The Complex of Experimental Facilities for the Cosmic Ray Investigation at the Tien Shan Mountain Station

The study describes the experimental complex of the station located in the Tien Shan mountains at an elevation of 3340 m above sea level. The complex consists of detectors of different types scattered across the station area, such as scintillation particles detectors, Cherenkov detectors, radio emission detectors for the measurement of the electron component of extensive air showers (EAS) created by the (1–1000) PeV cosmic ray particles, an ionization calorimeter and neutron detectors for the study of the nuclear-active component of EAS cores, and the underground particle detectors for the detection of cosmic ray muons. The data acquisition system allows the simultaneous recording of parameters from various stand-alone detectors registering an EAS, and storage of the acquired data in the database. As an illustration of research capability, the results of the EAS study are presented here which were obtained during the last few years at the different experimental set-ups constituting the Tien Shan complex.

Chapter 1 LHAASO Instruments and Detector technology

The Large High Altitude Air Shower Observatory ( LHAASO ) ( Fig. 1 ) is located at Mt. Haizi (4410 m a.s.l., 600 g/cm2, 29◦ 21’ 27.56” N, 100◦ 08’ 19.66” E) in Daocheng, Sichuan province, P.R. China. LHAASO consists of 1.3 km2 array ( KM2A ) of electromagnetic particle detectors ( ED ) and muon detectors ( MD ), a water Cherenkov detector array ( WCDA ) with a total active area of 78,000 m2, 18 wide field-of-view air Cherenkov telescopes (WFCTA ) and a newly proposed electron-neutron detector array ( ENDA ) covering 10,000 m2. Each detector is synchronized with all the other through a clock synchronization network based on the White Rabbit protocol. The observatory includes an IT center which comprises the data acquisition system and trigger system, the data analysis facility. In the following of this Chapter, all the above mentioned components of LHAASO will be briefly described, together with infrastructure which is a fundamental component of the LHAASO observatory.

Direct comparison of PEN and TPB wavelength shifters in a liquid argon detector

A large number of particle detectors employ liquid argon as their target material owing to its high scintillation yield and its ability to drift ionization charge over large distances. Scintillation light from argon is peaked at 128 nm and a wavelength shifter is required for its efficient detection. In this work, we directly compare the light yield achieved in two identical liquid argon chambers, one of which is equipped with polyethylene naphthalate (PEN) and the other with tetraphenyl butadiene (TPB) wavelength shifter. Both chambers are lined with enhanced specular reflectors and instrumented with SiPMs with a coverage fraction of approximately 1%, which represents a geometry comparable to the future large scale detectors. We measured the light yield of the PEN chamber to be 39.4$$\,\pm \,$$ ± 0.4(stat)$$\,\pm \,$$ ± 1.9(syst)% of the yield of the TPB chamber. Using a Monte Carlo simulation this result is used to extract the wavelength shifting efficiency of PEN relative to TPB equal to 47.2$$\,\pm \,$$ ± 5.7%. This result paves the way for the use of easily available PEN foils as a wavelength shifter, which can substantially simplify the construction of future liquid argon detectors.

Scintillation light increase of carbontetrafluoride gas at low temperature

Scintillation detector is widely used for the particle detection in the field of particle physics. Particle detectors containing fluorine-19 (19F) are known to have advantages for Weakly Interacting Massive Particles (WIMPs) dark matter search, especially for spin-dependent interactions with WIMPs due to its spin structure. In this study, the scintillation properties of carbontetrafluoride (CF4) gas at low temperature were evaluated because its temperature dependence of light yield has not been measured. We evaluated the light yield by cooling the gas from room temperature (300 K) to 263 K. As a result, the light yield of CF4 was found to increase by (41.0 ± 4.0stat. ± 6.6syst.)% and the energy resolution was also found to improve at low temperature.

Fluorescence of pyrene-doped polystyrene films from room temperature down to 4 K for wavelength-shifting applications

In liquid argon-based particle detectors, slow wavelength shifters (WLSs) could be used alongside the common, nanosecond scale, WLS tetraphenyl butadiene (TPB) for background mitigation purposes. At room temperature, pyrene has a moderate fluorescence light yield (LY) and a time constant of the order of hundreds of nanoseconds. In this work, four pyrene-doped polystyrene films with various purities and concentrations were characterized in terms of LY and decay time constants in a range of temperature between 4 K and 300 K under ultraviolet excitation. These films were found to have a LY between 35 and 50% of that of evaporated TPB. All light yields increase when cooling down, while the decays slow down. At room temperature, we observed that pyrene purity is strongly correlated with emission lifetime: highest obtainable purity samples were dominated by decays with emission time constants of ∼ 250–280 ns, and lower purity samples were dominated by an ∼ 80 ns component. One sample was investigated further to better understand the monomer and excimer emissions of pyrene. The excimer-over-monomer intensity ratio decreases when the temperature goes down, with the monomer emission dominating below ∼ 87 K.

Demonstrating a single-block 3D-segmented plastic-scintillator detector

Three-dimensional finely grained plastic scintillator detectors bring many advantages in particle detectors, allowing a massive active target which enables a high-precision tracking of interaction products, excellent calorimetry and a sub-nanosecond time resolution. Whilst such detectors can be scaled up to several-tonnes, as required by future neutrino experiments, a relatively long production time, where each single plastic-scintillator element is independently manufactured and machined, together with potential challenges in the assembly, complicates their realisation. In this manuscript we propose a novel design for 3D granular scintillator detectors where O(1 cm3) cubes are efficiently glued in a single block of scintillator after being produced via cast polymerization, which can enable rapid and cost-efficient detector construction. This work could become particularly relevant for the detectors of the next-generation long-baseline neutrino-oscillation experiments, such as DUNE, Hyper-Kamiokande and ESSnuSB.

How to Use Machine Learning to Improve the Discrimination between Signal and Background at Particle Colliders

The popularity of Machine Learning (ML) has been increasing in recent decades in almost every area, with the commercial and scientific fields being the most notorious ones. In particle physics, ML has been proven a useful resource to make the most of projects such as the Large Hadron Collider (LHC). The main advantage provided by ML is a reduction in the time and effort required for the measurements carried out by experiments, and improvements in the performance. With this work we aim to encourage scientists working with particle colliders to use ML and to try the different alternatives that are available, focusing on the separation of signal and background. We assess some of the most-used libraries in the field, such as Toolkit for Multivariate Data Analysis with ROOT, and also newer and more sophisticated options such as PyTorch and Keras. We also assess the suitability of some of the most common algorithms for signal-background discrimination, such as Boosted Decision Trees, and propose the use of others, namely Neural Networks. We compare the overall performance of different algorithms and libraries in simulated LHC data and produce some guidelines to help analysts deal with different situations. Examples include the use of low or high-level features from particle detectors or the amount of statistics that are available for training the algorithms. Our main conclusion is that the algorithms and libraries used more frequently at LHC collaborations might not always be those that provide the best results for the classification of signal candidates, and fully connected Neural Networks trained with Keras can improve the performance scores in most of the cases we formulate.

Charge sharing investigation in a Timepix3 (TPX3) detector through ion probing

The phenomenon of charge sharing in pixelated particle detectors and its relationship to a variety of physical parameters is investigated using a Timepix3 (TPX3) detector with a 500 μm thick silicon sensor. A probing technique is used with H, Li, and C ion beams produced at the Tandem Van de Graaff (VdG) accelerator at the University of Montreal (UdeM), as well as alpha particles from an 241Am radioactive source, to determine a direct relationship between particle depth and cluster size. Additionally, the primacy of a particle's energy on the determination of its corresponding cluster's size is confirmed.