Detector Response Research Articles

Autoencoder-Based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter

The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.

DRiFT current mode, trigger settings and flexible detector specifications applied to scintillator arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

A data-driven [formula omitted] simulation with normalizing flow

In high-energy physics, precise measurements rely on highly reliable detector simulations. Traditionally, these simulations involve incorporating experiment data to model detector responses and fine-tuning them. However, due to the complexity of the experiment data, tuning the simulation can be challenging. One crucial aspect for charged particle identification is the measurement of energy deposition per unit length (referred to as dE/dx). This paper proposes a data-driven dE/dx simulation method using the Normalizing Flow technique, which can learn the dE/dx distribution directly from experiment data. By employing this method, not only can the need for manual tuning of the dE/dx simulation be eliminated, but also high-precision simulation can be achieved.

Assessment of fluence- and dose-averaged linear energy transfer with passive luminescence detectors in clinical proton beams

Objective. This work investigates the use of passive luminescence detectors to determine different types of averaged linear energy transfer ( LET― ) for the energies relevant to proton therapy. The experimental results are compared to reference values obtained from Monte Carlo simulations. Approach. Optically stimulated luminescence detectors (OSLDs), fluorescent nuclear track detectors (FNTDs), and two different groups of thermoluminescence detectors (TLDs) were irradiated at four different radiation qualities. For each irradiation, the fluence- ( LET―f ) and dose-averaged LET ( LET―d ) were determined. For both quantities, two sub-types of averages were calculated, either considering the contributions from primary and secondary protons or from all protons and heavier, charged particles. Both simulated and experimental data were used in combination with a phenomenological model to estimate the relative biological effectiveness (RBE). Main results. All types of LET― could be assessed with the luminescence detectors. The experimental determination of LET―f is in agreement with reference data obtained from simulations across all measurement techniques and types of averaging. On the other hand, LET―d can present challenges as a radiation quality metric to describe the detector response in mixed particle fields. However, excluding secondaries heavier than protons from the LET―d calculation, as their contribution to the luminescence is suppressed by ionization quenching, leads to equal accuracy between LET―f and LET―d . Assessment of RBE through the experimentally determined LET―d values agrees with independently acquired reference values, indicating that the investigated detectors can determine LET― with sufficient accuracy for proton therapy. Significance. OSLDs, TLDs, and FNTDs can be used to determine LET― and RBE in proton therapy. With the capability to determine dose through ionization quenching corrections derived from LET― , OSLDs and TLDs can simultaneously ascertain dose, LET― , and RBE. This makes passive detectors appealing for measurements in phantoms to facilitate validation of clinical treatment plans or experiments related to proton therapy.

Improved modeling of detector response effects in phonon-based crystal detectors used for dark matter searches

Improved modeling of detector response effects in phonon-based crystal detectors used for dark matter searches

Dosimetric response of radiophotoluminescent glass detectors in a scanning pencil proton beam

The dose and linear energy transfer (LET) dependence of the radiophotoluminescence (RPL) response was evaluated for RPL glass detectors, taken from the environmental dosimeter type SC-1, using a clinical 100 MeV and 200 MeV scanning pencil proton beam. The measurements were performed at different positions along the Bragg curves. The fluence-averaged (LETf) and dose-averaged (LETd) LET at the positions of the detectors were calculated using two Monte Carlo codes (MCNP and PHITS). Before measurements in proton beams, the linearity of the dose response for the dose range of interest (up to 10 Gy) was checked and confirmed in a Co-60 gamma ray field, since the FGD-202 reader for SC-1 dosimeters is usually used for doses up to 1 Gy and we found no data for higher doses in the literature. For proton beams, the linear dose response was determined for the doses investigated from 0.5 Gy to 8.8 Gy. For the LET range, which corresponds to the LETd from 0.47 keV/μm to 4.70 keV/μm, a decrease in response with an increase in LET was observed.

Ultra-high-granularity detector simulation with intra-event aware generative adversarial network and self-supervised relational reasoning

Simulating high-resolution detector responses is a computationally intensive process that has long been challenging in Particle Physics. Despite the ability of generative models to streamline it, full ultra-high-granularity detector simulation still proves to be difficult as it contains correlated and fine-grained information. To overcome these limitations, we propose Intra-Event Aware Generative Adversarial Network (IEA-GAN). IEA-GAN presents a Transformer-based Relational Reasoning Module that approximates an event in detector simulation, generating contextualized high-resolution full detector responses with a proper relational inductive bias. IEA-GAN also introduces a Self-Supervised intra-event aware loss and Uniformity loss, significantly enhancing sample fidelity and diversity. We demonstrate IEA-GAN’s application in generating sensor-dependent images for the ultra-high-granularity Pixel Vertex Detector (PXD), with more than 7.5 M information channels at the Belle II Experiment. Applications of this work span from Foundation Models for high-granularity detector simulation, such as at the HL-LHC (High Luminosity LHC), to simulation-based inference and fine-grained density estimation.

Spatio-temporal deep recurrent convolutional neural network for infrared focal plane arrays non-uniformity correction

The inherent non-uniformity generated in infrared focal plane arrays (IRFPA) due to inconsistent responses of detectors, and it significantly degrades the performance of infrared imaging systems. Traditional Non-Uniformity Correction (NUC) methods mainly leverage the temporal low-frequency property of non-uniformity to remove it. In recent years, Convolutional Neural Network (CNN) has gained attention as a powerful tool for conducting NUC using solely spatial information from a single frame. In this study, we propose a deep neural network with a recurrent spatio-temporal feature fusion module to enhance CNN performance using inter-frame information. Initially, the proposed network uses CNN to coarsely extract FPN features solely from the spatial domain. Subsequently, the network merges it with the historical estimation under the guidance of two gating signals, which calculated from spatio-temporal information with gated convolutional layers. Both stages are jointly trained to ensure that the entire network operates end-to-end and adapts to different scenarios, eliminating complex parameter tuning efforts. Experiments demonstrated that the proposed network shows both the advantages of traditional and CNN-based NUC methods. It has a higher convergence starting point, faster convergence speed, and a 1 ∼ 2 dB improvement in PSNR compared to both types of methods.

Technical note: Characterization of a multi-point scintillation dosimetry research platform for a low-field MR-Linac.

MRI-guided radiation therapy (MRgRT) requires unique quality assurance equipment to address MR-compatibility needs, minimize electron return effect, handle complex dose distributions, and evaluate real-time dosimetry for gating. Plastic scintillation detectors (PSDs) are an attractive option to address these needs. To perform a comprehensive characterization of a multi-probe PSD system in a low-field 0.35T MR-linac, including detector response assessment and gating performance. A four-channel PSD system (HYPERSCINT RP-200) was assembled. A single channel was used to evaluate repeatability, percent depth dose (PDD), detector response as a function of orientation with respect to the magnetic field, and intersession variability. All four channels were used to evaluate repeatability, linearity, and output factors. The four PSDs were integrated into an MR-compatible motion phantom at isocenter and in gradient regions. Experiments were conducted to evaluate gating performance and tracking efficacy. For repeatability, the maximum standard deviation of repeated measurements was 0.13% (single PSD). Comparing the PSD to reference data, PDD had a maximum difference of 1.12% (10cm depth, 6.64×6.64 cm2). Percent differences for rotated detector setups were negligible (<0.3%). All four PSDs demonstrated linear response over 10-1000 MU delivered and the maximum percent difference between the baseline and measured output factors was 0.78% (2.49×2.49 cm2). Gating experiments had 400 cGy delivered to isocenter with<0.8 cGy variation for central axis measures and<0.7 cGy for the gradient sampled region. Real-time dosimetry measurements captured spurious beam-on incidents that correlated to tracking algorithm inaccuracies and highlighted gating parameter impact on delivery efficiency. Characterization of the multi-point PSD dosimetry system in a 0.35T MR-linac demonstrated reliability in a low-field MR-Linac setting, with high repeatability, linearity, small intersession variability, and similarity to baseline data for PDD and output factors. Time-resolved, multi-point dosimetry also showed considerable promise for gated MR-Linac applications.

X-ray characterization of a bulk resistive MICROMEGAS operating at low gas pressure

In the last decades, interest has grown in the development of detectors that can accurately measure energy and track of low-energy (1–100 keV) charged particles. In this paper we present our effort to construct a resistive MICROMEGAS detector with a wide amplification gap (192μm), to achieve high gain with a low discharge probability, even when operating with a low-pressure gas down to 50mbar. The detector response (gain, energy resolution, relative primary charge collection efficiency) to X-rays from a 55Fe source was measured under different operating conditions of amplification and drift fields, gas pressure and gas mixture composition. The results obtained and their temporal stability demonstrate that the detector can be used for the measurement of low-energy radiation with good energy resolution.

Enhancing Spectroscopic Experiment Calibration through Differentiable Programming

In this work, we present an innovative calibration technique leveraging differentiable programming to enhance energy resolution and reduce the energy scale systematic uncertainty in X-ray spectroscopic experiments. This approach is demonstrated using synthetic data and is applicable in general to various spectroscopic measurements. This method extends the scope of differentiable programming for calibration, employing Kernel Density Estimation (KDE) to achieve a target Probability Density Function (PDF) for a fully differentiable model of the calibration. To assess the effectiveness of the calibration, we conduct a toy simulation replicating the entire detector response chain and compare it with a standard calibration. This ensures a robust and reliable calibration methodology, holding promise for improving energy resolution and providing a more versatile and efficient approach without the need for extensive fine-tuning.

Search for light WIMP recoils on methane with NEWS-G

The NEWS-G collaboration is searching for light dark matter using single-electron-threshold Spherical Proportional Counters (SPCs) filled with light gaseous targets (H, He, Ne). NEWS-G has built a new 140 cm diameter SPC equipped with a multi-anode ACHINOS sensor. Robust calibrations with a UV laser and an \mathrm{^{37}}37Ar source were performed to characterize the detector response to low energy events and achieve statistical background rejection. This work presents preliminary results from physics data taken with methane, leading to world-leading spin-dependent sensitivity under 2 \mathrm{GeV/c^{2}}GeV/c2 WIMP masses.

Removing ring artifacts in CBCT images via Transformer with unidirectional vertical gradient loss.

Cone-beam computed tomography (CBCT), an important medical modality for disease detection and diagnosis, is currently widely used in clinical practice. However, due to the inconsistent response of CBCT detectors, the lack of proper calibration often leads to the occurrence of ring artifacts in CBCT-reconstructed images. These artifacts may affect physicians' assessment and diagnosis. Therefore, effective elimination of ring artifacts in CBCT images without degrading image quality isimportant. Given the pros and cons of existing methods for removing ring artifacts in CBCT images, this paper is devoted to designing a specific Transformer for this task, leveraging the global and local modeling ability ofTransformer. We design a loss function with dual-domain information fusion for the vanilla Transformer to correct ring artifacts in CBCT images. The method operates in image domain to predict artifact-free outputs and preserve more image details. Meanwhile, we design a tailored loss function incorporating polar domain optimization to remove ring artifacts more effectively. Specifically, an unidirectional gradient loss that constrains vertical gradients in polar domain is imposed, based on the geometric prior that in polar coordinates, ring artifacts predominately affect horizontal gradients while minimally influencing verticalgradients. We conduct extensive ablative and comparative experiments on CBCT/CT image set to validate the performance of the proposed method. First, four ablation experiments demonstrate the feasibility of our approach. Then, we compare our method with several classical methods and the latest state-of-the-arts, and our method achieves the highest quality of corrected images as well as the best evaluation metrics. In these experiments, 5332 CT images were used for training, and 550 CT images, and 500 real CBCT images were used for testing. The source code is available at https://github.com/shasha521/CBCT. Experimental results demonstrate that our method can significantly improve the effectiveness of ring artifact correction. By capitalizing on dual-domain information fusion and a customized loss function, the improved Transformer can not only effectively remove ring artifacts in CBCT images, but also preserve the details of original images quitewell.

Application of wavelet transform in anti-Compton phoswich detector for gamma spectrum

The response of an anti-Compton phoswich detector to gamma rays was investigated using Monte-Carlo method, and the pulses from different crystal cases, including gamma deposition only in the LaBr3(Ce) or CsI(Tl) crystal and coincidence in both crystals, were analyzed. A novel pulse discrimination method for gamma deposition events based on wavelet transform analysis, called SSD (Scale Shape Discrimination), was developed in this study. Compared to the traditional PSD (Pulse Shape Discrimination) method, SSD has the advantage of transforming one-dimensional pulses in the time-domain into two-dimensional time-frequency spectra, providing the more useful features for pulse discrimination. The performances of the Compton suppression and Full-energy peak loss using PSD and SSD methods was studied. The results show that the Compton suppression factor IPSD = 5.12 and ISSD = 5.32, and FEP loss factor PLPSD = 0.0554 and PLSSD = 0.0587. Meanwhile, the influences of the cutoff values for pulse discrimination on the results of I and PL with different method were analyzed.

A thermionic electron gun to characterize silicon drift detectors with electrons

The TRISTAN detector is a new detector for electron spectroscopy at the Karlsruhe Tritium Neutrino (KATRIN) experiment. The semiconductor detector utilizes the silicon drift detector technology and will enable the precise measurement of the entire tritium β-decay electron spectrum. Thus, a significant fraction of the parameter space of potential neutrino mass eigenstates in the keV-mass regime can be probed. We developed a custom electron gun based on the effect of thermionic emission to characterize the TRISTAN detector modules with mono-energetic electrons before installation into the KATRIN beamline. The electron gun provides an electron beam with up to 25 keV kinetic energy and an electron rate in the order of 105 electrons per second. This manuscript gives an overview of the design and commissioning of the electron gun. In addition, we will shortly discuss a first measurement with the electron gun to characterize the electron response of the TRISTAN detector.

Third sound detectors in accelerated motion

An accelerated observer moving through empty space sees particles appearing and disappearing, while an observer with a constant velocity does not register any particles. This phenomenon, generally known as the Unruh effect, relies on an initial vacuum state, thereby unifying the experience of all inertial observers. We propose an experiment to probe this observer-dependent detector response, using a laser beam in circular motion as a local detector of superfluid helium-4 surface modes or third sound waves. To assess experimental feasibility, we develop a theoretical framework to include a non-zero temperature initial state. We find that an acceleration-dependent signal persists, independent of the initial temperature. By introducing a signal-to-noise measure we show that observing this signal is within experimental reach.

Unfolding of mono-energy neutron spectra using artificial neural network based on LMBP training algorithm

In this work, neutron spectra are unfolded using artificial neural networks (ANNs). The neutron response of the NE213 scintillator detector, characterized by the pulse height distribution, is calculated to obtain the necessary data for unfolding the energy spectrum. This is achieved using both analytical response functions and response functions generated by the MCNPX-PHOTRACK code. In this query, the Levenberg-Marquardt method (LMM), which has a high computational speed in the learning method, is used to train the network. The performance of the ANN for unfolding the neutron energy spectrum of the NE213 scintillation detector was evaluated by comparing its results to the established Gravel method. The ANN method consistently produced spectra with a single peak closely matching the incident energy, while the Gravel method showed additional peaks and distortions. Quantitative analysis revealed a lower relative energy peak difference (indicating higher accuracy) for the ANN method compared to Gravel, particularly when noise was introduced into the data. These results suggest that ANNs offer a more robust and accurate approach for neutron spectrum unfolding.

Development And Validation of UV Spectrophotometric Method for The Estimation pf Amlodipine Besylate in Bulk and Dosage Form

A rapid, simple, accurate, and specific UV Spectrophotometric method has been developed for the determination of Amlodipine Besylate in bulk and dosage form. The spectrophotometric detection was carried out at an absorption maximum of 239 nm using dil. HCl as a solvent. The detector response for the Amlodipine Besylate was linear over the selected concentration range 4-20 µg/ml with a correlation coefficient of 0.999 and equation for the regression curve was found to be y= 0.109x + 0.006. These methods can be adopted in the routine assay analysis of Amlodipine Besylate API and pharmaceutical dosage form.

Framework for evaluating photon-counting detectors under pile-up conditions.

While X-ray photon-counting detectors (PCDs) promise to revolutionize medical imaging, theoretical frameworks to evaluate them are commonly limited to incident fluence rates sufficiently low that the detector response can be considered linear. However, typical clinical operating conditions lead to a significant level of pile-up, invalidating this assumption of a linear response. Here, we present a framework that aims to evaluate PCDs, taking into account their non-linear behavior. We employ small-signal analysis to study the behavior of PCDs under pile-up conditions. The response is approximated as linear around a given operating point, determined by the incident spectrum and fluence rate. The detector response is subsequently described by the proposed perturbation point spread function (pPSF). We demonstrate this approach using Monte-Carlo simulations of idealized direct- and indirect-conversion PCDs. The pPSFs of two PCDs are calculated. It is then shown how the pPSF allows to determine the sensitivity of the detector signal to an arbitrary lesion. This example illustrates the detrimental influence of pile-up, which may cause non-intuitive effects such as contrast/contrast-to-noise ratio inversion or cancellation between/within energy bins. The proposed framework permits quantifying the spectral and spatial performance of PCDs under clinically realistic conditions at a given operating point. The presented example illustrates why PCDs should not be analyzed assuming that they are linear systems. The framework can, for example, be used to guide the development of PCDs and PCD-based systems. Furthermore, it can be applied to adapt commonly used measures, such as the modulation transfer function, to non-linear PCDs.

The Recovery and Re-Calibration of a 13-Month Aerosol Extinction Profiles Dataset from Searchlight Observations from New Mexico, after the 1963 Agung Eruption

The recovery and re-calibration of a dataset of vertical aerosol extinction profiles of the 1963/64 stratospheric aerosol layer measured by a searchlight at 32° N in New Mexico, US, is reported. The recovered dataset consists of 105 aerosol extinction profiles at 550 nm that cover the period from December 1963 to December 1964. It is a unique record of the portion of the aerosol cloud from the March 1963 Agung volcanic eruption that was transported into the Northern Hemisphere subtropics. The data-recovery methodology involved re-digitizing the 105 original aerosol extinction profiles from individual Figures within a research report, followed by the re-calibration. It involves inverting the original equation used to compute the aerosol extinction profile to retrieve the corresponding normalized detector response profile. The re-calibration of the original aerosol extinction profiles used Rayleigh extinction profiles calculated from local soundings. Rayleigh and aerosol slant transmission corrections are applied using the MODTRAN code in transmission mode. Also, a best-estimate aerosol phase function was calculated from observations and applied to the entire column. The tropospheric aerosol phase function from an AERONET station in the vicinity of the searchlight location was applied between 2.76 to 11.7 km. The stratospheric phase function, applied for a 12.2 to 35.2 km altitude range, is calculated from particle-size distributions measured by a high-altitude aircraft in the vicinity of the searchlight in early 1964. The original error estimate was updated considering unaccounted errors. Both the re-calibrated aerosol extinction profiles and the re-calibrated stratospheric aerosol optical depth magnitudes showed higher magnitudes than the original aerosol extinction profiles and the original stratospheric aerosol optical depth, respectively. However, the magnitudes of the re-calibrated variables show a reasonable agreement with other contemporary observations. The re-calibrated stratospheric aerosol optical depth demonstrated its consistency with the tropics-to-pole decreasing trend, associated with the major volcanic eruption stratospheric aerosol pattern when compared to the time-coincident stratospheric aerosol optical depth lidar observations at Lexington at 42° N.