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DUNE Collaboration(Abud, A. A. et al), Amar Es-Sghir, H., Amedo, P., Antonova, M., Barenboim, G., Benitez Montiel, C., et al. (2024). Performance of a modular ton-scale pixel-readout liquid argon time projection chamber. Instruments, 8, 41–45pp.
Abstract: The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations.
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LHCb Collaboration(Aaij, R. et al), Jaimes Elles, S. J., Jashal, B. K., Libralon, S., Martinez-Vidal, F., Oyanguren, A., et al. (2024). Comprehensive analysis of local and nonlocal amplitudes in the B0→K∗0μ+μ− decay. J. High Energy Phys., 09, 026.
Abstract: A comprehensive study of the local and nonlocal amplitudes contributing to the decay B0→K∗0(→K+π−)μ+μ− is performed by analysing the phase-space distribution of the decay products. The analysis is based on pp collision data corresponding to an integrated luminosity of 8.4fb−1 collected by the LHCb experiment. This measurement employs for the first time a model of both one-particle and two-particle nonlocal amplitudes, and utilises the complete dimuon mass spectrum without any veto regions around the narrow charmonium resonances. In this way it is possible to explicitly isolate the local and nonlocal contributions and capture the interference between them. The results show that interference with nonlocal contributions, although larger than predicted, only has a minor impact on the Wilson Coefficients determined from the fit to the data. For the local contributions, the Wilson Coefficient C9, responsible for vector dimuon currents, exhibits a 2.1σ deviation from the Standard Model expectation. The Wilson Coefficients C10, C′9 and C′10 are all in better agreement than C9 with the Standard Model and the global significance is at the level of 1.5σ. The model used also accounts for nonlocal contributions from B0→K∗0[τ+τ−→μ+μ−] rescattering, resulting in the first direct measurement of the bsττ vector effective-coupling C9τ.
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Gonzalez-Iglesias, D., Gimeno, B., Esperante, D., Martinez-Reviriego, P., Martin-Luna, P., Pedraza, L. K., et al. (2024). A rapid method for prediction of the non-resonant ultra-fast multipactor regime in high gradient RF accelerating structures. Results Phys., 64, 107921–9pp.
Abstract: The purpose of this work is to present an analytical method that allows to estimate in an approximate and fast way the presence of the non-resonant and ultra-fast multipactor effect in RF accelerating structures in the presence of high gradient electromagnetic fields. This single-surface multipactor regime, which has been little studied in the scientific literature, is characterised by appearing only under conditions of very strong RF electric fields (of the order of tens or hundreds of MV/m), where it is predominant over other types of single- or dual-surface resonance described in classical multipactor theory. This type of multipactor causes a rapid growth of the electron population and poses a serious drawback in the operation of RF accelerator components operating under high gradient conditions. Specifically, in dielectric-assist accelerating structures (DAA) it has been experimentally found that the presence of multipactor limits the maximum operating gradient of these components due to a significant increase in the reflected power due to the discharge, being this phenomenon the main problem to overcome. In a previous work, we found and described in detail by means of numerical simulations the presence of this non-resonant and ultra-fast multipactor regime in a DAA structure design for hadrontherapy. Here we aim to present a simple and fast method to predict the presence of this non-resonant and ultra-fast multipactor regime in RF accelerator structures with cylindrical revolution symmetry around the acceleration axis. This method is especially useful in the design stages of accelerating structures as it provides much faster results than numerical simulations of the multipactor, with quite good accuracy in a wide range of cases as shown in this paper.
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Martin-Luna, P., Bonatto, A., Bontoiu, C., Xia, G., & Resta-Lopez, J. (2024). Plasmonic excitations in double-walled carbon nanotubes. Results Phys., 60, 107698–11pp.
Abstract: The interactions of charged particles moving paraxially in multi-walled carbon nanotubes (MWCNTs) may excite electromagnetic modes. This wake effect has recently been proposed as a potential novel method of short-wavelength high-gradient particle acceleration. In this work, the excitation of wakefields in double-walled carbon nanotubes (DWCNTs) is studied by means of the linearized hydrodynamic theory. General expressions have been derived for the excited longitudinal and transverse wakefields and related to the resonant wavenumbers which can be obtained from the dispersion relation. In the absence of friction, the stopping power of the wakefield driver, modelled here as a charged macroparticle, can be written solely as a function of these resonant wavenumbers. The dependencies of the wakefields on the radii of the DWCNT and the driving velocity have been studied. DWCNTs with inter-wall distances much smaller than the internal radius may be a potential option to obtain higher wakefields for particle acceleration compared to single-walled carbon nanotubes (SWCNTs).
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Barenboim, G., Del Debbio, L., Hirn, J., & Sanz, V. (2024). Exploring how a generative AI interprets music. Neural Comput. Appl., 36, 17007–17022.
Abstract: We aim to investigate how closely neural networks (NNs) mimic human thinking. As a step in this direction, we study the behavior of artificial neuron(s) that fire most when the input data score high on some specific emergent concepts. In this paper, we focus on music, where the emergent concepts are those of rhythm, pitch and melody as commonly used by humans. As a black box to pry open, we focus on Google’s MusicVAE, a pre-trained NN that handles music tracks by encoding them in terms of 512 latent variables. We show that several hundreds of these latent variables are “irrelevant” in the sense that can be set to zero with minimal impact on the reconstruction accuracy. The remaining few dozens of latent variables can be sorted by order of relevance by comparing their variance. We show that the first few most relevant variables, and only those, correlate highly with dozens of human-defined measures that describe rhythm and pitch in music pieces, thereby efficiently encapsulating many of these human-understandable concepts in a few nonlinear variables.
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