 112001–23pp.
Abstract: It is currently widely accepted that gluons, while massless at the level of the fundamental QCD Lagrangian, acquire an effective mass through the non-Abelian implementation of the classic Schwinger mechanism. The key dynamical ingredient that triggers the onset of this mechanism is the formation of composite massless poles inside the fundamental vertices of the theory. These poles enter the evolution equation of the gluon propagator and nontrivially affect the way the Slavnov-Taylor identities of the vertices are resolved, inducing a smoking-gun displacement in the corresponding Ward identities. In this article, we present a comprehensive review of the pivotal concepts associated with this dynamical scenario, emphasizing the synergy between functional methods and lattice simulations and highlighting recent advances that corroborate the action of the Schwinger mechanism in QCD.
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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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Pakarinen, J. et al, & Algora, A. (2017). Collectivity in Pb-196, Pb-198 isotopes probed in Coulomb-excitation experiments at REX-ISOLDE. J. Phys. G, 44(6), 064009–10pp.
Abstract: The neutron-deficient Pb-196,Pb-198 isotopes have been studied in Coulomb-excitation experiments employing the Miniball gamma-ray spectrometer and radioactive ion beams from the REX-ISOLDE post-accelerator at CERN. The reduced transition probabilities of the first excited 2(+) states in Pb-196 and Pb-198 nuclei have been measured for the first time. Values of B (E2) = 18.2(-4.1)(+4.8) W. u. and B (E2) = 13.1(-3.5)(+4.9) W. u., were obtained, respectively. The experiment sheds light on the development of collectivity when moving from the regime governed by the generalised seniority scheme to a region, where intruding structures, associated with different deformed shapes, start to come down in energy and approach the spherical ground state.
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Pajtler, M. V. et al, & Gadea, A. (2021). Excited states of Y-90,Y-92,Y-94 populated in Zr-90+Pb-208 multinucleon transfer reaction. Phys. Scr., 96(3), 035305–7pp.
Abstract: Multinucleon transfer reactions in Zr-90+Pb-208 have been studied via fragment-gamma coincidences, employing the PRISMA magnetic spectrometer coupled to the CLARA gamma-array. An analysis on Y isotopes has been carried out incorporating spectroscopic as well as reaction mechanism aspects. New gamma transitions have been observed in Y-94, confirming the findings of recent studies where nuclei were produced via fission of uranium, and a comparison with near-by Y-90,Y-92 isotopes populated in the same reaction has been discussed. Experimental cross sections have been extracted and compared with the GRAZING calculations, showing a fair agreement along the neutron pick-up side. The results confirm how multinucleon transfer reactions are a suitable mechanism for the study of neutron-rich nuclei.
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Pagura, V. P., Gomez Dumm, D., Noguera, S., & Scoccola, N. N. (2017). Magnetic catalysis and inverse magnetic catalysis in nonlocal chiral quark models. Phys. Rev. D, 95(3), 034013–7pp.
Abstract: We study the behavior of strongly interacting matter under an external constant magnetic field in the context of nonlocal chiral quark models within the mean field approximation. We find that at zero temperature the behavior of the quark condensates shows the expected magnetic catalysis effect, our predictions being in good quantitative agreement with lattice QCD results. On the other hand, in contrast to what happens in the standard local Nambu-Jona-Lasinio model, when the analysis is extended to the case of finite temperature, our results show that nonlocal models naturally lead to the inverse magnetic catalysis effect.
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NEXT Collaboration(Monrabal, F. et al), Laing, A., Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., et al. (2018). The NEXT White (NEW) detector. J. Instrum., 13, P12010–38pp.
Abstract: Conceived to host 5 kg of xenon at a pressure of 15 bar in the fiducial volume, the NEXT-White apparatus is currently the largest high pressure xenon gas TPC using electroluminescent amplification in the world. It is also a 1:2 scale model of the NEXT-100 detector for Xe-136 beta beta 0 nu decay searches, scheduled to start operations in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2016 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. This paper describes the detector and associated infrastructures, as well as the main aspects of its initial operation.
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Otten, S., Rolbiecki, K., Caron, S., Kim, J. S., Ruiz de Austri, R., & Tattersall, J. (2020). DeepXS: fast approximation of MSSM electroweak cross sections at NLO. Eur. Phys. J. C, 80(1), 12–9pp.
Abstract: We present a deep learning solution to the prediction of particle production cross sections over a complicated, high-dimensional parameter space. We demonstrate the applicability by providing state-of-the-art predictions for the production of charginos and neutralinos at the Large Hadron Collider (LHC) at the next-to-leading order in the phenomenological MSSM-19 and explicitly demonstrate the performance for pp ->(chi) over tilde (+)(1)(chi) over tilde (-)(1), (chi) over tilde (0)(2)(chi) over tilde (0)(2) and (chi) over tilde (0)(2)(chi) over tilde (+/-)(1) as a proof of concept which will be extended to all SUSY electroweak pairs. We obtain errors that are lower than the uncertainty from scale and parton distribution functions with mean absolute percentage errors of well below 0.5% allowing a safe inference at the next-to-leading order with inference times that improve the Monte Carlo integration procedures that have been available so far by a factor of O(10(7)) from O(min) to O(mu s) per evaluation.
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Otten, S., Caron, S., de Swart, W., van Beekveld, M., Hendriks, L., van Leeuwen, C., et al. (2021). Event generation and statistical sampling for physics with deep generative models and a density information buffer. Nat. Commun., 12(1), 2985–16pp.
Abstract: Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events like Monte Carlo generators. We study three processes: a simple two-body decay, the processes e(+)e(-)-> Z -> l(+)l(-) and pp -> tt<mml:mo><overbar></mml:mover> including the decay of the top quarks and a simulation of the detector response. By buffering density information of encoded Monte Carlo events given the encoder of a Variational Autoencoder we are able to construct a prior for the sampling of new events from the decoder that yields distributions that are in very good agreement with real Monte Carlo events and are generated several orders of magnitude faster. Applications of this work include generic density estimation and sampling, targeted event generation via a principal component analysis of encoded ground truth data, anomaly detection and more efficient importance sampling, e.g., for the phase space integration of matrix elements in quantum field theories. Here, the authors report buffered-density variational autoencoders for the generation of physical events. This method is computationally less expensive over other traditional methods and beyond accelerating the data generation process, it can help to steer the generation and to detect anomalies.
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Otal, A., Celada, F., Chimeno, J., Vijande, J., Pellejero, S., Perez-Calatayud, M. J., et al. (2022). Review on Treatment Planning Systems for Cervix Brachytherapy (Interventional Radiotherapy): Some Desirable and Convenient Practical Aspects to Be Implemented from Radiation Oncologist and Medical Physics Perspectives. Cancers, 14(14), 3467–15pp.
Abstract: Simple Summary There are no brachytherapy treatment planning systems (TPS) exclusively for the treatment of cervical tumours, so general-purpose TPSs are used. However, these treatments have some particular features concerning the treatment of other pathologies, especially in the case of exclusive use of MRI as an imaging modality and the presence of gynaecological applicators in combination with an interstitial part. That is why it is essential to review the latest versions of commercial TPSs to find the potential features to improve with the help of a group of experimented medical physicists and radiation oncologists. Furthermore, after reviewing the recent literature for advances applicable to cervical brachytherapy and through his own clinical experience, possible improvements are proposed to software providers for the development of new tools. Intracavitary brachytherapy (BT, Interventional Radiotherapy, IRT), plays an essential role in the curative intent of locally advanced cervical cancer, for which the conventional approach involves external beam radiotherapy with concurrent chemotherapy followed by BT. This work aims to review the different methodologies used by commercially available treatment planning systems (TPSs) in exclusive magnetic resonance imaging-based (MRI) cervix BT with interstitial component treatments. Practical aspects and improvements to be implemented into the TPSs are discussed. This review is based on the clinical expertise of a group of radiation oncologists and medical physicists and on interactive demos provided by the software manufacturers. The TPS versions considered include all the new tools currently in development for future commercial releases. The specialists from the supplier companies were asked to propose solutions to some of the challenges often encountered in a clinical environment through a questionnaire. The results include not only such answers but also comments by the authors that, in their opinion, could help solve the challenges covered in these questions. This study summarizes the possibilities offered nowadays by commercial TPSs, highlighting the absence of some useful tools that would notably improve the planning of MR-based interstitial component cervix brachytherapy.
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