Fri·Aug 7, 2020Friday·August 7, 2020

1. 01*

   Decay scheme of 50V

   F. A. Danevich🇺🇦 · M. Hult🇧🇪 · D. V. Kasperovych🇺🇦 · V.R. Klavdiienko🇺🇦 · G. Lutter🇧🇪 · G. Marissens🇧🇪 · O. G. Polischuk🇺🇦 · V. I. Tretyak🇺🇦

   Investigation of the ${}^{50}$V electron-capture to the $2^{+}$ 1553.8 keV level of ${}^{50}$Ti and search for ${\beta }^{-}$ decay of ${}^{50}$V to the $2^{+}$ 783.3 keV level of ${}^{50}$Cr (both those decays are fourfold forbidden with $\Delta J^{\Delta \pi }=4^{+}$) have been performed using a vanadium sample of natural isotopic abundance with mass of 955 g. The measurements were conducted with the help of an ultra low-background HPGe-detector system located 225 m underground in the laboratory HADES (Belgium). The measured value of the half-life of ${}^{50}$V for electron capture was $T_{1/2}^{\mathrm{EC}}=(2.77_{-0.19}^{+0.20})\times 10^{17}$ yr. The ${\beta }^{-}$-decay branch was not detected and the corresponding lower bound of the half-life was $T_{1/2}^{\beta }\ge 8.9\times 10^{18}$ yr at the 90\% confidence level.

   nucl-exPRC(2020)·5 citations
2. 02*

   Correlating $h\to {\mu }^{+}{\mu }^{-}$ to the Anomalous Magnetic Moment of the Muon via Leptoquarks

   Andreas Crivellin🇨🇭 · Dario Mueller🇨🇭 · Francesco Saturnino🇨🇭

   Recently, both ATLAS and CMS measured the decay $h\to {\mu }^{+}{\mu }^{-}$, finding a signal strength with respect to the Standard Model expectation of $1.2\pm 0.6$ and $1.19\begin{array}{c}+0.41+0.17\\ -0.39-0.16\end{array}$, respectively. This provides, for the first time, evidence that the Standard Model Higgs couples to second generation fermions. This measurement is particularly interesting in the context of the intriguing hints for lepton flavor universality violation, accumulated within recent years, as new physics explanations could also be tested in the $h\to {\mu }^{+}{\mu }^{-}$ decay mode. Leptoquarks are prime candidates to account for the flavor anomalies. In particular, they can provide the necessary chiral enhancement (by a factor $m_t/m_{\mu }$) to address $a_{\mu }$ with TeV scale new physics. In this letter we point out that such explanations of $a_{\mu }$ also lead to enhanced effects in $h\to {\mu }^{+}{\mu }^{-}$ and we examine the correlations between $h\to {\mu }^{+}{\mu }^{-}$ and $a_{\mu }$ within leptoquark models. We find that the effect in the branching ratio of $h\to {\mu }^{+}{\mu }^{-}$ ranges from several percent up to a factor three, if one aims at accounting for $a_{\mu }$ at the $2\sigma$ level. Hence, the new ATLAS and CMS measurements already provide important constraints on the parameter space, rule out specific $a_{\mu }$ explanations and will be very important to test the flavor anomalies in the future.

   ↳ hep-phhep-exnucl-exnucl-thPRL(2021)·84 citations
3. 03*

   New data for the definition of neutron beams for Boron Neutron Capture Therapy

   M. Macías · B. Fernández🇪🇸 · J. Praena🇪🇸

   Boron Neutron Capture Therapy (BNCT) is a neutron radiotherapy used to treat tumours cells previously doping with Boron-10. This therapy requires an epithermal neutron beam for the treatment of deep tumours and a thermal beam for shallow ones. Thanks to recent high-current commercial accelerators, Accelerator-Based Neutron Sources (ABNS) are competitive option for providing therapeutic neutron beams in hospitals. In this work, the neutron field generated by the ${}^7$Li(p,n)${}^7$Be reaction at $1950$keV is studied as neutron source in ABNS, being measured by the Time-Of-Flight (TOF) technique at HiSPANoS facility (Spain). Moreover, two Beam Shaping Assemblies (BSA) for deep and shallow tumour treatment, which are specially designed for the $1950$keV neutron field, are evaluated for BNCT via Monte Carlo simulations (MCNP). Results in agreement with the International Atomic Energy Agency (IAEA) figures of merit endorse the use of this neutron field for BNCT.

   ↳ physics.ins-detnucl-exphysics.app-phphysics.med-phRadiat.Phys.Chem.(2021)·0 citations
4. 04*

   Unsupervised Learning for Identifying Events in Active Target Experiments

   Robert Solli · Daniel Bazin🇺🇸 · Michelle P. Kuchera🇺🇸 · Ryan R. Strauss🇩🇪 · Morten Hjorth-Jensen🇺🇸

   This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on ${}^{46}$Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 convolutional neural network. We study clustering performance on both data from a simulated ${}^{46}$Ar experiment, and real events from the AT-TPC detector. We find that a $k$-means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+$k$-means approach finds high purity clusters of proton events for real experimental data. We also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

   ↳ cs.CVnucl-exNucl.Instrum.Meth.A(2021)·6 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.