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Rubio, B., Gelletly, W., Algora, A., Nacher, E., & Tain, J. L. (2017). Beta decay studies with total absorption spectroscopy and the Lucrecia spectrometer at ISOLDE. J. Phys. G, 44(8), 084004–25pp.
Abstract: Here we present the experimental activities carried out at ISOLDE with the total absorption spectrometer Lucrecia, a large 4 pi scintillator detector designed to absorb a full gamma cascade following beta decay. This spectrometer is designed to measure beta-feeding to excited states without the systematic error called Pandemonium. The set up allows the measurement of decays of very short half life. Experimental results from several campaigns, that focus on the determination of the shapes of beta-decaying nuclei by measuring their beta decay strength distributions as a function of excitation energy in the daughter nucleus, are presented.
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T2K Collaboration(Abe, K. et al), Antonova, M., Cervera-Villanueva, A., Fernandez, P., Izmaylov, A., & Novella, P. (2019). Search for neutral-current induced single photon production at the ND280 near detector in T2K. J. Phys. G, 46(8), 08LT01–16pp.
Abstract: Neutrino neutral-current (NC) induced single photon production is a sub-leading order process for accelerator-based neutrino beam experiments including T2K. It is, however, an important process to understand because it is a background for electron (anti)neutrino appearance oscillation experiments. Here, we performed the first search of this process below 1 GeV using the fine-grained detector at the T2K ND280 off-axis near detector. By reconstructing single photon kinematics from electron-positron pairs, we achieved 95% pure gamma ray sample from 5.738 x 10(20) protons-on-targets neutrino mode data. We do not find positive evidence of NC induced single photon production in this sample. We set the model-dependent upper limit on the cross-section for this process, at 0.114 x 10(-38) cm(2) (90% C.L.) per nucleon, using the J-PARC off-axis neutrino beam with an average energy of < E-v > similar to 0.6 GeV. This is the first limit on this process below 1 GeV which is important for current and future oscillation experiments looking for electron neutrino appearance oscillation signals.
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Davesne, D., Pastore, A., & Navarro, J. (2013). Skyrme effective pseudopotential up to the next-to-next-to-leading order. J. Phys. G, 40(9), 095104–8pp.
Abstract: The explicit form of the next-to-next-to-leading order ((NLO)-L-2) of the Skyrme effective pseudopotential compatible with all required symmetries and especially with gauge invariance is presented in a Cartesian basis. It is shown in particular that for such a pseudopotential there is no spin-orbit contribution and that the D-wave term suggested in the original Skyrme formulation does not satisfy the invariance properties. The six new (NLO)-L-2 terms contribute to both the equation of state and the Landau parameters. These contributions to symmetric nuclear matter are given explicitly and discussed.
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Gonzalez, P. (2014). Generalized screened potential model. J. Phys. G, 41(9), 095001–12pp.
Abstract: A new non relativistic quark model to calculate the spectrum of heavy quark mesons is developed. The model is based on an interquark potential interaction that implicitly incorporates screening effects from meson-meson configurations. An analysis of the bottomonium spectrum shows the appearance of extra states as compared to conventional non screened potential models.
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Khosa, C. K., Mars, L., Richards, J., & Sanz, V. (2020). Convolutional neural networks for direct detection of dark matter. J. Phys. G, 47(9), 095201–20pp.
Abstract: The XENON1T experiment uses a time projection chamber (TPC) with liquid xenon to search for weakly interacting massive particles (WIMPs), a proposed dark matter particle, via direct detection. As this experiment relies on capturing rare events, the focus is on achieving a high recall of WIMP events. Hence the ability to distinguish between WIMP and the background is extremely important. To accomplish this, we suggest using convolutional neural networks (CNNs); a machine learning procedure mainly used in image recognition tasks. To explore this technique we use XENON collaboration open-source software to simulate the TPC graphical output of dark matter signals and main backgrounds. A CNN turns out to be a suitable tool for this purpose, as it can identify features in the images that differentiate the two types of events without the need to manipulate or remove data in order to focus on a particular region of the detector. We find that the CNN can distinguish between the dominant background events (ER) and 500 GeV WIMP events with a recall of 93.4%, precision of 81.2% and an accuracy of 87.2%.
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