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NEXT Collaboration(Cebrian, S. et al), Alvarez, V., Carcel, S., Cervera-Villanueva, A., Diaz, J., Ferrario, P., et al. (2015). Accurate gamma and MeV-electron track reconstruction with an ultra-low diffusion Xenon/TMA TPC at 10 atm. Nucl. Instrum. Methods Phys. Res. A, 804, 8–24.
Abstract: We report the performance of a 10 atm Xenon/trimethylamine time projection chamber (TPC) for the detection of X-rays (30 keV) and gamma-rays (0.511-1.275 MeV) in conjunction with the accurate tracking of the associated electrons. When operated at such a high pressure and in similar to 1%-admixtures, trimethylamine (TMA) endows Xenon with an extremely low electron diffusion (1.3 +/- 0.13 mm-sigma (longitudinal), 0.95 +/- 0.20 mm-sigma (transverse) along 1 m drift) besides forming a convenient Penning-Fluorescent' mixture. The TPC, that houses 1.1 kg of gas in its fiducial volume, operated continuously for 100 live-days in charge amplification mode. The readout was performed through the recently introduced microbulk Micromegas technology and the AFTER chip, providing a 3D voxelization of 8 mm x 8 mm x 1.2 mm for approximately 10 cm/MeV-long electron tracks. Resolution in energy (epsilon) at full width half maximum (R) inside the fiducial volume ranged from R = 14.6% (30 keV) to R = 4.6% (1.275 MeV). This work was developed as part of the R&D program of the NEXT collaboration for future detector upgrades in the search of the neutrino-less double beta decay (beta beta 0 nu) in Xe-136, specifically those based on novel gas mixtures. Therefore we ultimately focus on the calorimetric and topological properties of the reconstructed MeV-electron tracks. In particular, the obtained energy resolution has been decomposed in its various contributions and improvements towards achieving the R =1.4%root MeV/epsilon levels obtained in small sensors are discussed.
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NEXT Collaboration(Serra, L. et al), Sorel, M., Alvarez, V., Carcel, S., Cervera-Villanueva, A., Diaz, J., et al. (2015). An improved measurement of electron-ion recombination in high-pressure xenon gas. J. Instrum., 10, P03025–21pp.
Abstract: We report on results obtained with the NEXT-DEMO prototype of the NEXT-100 high-pressure xenon gas time projection chamber (TPC), filled with pure xenon gas at 10 bar pressure and exposed to an alpha decay calibration source. Compared to our previous measurements with alpha particles, an upgraded detector and improved analysis techniques have been used. We measure event-by-event correlated fluctuations between ionization and scintillation due to electronion recombination in the gas, with correlation coefficients between -0.80 and -0.56 depending on the drift field conditions. By combining the two signals, we obtain a 2.8% FWHM energy resolution for 5.49 MeV alpha particles and a measurement of the optical gain of the electroluminescent TPC. The improved energy resolution also allows us to measure the specific activity of the radon in the gas due to natural impurities. Finally, we measure the average ratio of excited to ionized atoms produced in the xenon gas by alpha particles to be 0.561 +/- 0.045, translating into an average energy to produce a primary scintillation photon of W-ex = (39.2 +/- 3.2) eV.
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Belver, D., Blanco, A., Cabanelas, P., Diaz, J., Fonte, P., Garzon, J. A., et al. (2012). Analysis of the space-time microstructure of cosmic ray air showers using the HADES RPC TOF wall. J. Instrum., 7, P10007–9pp.
Abstract: Cosmic rays have been studied, since they were discovered one century ago, with a very broad spectrum of detectors and techniques. However, never the properties of the extended air showers (EAS) induced by high energy primary cosmic rays had been analysed at the Earth surface with a high granularity detector and a time resolution at the 0.1 ns scale. The commissioning of the timing RPC (Resistive Plate Chambers) time of flight wall of the HADES spectrometer with cosmic rays, at the GSI (Darmstadt, Germany), opened up that opportunity. During the last months of 2009, more than 500 millions of cosmic ray events were recorded by a stack of two RPC modules, of about 1.25 m(2) each, able to measure swarms of up to similar to 100 particles with a time resolution better than 100 ps. In this document it is demonstrated how such a relative small two-plane, high-granularity timing RPC setup may provide significant information about the properties of the shower and hence about the primary cosmic ray properties.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
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NEXT Collaboration(Renner, J. et al), Benlloch-Rodriguez, J., Botas, A., Ferrario, P., Gomez-Cadenas, J. J., Alvarez, V., et al. (2017). Background rejection in NEXT using deep neural networks. J. Instrum., 12, T01004–21pp.
Abstract: 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.
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NEXT Collaboration(Simon, A. et al), Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., Lopez-March, N., et al. (2021). Boosting background suppression in the NEXT experiment through Richardson-Lucy deconvolution. J. High Energy Phys., 07(7), 146–38pp.
Abstract: Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of <similar to> 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.
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NEXT Collaboration(Martinez-Lema, G. et al), Palmeiro, B., Botas, A., Laing, A., Renner, J., Simon, A., et al. (2018). Calibration of the NEXT-White detector using Kr-83m decays. J. Instrum., 13, P10014–21pp.
Abstract: The NEXT-White (NEW) detector is currently the largest radio-pure high-pressure xenon gas time projection chamber with electroluminescent readout in the world. It has been operating at Laboratorio Subterraneo de Canfranc (LSC) since October 2016. This paper describes the calibrations performed using Kr-83m decays during a long run taken from March to November 2017 (Run II). Krypton calibrations are used to correct for the finite drift-electron lifetime as well as for the dependence of the measured energy on the event transverse position which is caused by variations in solid angle coverage both for direct and reflected light and edge effects. After producing calibration maps to correct for both effects we measure an excellent energy resolution for 41.5 keV point-like deposits of (4.553 +/- 0.010 (stat.) +/- 0.324 (sys.)) % FWHM in the full chamber and (3.804 +/- 0.013 (stat.) +/- 0.112 (sys.)) % FWHM in a restricted fiducial volume. Using naive 1/root E scaling, these values translate into resolutions of (0.5916 +/- 0.0014 (stat.) +/- 0.0421 (sys.)) % FWHM and (0.4943 +/- 0.0017 (stat.) +/- 0.0146 (sys.)) % FWHM at the Q(beta beta) energy of xenon double beta decay (2458 keV), well within range of our target value of 1%.
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NEXT Collaboration(Lorca, D. et al), Martin-Albo, J., Laing, A., Ferrario, P., Gomez-Cadenas, J. J., Alvarez, V., et al. (2014). Characterisation of NEXT-DEMO using xenon K-alpha X-rays. J. Instrum., 9, P10007–20pp.
Abstract: The NEXT experiment aims to observe the neutrinoless double beta decay of Xe-136 in a high-pressure xenon gas TPC using electroluminescence (EL) to amplify the signal from ionization. Understanding the response of the detector is imperative in achieving a consistent and well understood energy measurement. The abundance of xenon K-shell X-ray emission during data taking has been identified as a multitool for the characterisation of the fundamental parameters of the gas as well as the equalisation of the response of the detector. The NEXT-DEMO prototype is a similar to 1.5 kg volume TPC filled with natural xenon. It employs an array of 19 PMTs as an energy plane and of 256 SiPMs as a tracking plane with the TPC light tube and SiPM surfaces being coated with tetraphenyl butadiene (TPB) which acts as a wavelength shifter for the VUV scintillation light produced by xenon. This paper presents the measurement of the properties of the drift of electrons in the TPC, the effects of the EL production region, and the extraction of position dependent correction constants using K-alpha X-ray deposits. These constants were used to equalise the response of the detector to deposits left by gammas from Na-22.
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HADES Collaboration(Agakishiev, G. et al), Diaz, J., & Gil, A. (2013). Deep sub-threshold K*(892)(0) production in collisions of Ar + KCl at 1.76A GeV. Eur. Phys. J. A, 49(3), 34–7pp.
Abstract: Results on the deep sub-threshold production of the short-lived hadronic resonance K*(892)(0) are reported for collisions of Ar + KCl at 1.76 A GeV beam energy, studied with the High Acceptance Di-Electron Spectrometer (HADES) at SIS18/GSI. The K*(892)(0) production probability per central collision of P-K*0 = (4.4 +/- 1.1 +/- 0.5) x 10(-4) and the K*(892)(0)/K-0 ratio of P-K*0/P-K0 = (1.9 +/- 0.5 +/- 0.3) x 10(-2) are determined at the lowest energy so far (i.e. deep below the threshold for the corresponding production in nucleon-nucleon collisions, root s(NN)-root s(thr) = -340MeV). The K*(0)/K-0 ratio is compared with results of other experiments and with the predictions of the UrQMD transport approach and of the statistical hadronization model. The experimental K*(0) yield and the K-*0/K-0 ratio are overestimated by the transport model by factors of about five and two, respectively. In a chemically equilibrated medium the ratio corresponds to a temperature of the thermalized system being systematically lower than the value determined by the yields of the stable and long-lived hadrons produced in Ar + KCl collisions. From the present measurement, we conclude that sub-threshold K* production either cannot be considered to proceed in a system being in thermal equilibrium or these short-lived resonances appear undersaturated, for example as a result of the rescattering of the decay particles in the ambient hadronic medium.
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NEXT Collaboration(Kekic, M. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., et al. (2021). Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment. J. High Energy Phys., 01(1), 189–22pp.
Abstract: Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses.
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