Simulation of large-scale fast neutron liquid scintillation detector

Neutron background measurement is always very important for dark matter detection due to almost the same effect for the recoiled nucleus scattered off by the incident neutron and dark matter particle. For deep under-ground experiments, the flux of neutron background is so low that large-scale detection is usually necessary. In this paper, by using Geant4, the relationship between detection efficiency and volume is investigated, meanwhile, two geometrical schemes for this detection including a single large-sized detector and arrayed multi-detector are compared under the condition of the same volume. The geometrical parameters of detectors are filtrated and detection efficiencies obtained under the similar background condition of China Jingping Underground Laboratory （CJPL）. The results show that for a large-scale Gd-doped liquid scintillation detector, the detection efficiency increases with the size of detector at the beginning and then trends toward a constant. Under the condition of the same length and cross section, the arrayed multi-detector has almost similar detection performance as the single large-sized detector, while too much detector number could cause degeneration of detection performance. Considering engineering factors, such as testing, assembling and production, the 4 × 4 arrayed detector scheme is flexible and more suitable. Furthermore, the conditions for using fast and slow signal coincidence detection and the detectable lower limit of neutron energy are evaluated by simulating the light process.

Digital pulse shape discrimination methods for n-γ separation in an EJ-301 liquid scintillation detector

A digital pulse shape discrimination system based on a programmable module NI-5772 has been established and tested with an EJ-301 liquid scintillation detector. The module was operated by running programs developed in Lab VIEW, with a sampling frequency up to 1.6 GS/s. Standard gamma sources ^22 Na,^137Cs and ^60 Co were used to calibrate the EJ-301 liquid scintillation detector, and the gamma response function was obtained. Digital algorithms for the charge comparison method and zero-crossing method have been developed. The experimental results show that both digital signal processing（DSP） algorithms can discriminate neutrons from γ-rays. Moreover,the zero-crossing method shows better n-γ discrimination at 80 ke Vee and lower, whereas the charge comparison method gives better results at higher thresholds. In addition, the figure-of-merit（FOM） for detectors of two different dimensions were extracted at 9 energy thresholds, and it was found that the smaller detector presented better n-γseparation for fission neutrons.

Study of n-γ discrimination in low energy range(above 40 keVee) by charge comparison method with a BC501A liquid scintillation detector

A VME-based experiment system for n-y discrimination using the charge comparison method was established.A data acquisition program for controlling the programmable modules and processing data online via VME64X bus was developed through the use of Lab VIEW.The two-dimensional（2D） scatter plots of the charge in the slow component vs.the total charge from ^（241）Am-Be and 252Cf neutron sources are presented.The 2D scatter plots of the energy vs.the ratio of the charge in the slow component to the total charge of the pulses are also presented.The quality of n-γ discrimination was checked by the figure-of-merit,and the results showed good performance of n-γ discrimination at the low energy range.Neutrons and γ-rays were separated above 50 keVee（electron-equivalent energy）.The quality of n-γ discrimination has been improved compared with others＇ results at five energies（150,250,350,450,550 keVee）.

Data-driven simultaneous vertex and energy reconstruction for large liquid scintillator detectors

High-precision vertex and energy reconstruction are crucial for large liquid scintillator detectors such as that at the Jiangmen Underground Neutrino Observatory(JUNO),especially for the determination of neutrino mass ordering by analyzing the energy spectrum of reactor neutrinos.This paper presents a data-driven method to obtain a more realistic and accurate expected PMT response of positron events in JUNO and develops a simultaneous vertex and energy reconstruction method that combines the charge and time information of PMTs.For the JUNO detector,the impact of the vertex inaccuracy on the energy resolution is approximately 0.6%.

Calibration and Unfolding of the Pulse Height Spectra of Liquid Scintillator-Based Neutron Detectors Using Photon Sources

An accurate energy calibration of a 5＂× 2＂ BC501A liquid scintillator-based neutron detector by means of photon sources and the unfolding of pulse height spectra are described. The photon responses were measured with 22Na, 137Cs and 54Mn photon sources and simulated using the GRESP code, which was developed at the Physiknlisch Technische Bundesanstalt in Germany. Pulse height spectra produced by three different photon sources were employed to investigate the effects of the unfolding techniques. It was found that the four unfolding codes of the HEPRO and UMG3.3 packages, including GRAVEL, UNFANA, MIEKE and MAXED, performed well with the test spectra and produced generally consistent results. They could therefore be used to obtain neutron energy spectra in toknmak experiments.

Event vertex and time reconstruction in large-volume liquid scintillator detectors

Large-volume liquid scintillator detectors with ultra-low background levels have been widely used to study neutrino physics and search for dark matter.Event vertex and event time are not only useful for event selection but also essential for the reconstruction of event energy.In this study,four event vertex and event time reconstruction algorithms using charge and time information collected by photomultiplier tubes were analyzed comprehensively.The effects of photomultiplier tube properties were also investigated.The results indicate that the transit time spread is the main effect degrading the vertex reconstruction,while the effect of dark noise is limited.In addition,when the event is close to the detector boundary,the charge information provides better performance for vertex reconstruction than the time information.

Improvement of machine learning-based vertex reconstruction for large liquid scintillator detectors with multiple types of PMTs

The precise vertex reconstruction for large liquid scintillator detectors is essential.A novel machine learning-based method was successfully developed to reconstruct an event vertex in JUNO.In this study,the performance of machine learning-based vertex reconstruction was further improved by optimizing the input images of neural networks.By separating the information of different types of PMTs and adding the information of the second hit of PMTs,the vertex resolution was improved by approximately 9.4% at 1 MeV and 9.8% at 11 MeV.

A LN2-based cooling system for a next-generation liquid xenon dark matter detector

In recent years, cooling technology for liquid xenon(LXe) detectors has advanced driven by the development of dark matter(DM) detectors with target mass in the 100–1000 kg range. The next generation of DM detectors based on LXe will be in the 50,000 kg(50 t)range requiring more than 1 k W of cooling power. Most of the prior cooling methods become impractical at this level.For cooling a 50 t scale LXe detector, a method is proposed in which liquid nitrogen(LN2) in a small local reservoir cools the xenon gas via a cold finger. The cold finger incorporates a heating unit to provide temperature regulation. The proposed cooling method is simple, reliable, and suitable for the required long-term operation for a rare event search. The device can be easily integrated into present cooling systems, for example the ‘‘Cooling Bus’ ’employed for the Panda X I and II experiments. It is still possible to cool indirectly with no part of the cooling or temperature control system getting in direct contact with the clean xenon in the detector. Also, the cooling device can be mounted at a large distance, i.e., the detector is cooled remotely from a distance of 5–10 m. The method was tested in a laboratory setup at Columbia University to carry out different measurements with a small LXe detector and behaved exactly as predicted.

Unambiguously Resolving the Potential Neutrino Magnetic Moment Signal at Large Liquid Scintillator Detectors

Non-vanishing electromagnetic properties of neutrinos have been predicted by many theories beyond the Standard Model, and an enhanced neutrino magnetic moment can have profound implications for fundamental physics. The XENON1T experiment recently detected an excess of electron recoil events in the 1–7 keV energy range, which can be compatible with solar neutrino magnetic moment interaction at a most probable value of μ_(v) = 2.1 × 10^(-11)μ_(B).However, tritium backgrounds or solar axion interaction in this energy window are equally plausible causes.Upcoming multi-tonne noble liquid detectors will test these scenarios more in depth, but will continue to face similar ambiguity. We report a unique capability of future large liquid scintillator detectors to help resolve the potential neutrino magnetic moment scenario. With O(100) kton·year exposure of liquid scintillator to solar neutrinos, a sensitivity of μ_(v) < 10^(-11)μ_(B) can be reached at an energy threshold greater than 40 keV, where no tritium or solar axion events but only neutrino magnetic moment signal is still present.

Discrimination of pp solar neutrinos and^(14)C double pile-up events in a large-scale LS detector

As a unique probe,the precision measurement of pp solar neutrinos is important for studying the sun’s energy mechanism as it enables monitoring the thermodynamic equilibrium and studying neutrino oscillations in the vacuum-dominated region.For a large-scale liquid scintillator detector,a bottleneck for pp solar neutrino detection is the pile-up events of intrinsic14C decay.This paper presents a few approaches to discriminating between pp solar neutrinos and ^(14)C pile-up events by considering the differences in their time and spatial distributions.In this study,a Geant4-based Monte Carlo simulation is conducted.Multivariate analysis and deep learning technology are adopted to investigate the capability of ^(14)C pile-up reduction.The BDTG (boosted decision trees with gradient boosting) model and VGG network demonstrate good performance in discriminating pp solar neutrinos and ^(14)C double pile-up events.Under the ^(14)C concentration assumption of 5×10-18g/g,the signal significance can achieve 10.3 and 15.6 using the statistics of only one day.In this case,the signal efficiency for discrimination using the BDTG model while rejecting 99.18% ^(14)C double pile-up events is 51.1%,and that for the case where the VGG network is used while rejecting 99.81%of the ^(14)C double pile-up events is 42.7%.

The Method on Deducing Multiplicity Measurement Equations of Neutron/γ

Based on some important domestic and international references,the third γ multiplicity measurement equation is derived,but it is different from the results given in current researches.The neutron multiplicity equation is deduced in this paper,especially the fourth fast-neutron multiplicity equation based on the liquid scintillation detectors,which is more complex than the other multiplicity equations up to the fourth order.The equations given in this paper can be used to verify the validity and availability of principles for the multiplicity measurement up to the fourth order,and extend the application scopes of the neutron multiplicity measurement,such as correcting the additional measurement value to eliminate influences for dead times.It will be the foundation of nuclear researches,if the higher order multiplicity measurement is important for nuclear materials’control and accountability.

JUNO sensitivity on proton decay p→νK^(+)searches

The Jiangmen Underground Neutrino Observatory(JUNO)is a large liquid scintillator detector designed to explore many topics in fundamental physics.In this study,the potential of searching for proton decay in the p→νK^(+)mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification.Moreover,the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals.Based on these advantages,the detection efficiency for the proton decay via p→νK^(+)is 36.9%±4.9%with a background level of 0.2±0.05(syst)±0.2(stat)events after 10 years of data collection.The estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 years,which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies.