Detector Simulation Research Articles

BGO quenching effect on spectral measurements of cosmic-ray nuclei in DAMPE experiment

The Dark Matter Particle Explorer (DAMPE) is a satellite-borne detector designed to measure high energy cosmic-rays and γ-rays. As a key sub-detector of DAMPE, the Bismuth Germanium Oxide (BGO) imaging calorimeter is utilized to measure the particle energy with a high resolution. The nonlinear fluorescence response of BGO for large ionization energy deposition, known as the quenching effect, results in an under-estimate of the energy measurement for cosmic-ray nuclei. In this paper, various models are employed to characterize the BGO quenching factors obtained from the experimental data of DAMPE. Applying the proper quenching model in the detector simulation process, we investigate the tuned energy responses for various nuclei and compare the results based on two different simulation softwares, i.e. GEANT4 and FLUKA. The BGO quenching effect results in a decrease of the measured energy by approximately 2.5% (5.7%) for carbon (iron) at ∼10 GeV/n and <1% above 1 TeV/n, respectively. Accordingly, the correction of the BGO quenching effect leads to an increase of the low-energy flux measurement of cosmic-ray nuclei.

Recent developments in data reconstruction for aerogel RICH at Belle II

In the forward end-cap of the Belle II spectrometer, particle identification is provided by a proximity focusing RICH detector with an aerogel radiator (ARICH). The ARICH’s primary function is to effectively distinguish between pions and kaons in the momentum range of 0.5GeV/c to about 4GeV/c, as well as to contribute to identification of low-momentum leptons. Since its operation began, Belle II has collected over 420fb−1 of data. Based on this large data sample, studies of several effects that impact the performance of the ARICH detector were carried out. In this paper, we present a comparison of the observed Cherenkov ring image and detector particle identification performance in the measured data and detector simulation. Furthermore, we highlight recent efforts aimed at enhancing the ARICH’s performance by taking into account the effects of particle decay in flight and scattering in materials before the detector, as well as by refining the probability density function used for particle identification likelihood evaluation.

Optical systems for future Ring Imaging Cherenkov detectors

Optical systems for Ring Imaging Cherenkov (RICH) detectors have historically taken a variety of designs. Nowadays, technological developments allow more flexibility in the design and construction than was possible in the past, such as lightweight secondary mirrors that can be placed in the acceptance of an experiment, widespread use of non-spherical optical surfaces, flexible and fast tools for parametric optimisation of the optical systems before feeding into a full detector simulation. Within this context, the design of the LHCb RICH optical system for the current Run-3 data-taking of the LHC will be presented and compared to the parametric design of the proposed optics for the Upgrade II for the future HL-LHC phase.

A Study on the Quantitative Fire Performance Evaluation Method of Building Finishing Materials with a Focus on Medical Facilities

Buildings in modern society tend to gradually expand in size due to technological development and overcrowding, which increases the risk of fire. Therefore, continuous efforts are being made to ensure the evacuation safety of occupants by installing firefighting facilities and using flame retardant building finishing materials. This study aims to present a fire performance evaluation plan for building finishing materials using simulations and identify risks that arise from not using flame retardant building finishing materials in medical facilities with vulnerable occupants. A control group for fire performance evaluation was selected using polyurethane foam, while two types of cellulose-based building finishing materials with different flame retardants were chosen for analysis. The cellulose-based finishing materials included expanded graphite, magnesium hydroxide, montmorillonite, and ammonium polyphosphate. Fire performance was evaluated using FDS and path detector simulations based on NES 713 and ISO 5660-1. The results of the study showed that there was a difference of three people in the prediction of the number of deaths depending on the scope of analysis, and it was confirmed that the toxic gas detected was different depending on the added flame retardant. Additionally, construction finishing materials with flame retardant performance increased ASET by at least 130 s compared to polyurethane foam, and the evacuation safety exceeded 1, confirming the effectiveness of securing evacuation stability for occupants.

Inclusion of a GaAs detector model in the Photon Counting Toolkit software for the study of breast imaging systems.

We present an upgraded version of the Photon Counting Toolkit (PcTK), a freely available by request MATLAB tool for the simulation of semiconductor-based photon counting detectors (PCD), which has been extended and validated to account for gallium arsenide (GaAs)-based PCD(s). The modified PcTK version was validated by performing simulations and acquiring experimental data for three different cases. The LAMBDA 60 K module planar detector (X-Spectrum GmbH, Germany) based on the Medipix3 ASIC technology was used in all cases. This detector has a 500-μm thick GaAs sensor and a 256 × 256-pixel array with 55 μm pixel size. The first validation was a comparison between simulated and measured spectra from a 109Cd radionuclide source. In the second validation study, experimental measurements and simulations of mammography spectra were generated to observe the performance of the GaAs version of the PcTK with polychromatic radiation used in conventional x-ray imaging systems. The third validation study used single event analysis to validate the spatio-energetic model of the extended PcTK version. Overall, the software provided a good agreement between simulated and experimental data, validating the accuracy of the GaAs model. The software could be an attractive tool for accurate simulation of breast imaging modalities relying on photon counting detectors and therefore could assist in their characterization and optimization.

Performance of the 1-ton prototype neutrino detector at CJPL-I

China Jinping Underground Laboratory provides an ideal site for solar, geo-, and supernova neutrino studies. With a prototype neutrino detector running since 2017, containing 1-ton liquid scintillator, we tested its experimental hardware, performed the detector calibration and simulation, and measured its radioactive backgrounds, as an early stage of the Jinping Neutrino Experiment (JNE). We investigated the radon background and implemented the nitrogen sealing technology to control it. This paper presents the details of these studies and will serve as a key reference for the construction and optimization of the future large detector of JNE.

Pair production of the vectorlike top partner at the CLIC

New vectorlike T-quarks (VLQ-T) have been predicted in many scenarios of new physics beyond the Standard Model, the current mass exclusion limits from LHC experiments will be relaxed by the presence of additional decay channels. In this work, we investigate the prospect of discovering the pair production of VLQ-T at the future 3 TeV Compact Linear Collider (CLIC), by focusing on the final signals via the standard decay channel T→Wb where one of the W bosons decays leptonically and the other decays hadronically. By performing a rapid detector simulation of the signal and background events as well as considering the initial state radiation and beamstrahlung effects, the exclusion limit at the 95% confidence level and the 5σ discovery prospects are, respectively, obtained on the integrated luminosity and the branching ratio of T→Wb for three typical VLQ-T masses.

Neutrino-tagged jets at the Electron-Ion Collider

We explore the potential of jet observables in charged-current deep-inelastic scattering (CC DIS) events at the future Electron-Ion Collider (EIC). Tagging jets with a recoiling neutrino, which can be identified by the event's missing transverse momentum, will allow for flavor-sensitive measurements of Transverse Momentum Dependent parton distribution functions (TMDs). We present the first predictions for transverse-spin asymmetries in azimuthal neutrino-jet correlations and hadron-in-jet measurements. We study the kinematic reach and the precision of these measurements and explore their feasibility using parameterized detector simulations. We conclude that jet production in CC DIS, while challenging in terms of luminosity requirements, will complement the EIC experimental program to study the three-dimensional structure of the nucleon encoded in TMDs.

Detailed simulation for the ClearMind prototype detection module and event reconstruction using artificial intelligence

The ClearMind project aims to develop the TOF-PET position sensitive detection module optimized for the time resolution, spatial resolution, and detection efficiency. For this, the ClearMind project uses a large (59 × 59 mm2) monolithic PbWO4 (PWO) scintillating crystal with a bialkali photo-electric layer deposited directly on the crystal. Scintillation and Cherenkov photons result together from the 511 keV gamma-ray interaction into the PWO crystal. A micro-channel plate photomultiplier tube (MCP-PMT) encapsulating the PWO crystal amplifies photoelectrons generated at the photocathode, and the corresponding anode signals are collected through the transmission lines read out at both ends and digitized by a SAMPIC module. In this work, we present a realistic Geant4 simulation of the ClearMind prototype detector, including the propagation of the visible photons in the crystal, the modeling of a realistic response of the photocathode and of the PMT, and the propagation of the electrical signals over the transmission lines. The reconstruction of the gamma conversion in the detector volume is performed from the signals registered at both ends of the transmission lines. We compare the reconstruction precision of a statistical algorithm against machine learning algorithms developed using the TMVA package. We expect to reach a spatial resolution down to a few mm3 (FWHM). Finally, we will discuss prospects for the ClearMind detector.

X-ray radiography of HPGe detectors for Monte Carlo simulations

The results of the development of a radiographic installation that allows to control the size of the internal elements of HPGe detectors' cryostats for simulation by Monte Carlo method, are presented. Calibration and assessment of image quality value of the developed radiographic installation were carried out in accordance with ISO Standards 19232–1 and 19232–5. Simulation of the HPGe detector's registration efficiency in the range of 50 keV-3 MeV with the MCC-MT program showed that the discrepancy between the calculated and experimental results when adjusting the detector model using radiological measurement data does not exceed 3% in geometry for point sources and 5% for the Eu-152 source in the Marinelli beaker geometry.

Improvement of the CGEM detector simulation with cosmic-rays

A Cylindrical Gas Electron Multiplier (CGEM) is under construction for the upgrade of the BESIII inner tracker. A preliminary simulation of the CGEM signal before the frond-end electronics has been worked out by making some sampling models from the beforehand Garfield++ simulation. The electronics response functions are implemented making the simulation of CGEM more complete. By comparing the cosmic-ray data acquired by two layers of CGEM and the simulation, the micro-sector effect is simulated and some key parameters in the sampling models are fine tuned in this order: gain, charge sharing, charge fluctuation and electron diffusion. A general agreement is achieved between the cosmic-ray data and the simulation with these improvements.

Deep machine learning for the PANDA software trigger

Deep machine learning methods have been studied for the software trigger of the future PANDA experiment at FAIR, using Monte Carlo simulated data from the GEANT-based detector simulation framework PandaRoot. Ten physics channels that cover the main physics topics, including electromagnetic, exotic, charmonium, open charm, and baryonic reaction channels, have been investigated at four different anti-proton beam momenta. Different classification concepts and network architectures have been studied. Finally a residual convolutional neural network with four residual blocks in a binary classification scheme has been chosen due to its extendability, performance and stability. The presented study represents a feasibility study of a completely software-based trigger system. Compared to a conventional selection method, the deep machine learning approach achieved a significant efficiency gain of up to 200%, while keeping the background reduction factor at the required level of 1/1000. Furthermore, it is shown that the use of additional input variables can improve the data quality for subsequent analysis. This study shows that the PANDA software trigger can benefit greatly from the deep machine learning methods.

Simulation of silicon strip detector for space-based cosmic ray experiments with Allpix$$^{2}$$

Simulation of silicon strip detector for space-based cosmic ray experiments with Allpix$$^{2}$$

A generative adversarial network to speed up optical Monte Carlo simulations

Detailed simulation of optical photon transport and detection in radiation detectors is often used for crystal-based gamma detector optimization. However, the time and memory burden associated with the track-wise approach to particle transport and detection in commonly used Monte Carlo codes makes optical simulation prohibitive at a system level, where hundreds to thousands of scintillators must be modeled. Consequently, current large system simulations do not include detailed detector models to analyze the potential performance gain with new radiation detector technologies. Generative adversarial networks (GANs) are explored as a tool to speed up the optical simulation of crystal-based detectors. These networks learn training datasets made of high-dimensional data distributions. Once trained, the resulting model can produce distributions belonging to the training data probability distribution. In this work, we present the proof of concept of using a GAN to enable high-fidelity optical simulations of nuclear medicine systems, mitigating their computational complexity. The architecture of the first network version and high-fidelity training dataset is discussed. The latter is generated through accurate optical simulation with GATE/Geant4, and contains the position, direction, and energy distributions of the optical photons emitted by 511 keV gamma rays in bismuth germanate and detected on the photodetector face. We compare the GAN and simulation-generated distributions in terms of similarity using the Jensen–Shannon distance. Excellent agreement was found with similarity values higher than 93.5% for all distributions. Moreover, the GAN speeded the optical photon distribution generation by up to two orders of magnitude. These very promising results have the potential to drastically change the use of nuclear imaging system optical simulations by enabling high-fidelity system-level simulations in reasonable computation times. The ultimate is to integrate the GAN within GATE/Geant4 since numerous applications (large detectors, bright scintillators, Cerenkov-based timing positron emission tomography) can benefit from these improvements.

Single vector-like quark X production in the tW channel at high energy pp colliders

Vector-like quarks (VLQs) are color-triplet spin-1/2 fermions whose left- and right-handed chiral components have the same transformation properties under the weak-isospin SU(2) gauge group. The X vector-like particle with a charge of |Q|=+5/3 exists in the (X,T) doublet or (X,T,B) triplet states. Based on a simplified model, we investigate the prospect of discovering the doublet right-handed X via the single production of X followed by X→tW at the 14 TeV High Luminosity LHC (HL-LHC), 27 TeV High Energy LHC (HE-LHC), and 100 TeV hadron-hadron Future Circular Hadron Collider (FCC-hh). We perform a detailed detector simulation, and find that the excluding and discovering capabilities on the X quark are enhanced obviously with the increase of collision energy. Assuming the system uncertainty is 30% of the number of the background events, the excluding capabilities are given as follows: (1) the HL-LHC can exclude the correlated regions of the mixing constant sin⁡θR∈[0.082,0.2] and the X quark mass mX ∈ [1000 GeV, 1680 GeV] with L=3 ab−1; (2) the HE-LHC can exclude the correlated regions of sin⁡θR∈[0.067,0.2] and mX ∈ [1000 GeV, 2230 GeV] with L=15 ab−1; (3) the FCC-hh can exclude the correlated regions of sin⁡θR∈[0.078,0.2] and mX ∈ [1000 GeV, 2560 GeV] with L=30 ab−1.

GEANT4 simulation and spectrum restoration of a pixelated X-ray detector

We perform a detailed simulation of a pixelated CdTe detector using the GEANT4 toolkit completed with a custom code emulating the detector's electronic response. We demonstrate that a measured tungsten X-ray spectrum can be majorly restored back to the original incident spectrum using the developed model, without requiring the dedicated hardware charge sharing correction.

A hybrid 3D/2D field response calculation for liquid argon detectors with PCB based anode plane

Liquid Argon Time Projection Chamber (LArTPC) technology is commonly utilized in neutrino detector designs. It enables detailed reconstruction of neutrino events with high spatial precision and low energy threshold. Its field response (FR) model describes the time-dependent electric currents induced in the anode-plane electrodes when ionization electrons drift nearby. An accurate and precise FR is a crucial input to LArTPC detector simulations and charge reconstruction. Established LArTPC designs have been based on parallel wire planes. It allows accurate and computationally economic two-dimensional (2D) FR models utilizing the translational symmetry along the direction of the wires. Recently, novel LArTPC designs utilize electrodes formed on printed circuit board (PCB) in the shape of strips with through holes. The translational symmetry is no longer a good approximation near the electrodes and a new FR calculation that employs regions with three dimensions (3D) has been developed. Extending the 2D models to 3D would be computationally expensive. Fortuitously, the nature of strips with through holes allows for a computationally economic approach based on the finite-difference method (FDM). In this paper, we present a new software package pochoir that calculates LArTPC field response for these new strip-based anode designs. This package combines 3D calculations in the volume near the electrodes with 2D far-field solutions to achieve fast and precise field response computation. We apply the resulting FR to simulate and reconstruct samples of cosmic-ray muons and 39Ar decays from a Vertical Drift (VD) detector prototype operated at CERN. We find the difference between real and simulated data within 5%. Current state-of-the-art LArTPC software requires a 2D FR which we provide by averaging over one dimension and estimate that variations lost in this average are smaller than 7%.

A comparative study of Z′ mediated charged lepton flavor violation at future lepton colliders

Charged lepton flavor violation (CLFV) represents a transition between charged leptons of different generations that violates lepton flavor conservation, which is a clear signature of possible new physics beyond the standard model. By exploiting a typical example model of extra Z′ gauge boson, we perform a detailed comparative study on CLFV searches at several future lepton colliders, including a 240 GeV electron-positron collider and a TeV scale muon collider. Based on detailed signal and background Monte-Carlo studies with fast detector simulations, we derive the potentials in searching for Z′ mediated CLFV couplings with eμ, eτ and μτ of different future colliders. The results are compared with the current and prospect limits set by either low-energy experiments or the high-energy LHC experiments. The sensitivity of the τ related CLFV coupling strength at future lepton colliders will be significantly improved in comparison to the current best constraints and the prospect constraints for the μτ channel.

Is the machine smarter than the theorist: Deriving formulas for particle kinematics with symbolic regression

We demonstrate the use of symbolic regression in deriving analytical formulas, which are needed at various stages of a typical experimental analysis in collider phenomenology. As a first application, we consider kinematic variables like the stransverse mass, $M_{T2}$, which are defined algorithmically through an optimization procedure and not in terms of an analytical formula. We then train a symbolic regression and obtain the correct analytical expressions for all known special cases of $M_{T2}$ in the literature. As a second application, we reproduce the correct analytical expression for a next-to-leading order (NLO) kinematic distribution from data, which is simulated with a NLO event generator. Finally, we derive analytical approximations for the NLO kinematic distributions after detector simulation, for which no known analytical formulas currently exist.

Virtual monochromatic imaging with projection-based material decomposition algorithm for metal artifacts reduction in photon-counting detector computed tomography.

Metal artifacts present a major challenge to computed tomography (CT) because they reduce the image quality in medical diagnosis and treatment. Several metal artifact reduction (MAR) methods have been proposed to address this issue in previous studies. This study aimed to synthesize a virtual monochromatic image for MAR in CT images using projection-based material decomposition (MD) algorithms. We developed a spectral micro-CT prototype system equipped with a photon-counting detector (PCD) and PCD-CT imaging simulator to assess the performances of different MAR methods. Two projection-based MD algorithms were implemented and evaluated for their MAR performances in CT images and compared with conventional sinogram inpainting MAR methods. Different parts of digital 4D-extended cardiac torso (XCAT) phantoms with metal implants were designed to simulate various real scenarios. A homemade metal artifact evaluation (MAE) phantom was used to evaluate the MAR performance in experiments. The simulated results of the XCAT phantom indicated that the projection-based virtual monochromatic CT (VMCT) images provided better image quality than the conventional MAR images without blurring the normal tissues at the position of the metal artifacts. Various quantitative indicators support this conclusion. Additionally, the experimental results of the MAE phantom reveal that projection-based VMCT images can avoid image distortion caused by metal artifacts, unlike conventional MAR methods. In regards to the projection-based VMCT images, the simulated and experimental results demonstrated that using the linear maximum likelihood estimators with an error correction look-up table algorithm yielded better MAR performance compared to that obtained using a polynomial algorithm. Furthermore, projection-based VMCT images can not only reduce metal artifacts effectively but also simultaneously prevents object blurring at the metal artifact position and image distortion of the metal implants. Hence, the CT image quality can be further improved to increase the abilities for both preoperative and postoperative assessment of metal implants.