The study of intelligent algorithm in particle identification of heavy-ion collisions at low and intermediate energies

Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the dilemma of traditional particle identification methods.This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies.Multiple intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 simulation.Tree-based machine learning algorithms and deep learning algorithms e.g.TabNet show excellent performance and generalization ability.Adding additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is nonuniform.Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.

Particle identification using artificial neural networks at BESⅢ

A multilayered perceptrons＇ neural network technique has been applied in the particle identification at BESIII. The networks are trained in each sub-detector level. The NN output of sub-detectors can be sent to a sequential network or be constructed as PDFs for a likelihood. Good muon-ID, electron-ID and hadron-ID are obtained from the networks by using the simulated Monte Carlo samples.

Two annular CsI(Tl) detector arrays for the charged particle telescopes

In this study,we constructed two annular detector arrays comprising 24 wedge-shaped CsI(Tl) crystals,and tested them using anαsource and radioactive beams of ^(14-16) Con a CD_2 target.We compared the properties of a CsI(Tl) crystal encapsulated with various reflectors,revealing that using the 80-μm-thick ESR film to pack the CsI(Tl) crystal yielded the largest light output with the smallest non-uniformity in light output (ΔLO).For the 24 CsI(Tl) detectors with the 80-μm-thick ESR films,the average energy resolution improved as the average light output increased;however,it deteriorated as theΔLO value increased.To form two annular Si-CsI(Tl) telescopes for identifying the light-charged particles,theΔLO value and energy resolution of each CsI(Tl) detector were maintained under 20%and 7.7%,respectively.These telescopes were tested for the first time in a direct nuclear reaction experiment using ^(14-16) C+d.The results demonstrated that the Z=1 and Z=2 charged particles were adequately discriminated by the telescopes using the standardΔE-E method.

A new method of charged particle identification based on frequency spectrum analysis

A new frequency domain method for charged particle identification, called Frequency Ratio Analysis（FRA）, is proposed by analyzing the frequency spectra of proton pulses and alpha pulses acquired from a totally depleted Si detector. Identification performance of the FRA method is evaluated and compared with two time domain methods, the current pulse amplitude method and the second moment method. The results show that the FRA method is not only feasible and effective but also superior to the two time domain methods, as it achieves an obvious increase in value of the figure-of-merit（FOM）.

Toward real-time digital pulse process algorithms for CsI(Tl)detector array at external target facility in HIRFL-CSR

A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To process the CsI(Tl) signals generated by γ-rays and light-charged ions, a scheme for digital pulse processing algorithms is proposed. Every step in the algorithms was benchmarked using standard γ and α sources. The scheme, which included a moving average filter, baseline restoration, leading-edge discrimination, moving window deconvolution, and digital charge comparison, was subsequently implemented on the FPGA. A good energy resolution of 5.7% for 1.33-MeV γ-rays and excellent α-γ identification using the digital charge comparison method were achieved, which satisfies CsI(Tl) array performance requirements.

CsI-bowl:an ancillary detector for exit channel selection inγ-ray spectroscopy experiments

A particle detector array designed for light-charged particles, known as the CsI-bowl, was built for exit channel selection for in-beam γ-ray spectroscopy experiments. This device is composed of 64 CsI(Tl) detectors, organized in a structure reminiscent of a tea-bowl. High quantum efficiency photodiodes, characterized by their minimal mass, were employed to collect scintillation light. Its design, construction, particle identification resolution, and its effectiveness in relation to exit channel selection are described in this paper. In source tests, the optimal figure of merit for the identification of α-particles and γ-rays using the charge comparison method was found to be 3.3 and 12.1 for CsI detectors coupled to photodiodes and avalanche photodiodes, respectively. The CsI-bowl demonstrated effectiveness in identifying particles, specifically the emission of protons and α-particles in the58Ni(19F, xpyn) fusion–evaporation reaction, thereby enabling the selection of the desired exit channels.

Identification of deuterons at BESIII

The identification of deuterons with momenta in the range of 0.52−0.72 GeV/c is studied with specific ionization energy loss information using a data sample collected by the BESIII detector at center-of-mass energies between 4.009 and 4.946 GeV.Clean deuteron samples are selected using time of flight information.For all data samples,the deuteron identification efficiencies are higher than 95%,with a maximum difference of%between data and Monte Carlo simulation.This verifies the effectiveness of the deuteron identification method based on specific ionization energy loss and provides valuable information for future studies on processes involving deuterons in the final state at BESIII.

RESEARCH ON THE ALGORITHM OF BINARY IMAGE CROSS-CORRELATION FOR UNSTEADY FLOW FIELD MEASUREMENT

The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an effective algorithm for particle identification from consecutive images, the accurate velocity vector field can be obtained. The real velocity field in a valve chamber was measured by BICC in this study. From the full-field velocity information, the pressure and vorticity fields were also extracted by post-processing. (Edited author abstract) 6 Refs.

Calibration and performance of the neutron detector onboard of the DAMPE mission

The DArk Matter Particle Explorer(DAMPE),one of the four space-based scientific missions within the framework of the Strategic Pioneer Program on Space Science of the Chinese Academy of Sciences,was successfully launched on 2015 Dec.17 from Jiuquan launch center.One of the most important scientific goals of DAMPE is to search for evidence of dark matter indirectly by measuring the spectrum of high energy cosmic-ray electrons.The neutron detector,one of the four sub-payloads of DAMPE,is designed to distinguish high energy electrons from hadron background by measuring the secondary neutrons produced in the shower.In this paper,a comprehensive introduction of the neutron detector is presented,including the design,calibration and performance.The analysis with simulated data and flight data indicates a powerful proton rejection capability of the neutron detector,which plays an essential role for TeV electron identification of DAMPE.

Wear Fault Diagnosis of Machinery Based on Neural Networks and Gray Relationships

In this paper, the regular characteristic of -wear particles related to fault type of machines based on condition monitoring of reciprocal machinery is discussed. The typical -wear particles spectrum is established according to the equipment structure , friction and wear rule and the characteristic of 'wear particles; The identification technology of wear particles is proposed based on neural networks and a gray relationship ; an intelligent wear particles identification system is designed. The diagnosis example shows that this system can promote the accuracy and the speed of wear particles identification.

Evaluation of particle acceptance for space particle telescope

The particle acceptance instead of the G-factors has been introduced for a particle telescope. The particle acceptance of a telescope module TEST is simulated by using the GEANT4 Monte-Carlo package. The results are presented and explained.

Monte Carlo study on the low momentum μ-π identification of the BESⅢ EM calorimeter

Abstract The BESⅢ detector has a high-resolution electromagnetic calorimeter which can be used for low momentum μ-π identification. Based on Monte Carlo simulations, μ-π separation was studied. A multilayer perceptron neural network making use of the defined variables was used to do the identification and a good μ-π separation result was obtained.

Application of the HKS in the identification of kaons produced in the reaction(e,e'K^+)

At Jefferson Laboratory the experiment E02-017 was carried out to investigate the fission associated with kaons in the hypernuclei-producing interaction p（e,K^＋e＇）A. The newly installed high resolution kaon spectrometer （HKS） in Hall C was used as a key instrument to identify kaons. This paper introduces the HKS hardware and describes the way the kaons are identified. Maintaining most of the kaons （nearly 100%） in the data, HKS identifies kaons with a purity of -67% in this experiment. The resolution of the kaon target time reconstructed by HKS reaches 0.42 ns.

An artificial neural network for proton identification in HERMES data

The HERMES time-of-flight （TOF） system is used for proton identification, but must be carefully calibrated for systematic biases in the equipment. This paper presents an artificial neural network （ANN） trained to recognize protons from ∧^0 decay using only raw event data such as time delay, momentum, and trajectory. To avoid the systematic errors associated with Monte Carlo models, we collect a sample of raw experimental data from the year 2000. We presume that when for a positive hadron （assigned one proton mass） and a negative hadron （assigned one π^- mass） the reconstructed invariant mass lies within the ∧^0 resonance, the positive hadron is more likely to be a proton. Such events are assigned an output value of one during the training process; all others were assigned the output value zero. The trained ANN is capable of identifying protons in independent experimental data, with an efficiency equivalent to the traditional TOF calibration. By modifying the threshold for proton identification, a researcher can trade off between selection efficiency and background rejection power. This simple and convenient method is applicable to similar detection problems in other experiments.

Landmarks in the application of electrical tomography in particle science and technology

Selected milestones in the development and use of electrical tomography in powder conveying, slurry processing and multi-phase flow are highlighted. The ability to map concentration in opaque mixtures under process-realistic conditions was a major innovation for the method and has had far reaching implications. Subsequent developments have enabled velocity information to be abstracted resulting in the ability to measure component flux and motion.

Applying Bayesian neural networks to identify pion,kaon and proton in BESⅡ

The Monte-Carlo samples of pion, kaon and proton generated from 0.3 GeV/c to 1.2 GeV/c by the ‘tester＇ generator from SIMBES which are used to simulate the detector of BES Ⅱ are identified with the Bayesian neural networks （BNN）. The pion identification and misidentification efficiencies are obviously better at high momentum region using BNN than the methods of χ^2 analysis of dE/dX and TOF information. The kaon identification and misidentification efficiencies are obviously better from 0.3 GeV/c to 1.2 GeV/c using BNN than the methods of X2 analysis. The proton identification and misidentification efficiencies using BNN are basically consistent with the ones of χ^2 analysis. The anti-proton identification and misidentification efficiencies are better below 0.6 GeV/c using BNN than the methods of χ^2 analysis.

A multilayer△E-ER telescope for breakup reactions at energies around the Coulomb barrier

The breakup reactions of weakly-bound nuclei at energies around the Coulomb barrier and the cor- responding coupling effect on the other reaction channels are hot topics nowadays. To overcome the difficulty in identifying both heavier and lighter fragments simultaneously, a new kind of ionization-chamber based detector tele- scope has been designed and manufactured. It consists of a PCB ionization chamber and three different thickness silicon detectors installed inside the chamber, which form a multilayer △E-ER telescope. The working conditions were surveyed by using an a source. An in-beam test experiment shows that the detector has good particle identifi- cation for heavy particles like 17F and 160 as well as light particles like protons and alpha particles. The measured quasi-elastic scattering angular distribution and the related discussions for 17F＋208pb are presented.

Studies of dE/dx measurements with the BESⅢ

The Beijing Spectrometer Ⅲ（BESⅢ）is a general-purpose detector used for the study of τ-charm physics at the Beijing Electron-Positron Collider Ⅱ（BEPC Ⅱ）.This paper presents our studies of the dE/dx measurement in the drift chamber of BESⅢ,which is important for the identification of charged particles.Corrections applied to the dE/dx measurement in data reconstruction are discussed.After our current dE/dx calibration,a resolution of about 6% has been obtained for minimum ionization particles,and a 3σ K/πseparation is obtained for momenta up to 760 MeV/c.These results meet the design goals of the BESⅢ drift chamber.

Study of MRPC technology for BESIII endcap-TOF upgrade

Purpose In order to improve the charged particle identi-fication capability,end-cap time-of-flight(ETOF)detector of the Beijing Spectrometer(BESIII)has been upgraded with multi-gap resistive plate chamber(MRPC)technology,aiming at an overall time resolution of 80 ps for minimum-ionization particles to extend the K/πseparation(2σ)momentum range to 1.4 GeV/c.Methods The previous version of ETOF in BESIII consisted of plastic scintillators.The multi-hit events distort both shape and amplitude of the output signals.MRPC technique was chosen for the BESIII ETOF upgrade as it provides high time resolution and high detection efficiency,is of relatively low cost and is insensitive to neutral particles.Most importantly,the fine segmentation of the MRPC readout stripes can suppress multi-hit events effectively.Results The final design of MRPC module for ETOF is characterized by double-stack(2×6)structure,dual-end readout mode and precision electronics.To batch-produce and test these MRPC modules,a series of tools and production procedures as well as related performance simulation and test methods were developed.Results showed that each MRPC module’s intrinsic time resolution(including the electronics contribution)is around 50 ps and the efficiency is better than 97%.The overall performance of the upgraded ETOF is better than the designed index.The new ETOF has been successfully installed at BESIII and run in 2016.

Design and performance study of the LEPD silicon tracker onboard the CSES satellite

The low energy particle detector （LEPD） is one of the main payloads onboard the China seismic electromagnetic satellite （CSES）. The detector is designed to ascertain space electrons （0.1–10 MeV） and protons （2–50 MeV）. It has the capability of identifying the electrons and protons, to measure the energy spectrum and the incident angle of the particles. The LEPD is made up of a silicon tracker system, a CsI （Tl） mini-calorimeter, an anti-coincidence system made by plastic scintillator, as well as electronics and a data acquisition system （DAQ）. The tracker is also a kind of E-E telescope; it consists of two layers of double-sided silicon strip detectors （DSSD）. The signals emerging from the silicon tracker can be read out by two pieces of application specific integrated circuit （ASIC）, which also can generate an event trigger for the LEPD. The functions of the DSSD system in the LEPD for charged particles were tested by 241Am @5.486 MeV α particles. The results show that the DSSD system works well, and has high performance to detect charged particles and measure the position of incident particles.