BABAR Collaboration(Lees, J. P. et al), Martinez-Vidal, F., & Oyanguren, A. (2021). Study of the process e(+) e(-) -> pi(+)pi (-) pi(0) using initial state radiation with BABAR. Phys. Rev. D, 104(11), 112003–31pp.
Abstract: The process e(+)e(-) -> pi(+) pi(-) pi(0)gamma is studied at a center-of-mass energy near the Upsilon(4S) resonance using a data sample of 469 fb(-1) collected with the BABAR detector at the PEP-II collider. We have performed a precise measurement of the e(+)e(-) -> pi(+) pi(-) pi(0) cross section in the center-of-mass energy range from 0.62 to 3.5 GeV. In the energy regions of the omega and phi resonances, the cross section is measured with a systematic uncertainty of 1.3%. The leading-order hadronic contribution to the muon magnetic anomaly calculated using the measured e(+) e(-) -> pi(+) pi(-) pi(0) cross section from threshold to 2.0 GeV is (45.86 +/- 0.14 +/- 0.58) x 10(-10). From the fit to the measured 3 pi mass spectrum we have determined the resonance parameters Gamma(omega -> e(+)e(-)) B(omega -> pi(+) pi- pi(0)) = (0.5698 +/- 0.0031 +/- 0.0082) keV, Gamma(phi -> e(+)e(-)) B(phi -> pi(+) pi(-)pi(0)) = (0.1841 +/- 0.0021 +/- 0.0080) keV, and B(rho -> 3 pi) = (0.88 +/- 0.23 +/- 0.30) x 10(-4). The significance of the rho -> 3 pi signal is greater than 6 sigma. For the J/psi resonance we have measured the product Gamma(J/psi -> e(+) e(-)) B (J/psi -> 3 pi) = (0.1248 +/- 0.0019 +/- 0.0026) keV.
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Babiano-Suarez, V. et al, Lerendegui-Marco, J., Balibrea-Correa, J., Caballero, L., Calvo, D., Ladarescu, I., et al. (2021). Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques. Eur. Phys. J. A, 57(6), 197–17pp.
Abstract: i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (n, gamma) cross-section measurements using time-of-flight technique. This work presents the first experimental validation of the i-TED apparatus for high-resolution time-of-flight experiments and demonstrates for the first time the concept proposed for background rejection. To this aim, the Au-197(n, gamma) and Fe-56(n, gamma) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C6D6 detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of similar to 3 higher detection sensitivity than state-of-the-art C6D6 detectors in the 10 keV neutron-energy region of astrophysical interest. This paper explores also the perspectives of further enhancement in performance attainable with the final i-TED array consisting of twenty position-sensitive detectors and newanalysis methodologies based on Machine-Learning techniques.
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Baglio, J., Campanario, F., Glaus, S., Muhlleitner, M., Ronca, J., & Spira, M. (2021). gg -> HH: Combined uncertainties. Phys. Rev. D, 103(5), 056002–5pp.
Abstract: In this paper we discuss the combination of the usual renormalization and factorization scale uncertainties of Higgs-pair production via gluon fusion with the novel uncertainties originating from the scheme and scale choice of the virtual top mass. Moreover, we address the uncertainties related to the top-mass definition for different values of the trilinear Higgs coupling and their combination with the other uncertainties.
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Balazs, C. et al, Mamuzic, J., & Ruiz de Austri, R. (2021). A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications. J. High Energy Phys., 05(5), 108–46pp.
Abstract: Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.
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Balibrea-Correa, J., Lerendegui-Marco, J., Babiano-Suarez, V., Caballero, L., Calvo, D., Ladarescu, I., et al. (2021). Machine Learning aided 3D-position reconstruction in large LaCl3 crystals. Nucl. Instrum. Methods Phys. Res. A, 1001, 165249–17pp.
Abstract: We investigate five different models to reconstruct the 3D gamma-ray hit coordinates in five large LaCl3(Ce) monolithic crystals optically coupled to pixelated silicon photomultipliers. These scintillators have a base surface of 50 x 50 mm(2) and five different thicknesses, from 10 mm to 30 mm. Four of these models are analytical prescriptions and one is based on a Convolutional Neural Network. Average resolutions close to 1-2 mm fwhm are obtained in the transverse crystal plane for crystal thicknesses between 10 mm and 20 mm using analytical models. For thicker crystals average resolutions of about 3-5 mm fwhm are obtained. Depth of interaction resolutions between 1 mm and 4 mm are achieved depending on the distance of the interaction point to the photosensor surface. We propose a Machine Learning algorithm to correct for linearity distortions and pin-cushion effects. The latter allows one to keep a large field of view of about 70%-80% of the crystal surface, regardless of crystal thickness. This work is aimed at optimizing the performance of the so-called Total Energy Detector with Compton imaging capability (i-TED) for time-of-flight neutron capture cross-section measurements.
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