Background rejection in NEXT using deep neural networks

[EN] We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.The NEXT Collaboration acknowledges support from the following agencies and institutions: the European Research Council (ERC) under the Advanced Grant 339787-NEXT; the Ministerio de Economia y Competitividad of Spain and FEDER under grants CONSOLIDER-Ingenio 2010 CSD2008-0037 (CUP), FIS2014-53371-C04 and the Severo Ochoa Program SEV-2014-0398; GVA under grant PROMETEO/2016/120. Fermilab is operated by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the United States Department of Energy. JR acknowledges support from a Fulbright Junior Research Award.Renner, J.; Farbin, A.; Muñoz Vidal, J.; Benlloch-Rodríguez, J.; Botas, A.; Ferrario, P.; Gómez-Cadenas, J.... (2017). Background rejection in NEXT using deep neural networks. Journal of Instrumentation. 12. https://doi.org/10.1088/1748-0221/12/01/T01004S1

Centrality evolution of the charged-particle pseudorapidity density over a broad pseudorapidity range in Pb-Pb collisions at root s(NN)=2.76TeV

Peer reviewe

VVV: The near-IR Milky Way bulge and plane survey

The ESO public survey “VISTA Variables in the Via Lactea” (VVV) started mapping the inner disk and bulge of our Galaxy with the VISTA 4m telescope in the near-IR in 2010. The planned survey area of 520 deg2 is observed in the Z, Y, J, H and Ks filters, and in addition more than 100 epochs of repeated imaging in Ks will be collected over ∼5 years. The final products will be a deep near-IR atlas in five passbands, and catalogue of more than a million variable sources. This public survey will provide data available to the whole community and therefore will enable further studies of the history of the Milky Way, its star cluster evolution, and the population census of the Galactic Bulge and center, as well as the investigations of the star formation regions in the disk

VVV: The near-IR Milky Way bulge and plane survey*

The ESO public survey “VISTA Variables in the Via Lactea” (VVV) started mapping the inner disk and bulge of our Galaxy with the VISTA 4m telescope in the near-IR in 2010. The planned survey area of 520 deg2 is observed in the Z, Y, J, H and Ks filters, and in addition more than 100 epochs of repeated imaging in Ks will be collected over ∼5 years. The final products will be a deep near-IR atlas in five passbands, and catalogue of more than a million variable sources. This public survey will provide data available to the whole community and therefore will enable further studies of the history of the Milky Way, its star cluster evolution, and the population census of the Galactic Bulge and center, as well as the investigations of the star formation regions in the disk

Influence of MWCNT/surfactant dispersions on the rheology of Portland cement pastes

This work studies the effect of MWCNT/surfactant aqueous dispersions on the rheology of cement paste. Three types of surfactants (sodium dodecyl sulfate, cetylpyridinium chloride and triton TX-100) were used to prepare cement pastes with and without MWCNT. Three rheological parameters were determined for each sample: static yield stress, yield stress, and viscosity. The first was measured directly, while the other two were obtained by fitting a Bingham model to the descending portion of a flow curve. Additionally, X-ray diffraction and isothermal calorimetry were used to follow the hydration reaction of cement during the first hour. It was found that the MWCNT/surfactant dispersions generate an overall shift to higher yield stress values while maintaining viscosity, suggesting a modification of the interparticle attraction. It was concluded that the triple interaction MWCNT-surfactant-cement governs the rheology of cement pastes. © 2018 Elsevier Lt

Reinforcing Effect of Carbon Nanotubes/Surfactant Dispersions in Portland Cement Pastes

Decoupling the individual effects of multiwalled carbon nanotubes (MWCNTs) and surfactants when used as reinforcement materials in cement-based composites is aimed in this study. Powder MWCNTs were dispersed in deionized water using different types of surfactants as chemical dispersing agents and an ultrasonic tip processor. Cement pastes with carbon nanotubes additions of 0.15% by mass of cement were produced in two steps: first, the MWCNT/surfactant dispersions were combined with the mixing water, and then, cement was added and mixed until a homogeneous paste was obtained. Mechanical properties of the pastes cured at 7 days were measured, and their fracture behavior was characterized using the linear elastic finite element analysis. It was found that the reinforcing effect of MWCNT was masked by the negative effect of surfactants in the cement matrix; nevertheless, nanotubes were capable of increasing both stress and strain capacity of the composite by controlling the crack propagation process at the tip of the crack. © 2018 Oscar A. Mendoza Reales et al