Detector Signal Research Articles

Detector signal characterization with a Bayesian network in XENONnT

Detector signal characterization with a Bayesian network in XENONnT

A novel method for measuring the charging kinetics of dielectrics under electron irradiation in SEM

A novel method is proposed to measure the charging potential of dielectric targets under medium energy electron irradiation in a scanning electron microscope. The method is based on the measurement of backscattered electron signals by standard semiconductor or scintillation detectors. The signal is pre-calibrated by grey scale levels on the SEM screen. The detector signal is made up with backscattered and secondary electrons which are accelerated in the electric field created above the dielectric surface under irradiation.

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

Real-time queue length is a crucial information, increasingly needed for signal operation and signal optimization purposes. This paper proposes a novel multivariate time-varying Kalman filter approach to estimate the cycle-based maximum queue lengths in real-time by only using high-resolution vehicle loop detector data and signal timing data. The modeling framework builds on state changing points that can be identified at detector site and shockwave theory that models the propagation of traffic states in the space–time domain. The times at which traffic states change at the detector site, known as break points (e.g., free flow to jam condition, jam to saturation condition, etc.) are identified using high resolution detector data and the end of the queue is estimated using linear models that build on the shockwave theory. Nevertheless, this deterministic approach, which is previously proposed in the literature, does not account for measurements errors associated with traffic state changing points or the assumptions in the shockwave theory. Therefore, we propose a multivariate time-varying Kalman filter approach to produce a robust estimate for the cycle-based maximum queue length in both undersaturated and oversaturated conditions. Further, the developed algorithm can estimate the residual queue length and inform its occurrence in case of oversaturation. The proposed methodology can easily be adapted in practice, as it relies solely on measurements from a single loop detector that may be located close to the stop line.

Development of an alternative device for measurement and characterization of selected meteorological parameters

Weather monitoring and forecasting during some of nature’s most violent events, such as lightning and thunder, necessitates immediate preventive action for improved agricultural precision, power equipment effectiveness among others. Weather stations that are all-in-one for villages, low-income communities, and cities could provide a dependable, cost-effective, robust, and user-friendly solution. A wide range of low-cost weather monitoring stations equipped with ground-based and satellite-based lightning detectors are available on the market. This paper develops a low-cost real-time data logger device that measures lightning strikes and other weather parameters. Temperature and relative humidity are detected and recorded by the sensor (BME280). The sensing unit, readout circuit unit, microcontroller unit, recording unit, real-time clock, display unit, and power supply unit are the seven sections of the lightning detector with a real-time data logger. The sensing unit of the instrument is made of a lightning sensor glued to a polyvinyl chloride (PVC) to prevent moisture inflow and short circuit. The readout circuit consists of a 16-bit analog-to-digital converter and a filter designed to improve the output signal of the lightning detector. It was programmed with C-language and tested using the integrated development environment on the Arduino-Uno microcontroller (IDE). The device was calibrated, and its accuracy was determined using data from a standard lightning detector instrument from the Nigerian Meteorological Agency (NIMET).

Prediction of supernova neutrino signals by detectors and its future challenges

Supernova neutrinos produced during a core collapse of a massive star, carries 99% of the energy produced during the violent phenomenon. These neutrinos are weakly interacting massive particles and can provide useful information for both particle physics (neutrino oscillations parameters) and astrophysics (explosion mechanism). This information can be used to explore physics beyond the standard model. Neutrinos escape from the supernova core hours before the light, so a neutrino signal providing information about supernova direction can enable early observation. The current generation of detectors, like, Super-Kamiokande (Super-K), Large Volume Detector (LVD), Borexino, Kamioka Liquid Scintillator Antineutrino Detector (KamLAND), and IceCube, as well as HALO, Daya Bay(reactor neutrino experiment) and NuMI Off-Axis νe Appearance experiment (NOvA), have the ability to detect only a few orders of magnitude of events and the next generation experiment like, Hyper-Kamiokande (Hyper-K), Deep Underground Neutrino Experiment (DUNE), and Jiangmen Underground Neutrino Observatory (JUNO) will have yet another order of magnitude in reach, as well as richer flavor sensitivity. This work will present a Monte Carlo based study using the SNOwGLoBES [1] package, which is used to estimate the event rate using folded fluxes, cross-sections, and detector smearing to determine mean expected neutrino interaction signals in multiple current and future detectors. A study is carried out for the calculation of core-collapse neutrino event rates in realistic detectors for different flux models, effects of different parameters on flux and its variation with time.

Improved Radio-Cesium Detection Using Quantitative Real-Time Autoradiography.

Cesium-134 and -137 are prevalent, long-lived, radio-toxic contaminants released into the environment during nuclear accidents. Large quantities of insoluble, respirable Cs-bearing microparticles (CsMPs) were released into the environment during the Fukushima Daiichi nuclear accident. Monitoring for CsMPs in environmental samples is essential to understand the impact of nuclear accidents. The current detection method used to screen for CsMPs (phosphor screen autoradiography) is slow and inefficient. We propose an improved method: real-time autoradiography that uses parallel ionization multiplier gaseous detectors. This technique permits spatially resolved measurement of radioactivity while providing spectrometric data from spatially heterogeneous samples-a potential step-change technique for use after nuclear accidents for forensic analysis. With our detector configuration, the minimum detectable activities are sufficiently low for detecting CsMPs. Further, for environmental samples, sample thickness does not detrimentally affect detector signal quality. The detector can measure and resolve individual radioactive particles ≥465 μm apart. Real-time autoradiography is a promising tool for radioactive particle detection.

Sensitivity Enhancement for Separation-Based Analytical Techniques Utilizing Solid-Phase Enrichment Approaches and Analyte Derivatization for Trace Analysis in Various Matrices

Despite the fact that strong routine separation methodologies can give reliable specificity and validity at usual working pharmaceutical concentrations, they may fail at very low concentration levels. This poses considerable challenges for researchers investigating product purity and therapeutic drug monitoring. Sensitivity enhancement procedures are thus required to maximize the performance of separation techniques. Solid-phase extraction/solid-phase enrichment (SPE/SPEn) and pre-, post-, and in-column derivatization, as well as the use of sensitive detection devices, are the simplest strategies for improving sensitivity of separation-based analytical techniques. Large-volume injection of samples with online SPE/SPEn coupled with separation techniques increased sensitivity and improved detection as well as quantification limits without affecting peak shape and system performance. Although the primary purpose of derivatization is to improve sensitivity and selectivity, greener derivatization is growing in popularity and should be considered in analytical chemistry. In general, two strategies are essential for accomplishing greener derivatization goals. The first is the search for and use of ecologically acceptable derivatizing reagents, solvents, and reaction conditions. The second is miniaturization and automation of analytical methods. This review discusses significant advances in separation-based analytical techniques, specifically enrichment approaches and detector signal improvement for pharmaceutical quantification in various matrices at very low concentration levels. As a result of improved analytical systems setup in drug assays, the possibility of high-throughput analyses was also highlighted.

A Low-Power DROIC With Extended-Counting ADC for Uncooled Infrared Silicon Diode Detectors

A low-power digital readout integrated circuit (DROIC) for silicon diode uncooled infrared focal plane arrays (IRFPAs) is presented. The DROIC adopts a 14-bit column-level extended-counting analog-to-digital converter (ADC) based on a cascade of a coarse continuous-time Σ-ADC and a fine single-slope ADC. While the weak detector signal is integrated, the coarse conversion is implemented by a feedback current-steering digital-to-analog converter (IDAC), which shortens the signal chain and reduces the bandwidth requirement for the op-amp, to reduce power consumption. Besides, the ramp signal of the fine conversion is generated locally by an additional column-level IDAC, which matches the coarse conversion IDAC to decrease the DNL. Also, a low-power non-uniformity calibration circuit is adopted to compensate the non-uniformity of the IRFPA and adjust the ADCfs input signal range. The DROIC with 1024 ×768 pixel array is fabricated in a 0.18μm CMOS process. The experimental results demonstrate the DROIC consumes 109mW. The noise is 1.7LSB and the equivalent input noise voltage of the column circuit is about 2.1μVrms. The INL and DNL are less than +6.1LSB/.4.4LSB and +0.40LSB/.0.38LSB, respectively.

NTIMP1—A Fast Pulse Readout Chip With 1.2 V Power Supply Applied to the Diamond Detector in HIAF

A very fast pulse readout ASIC, NTIMP1, with 1.2 V power supply is presented in this work. It is going to be used as front-end electronics (FEE) for reading out the diamond detector signals in the TOF (Time of Flight) wall of RIBLL2 experiment of the High Intensity Heavy Ion Accelerator Facility (HIAF), China. So that an 8-channel fast front-edge readout chip named as NTIMP1 is proposed in this work. Each channel of NTIMP1 has a high-bandwidth preamplifier (with adjustable thresholds) dealing with differential current input, a fast hysteresis discriminator, and a LVDS (Low-Voltage Differential Signaling) module ensuring long-distance signal transmission. Fabricated with 0.13 μm standard CMOS Technology, NTIMP1 can get an input ranging from 2 fC to 2000 fC and the input impedance of the preamplifier can be adjusted externally with an off-chip resistor, so as to match with the electrode impedance of diamond detector. The bandwidth of the preamplifier is 495.5 MHz, which allows a very short signal peaking time of no more than 1 ns. The jitter of the leading edge is lower than 15 ps with 100 fC input charge suggesting that NTIMP1 is suitable for high-resolution TOF measurement as well as time-slewing correction.

Streaming DAQ Software Prototype at the J-PARC Hadron Experimental Facility

In recent years, experiments in particle physics and nuclear physics have required faster data collection systems and advanced trigger systems as the beam intensity has been increased. The current data acquisition (DAQ) system at the Japan Proton Accelerator Research Complex (J-PARC) Hadron Experimental Facility (HEF) uses fixed- and low-latency triggers with dedicated hardware to reduce data and event-building software that merges data into a single endpoint. This conventional DAQ system is expected to be inadequate for future experiments. It has to be replaced with a new simplified but powerful system called streaming DAQ, which collects the detector signals and filters them with software running on many computers. Therefore, we developed a prototype of streaming DAQ software for the J-PARC HEF using FairMQ and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Redis</i> as middleware. The key features include simplicity and a low learning cost to develop and be operated by a small number of people. The software can be used in a fully streaming readout system and in the triggered DAQ and the combined DAQ of the hardware and software triggers.

PulseDL-II: A System-on-Chip Neural Network Accelerator for Timing and Energy Extraction of Nuclear Detector Signals

Front-end electronics equipped with high-speed digitizers are being used and proposed for future nuclear detectors. Recent literature reveals that deep learning models, especially one-dimensional convolutional neural networks, are promising when dealing with digital signals from nuclear detectors. Simulations and experiments demonstrate the satisfactory accuracy and additional benefits of neural networks in this area. However, specific hardware accelerating such models for online operations still needs to be studied. In this work, we introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PulseDL-II</i> , a system-on-chip (SoC) specially designed for applications of event feature (time, energy, etc.) extraction from pulses with deep learning. Based on the previous version, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PulseDL-II</i> incorporates a RISC CPU into the system structure for better functional flexibility and integrity. The neural network accelerator in the SoC adopts a three-level (arithmetic unit, processing element, neural network) hierarchical architecture and facilitates parameter optimization of the digital design. Furthermore, we devise a quantization scheme compatible with deep learning frameworks (e.g., TensorFlow) within a selected subset of layer types. We validate the correct operations of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PulseDL-II</i> on field programmable gate arrays (FPGA) alone and with an experimental setup comprising a direct digital synthesis (DDS) and analog-to-digital converters (ADC). The proposed system achieved 60 ps time resolution and 0.40% energy resolution at signal to noise ratio (SNR) of 47.4 dB.

Fire Alarm Systems

Abstract: The electrical or electronic system that can detect fire-related accidents and can alert or notify peoples, is called a Fire alarm and detection system. The fire alarm system is very important for safety in residential buildings, factories, houses, School/colleges, Hospital etc. Generally, the fire alarm system is installed in a building to detect the fire anywhere in that building. The fire alarm system has two main parts - a detection system and a notification or alarm system. Using the detection system, it senses the fire or fire-related incidents, and using the alarm system it notifies the people. Fire alarm system consists of control panel, smoke detector, MCP and Electronic Sounder. The Brain of fire alarm system is the Fire Alarm Control Panel. It is the central hub for all the detector signal to be wired and provides a status indication to the users.

Large-acceptance isotope identification array FAZIA: Status and R&D activities for upgrade

The FAZIA apparatus is a multi-detector array designed to identify a wide range of charge and mass of reaction products in heavy-ion collisions in the Fermi energy domain. The basic module of FAZIA is the block, consisting of 16 three-layer telescopes. The first two layers are highly homogeneously doped Si detectors with thicknesses of 300μm and 500μm, respectively, and the third layer is a 10 cm thick CsI(Tl) scintillator read out by a photodiode. The detector signals are extracted in real time based on the digital signal processing implemented on the FPGAs. The recent experiments demonstrated that the charge could be discriminated up to more than Z = 54 using the ΔE-E technique and the pulse shape analysis. In addition, the isotopic discrimination has been achieved up to Z ∼ 25 with the ΔE-E technique and up to Z ∼ 20 with the pulse shape analysis in the silicon layer. Recently, there have been activities for the FAZIA detector upgrade to use thicker and thinner silicon layers for enlarging the kinematic coverage. In addition, R&D is in progress to make the front-end electronics board more compact and versatile. This paper is dedicated to the description of the current status of the FAZIA detector and some highlights of the R&D activities for the upgrade.

Characterization of a diode dosimeter for UHDR FLASH radiotherapy.

Ultra-high dose rate (UHDR) FLASH beams typically deliver dose at rates of >40 Gy/sec. Characterization of these beams with respect to dose, mean dose rate, and dose per pulse requires dosimeters which exhibit high temporal resolution and fast readout capabilities. A diode EDGE Detector with a newly designed electrometer has been characterized for use in an UHDR electron beam and demonstrated appropriateness for UHDR FLASH radiotherapy dosimetry. Dose linearity, mean dose rate, and dose per pulse dependencies of the EDGE Detector were quantified and compared with dosimeters including a W1 scintillator detector, radiochromic film, and ionization chamber that were irradiated with a 10 MeV UHDR beam. The dose, dose rate, and dose per pulse were controlled via an in-house developed scintillation-based feedback mechanism, repetition rate of the linear accelerator, and source-to-surface distance, respectively. Depth-dose profiles and temporal profiles at individual pulse resolution were compared to the film and scintillation measurements, respectively. The radiation-induced change in response sensitivity was quantified via irradiation of ∼5kGy. The EDGE Detector agreed with film measurements in the measured range with varying dose (up to 70 Gy), dose rate (nearly 200 Gy/s), and dose per pulse (up to 0.63 Gy/pulse) on average to within 2%, 5%, and 1%, respectively. The detector also agreed with W1 scintillation detector on average to within 2% for dose per pulse (up to 0.78 Gy/pulse). The EDGE Detector signal was proportional to ion chamber (IC) measured dose, and mean dose rate in the bremsstrahlung tail to within 0.4% and 0.2% respectively. The EDGE Detector measured percent depth dose (PDD) agreed with film to within 3% and per pulse output agreed with W1 scintillator to within -6% to +5%. The radiation-induced response decrease was 0.4% per kGy. The EDGE Detector demonstrated dose linearity, mean dose rate independence, and dose per pulse independence for UHDR electron beams. It can quantify the beam spatially, and temporally at sub millisecond resolution. It's robustness and individual pulse detectability of treatment deliveries can potentially lead to its implementation for in vivo FLASH dosimetry, and dose monitoring.

Strong-field nonsequential double photoionization using virtual-detector theory with path summation

We present an ab initio study of the nonsequential strong-field ionization dynamics of a model two-electron atom with helium character. Single- and double-ionization events are characterized and displayed using detector signals extracted at different points in the two-electron two-dimensional space. The double photoelectron momentum distribution is calculated via coherent path-summation over virtual-particle trajectories. A comparison is made between the momentum distributions obtained with the virtual-detector method, the Schr\"odinger wave function, and the time-dependent surface flux method developed by Tao and Scrinzi [New J. Phys. 14, 013021 (2012)]. Insights into different ionization and electron recollision pathways are gained from detailed virtual-particle tracking and energy-time readouts. This study demonstrates the extension of virtual-detector theory to strong-field multielectron quantum dynamics and highlights the importance of the evolving quantum phase in quasiclassical electron propagation.

A PIN photodiode ionizing radiation detector with small angular dependence and low buildup

PurposeTo develop an improved PIN photodiode detector that has low angular dependence and small buildup. Show that the measured dose compares well with the dose calculated by a treatment planning system for static fields at oblique angles and rotationally delivered fields. MethodsCommercially available PIN photodiodes, VEMD1060X01, (Vishay Semiconductor, Shelton, CT), are fabricated into detectors that can be used for measurement of ionizing radiation. PIN photodiodes are soldered onto coaxial cables in an edge-on orientation and are mounted in a symmetrical package. Detector signals are measured with an electrometer with zero input bias voltage. Dose is measured from a Varian Trilogy (Varian Medical Systems, Milpitas, CA) linear accelerators 6 MV photon and 6 MeV electron beams. An Eclipse (Varian Medical Systems, Milpitas, CA) commercial treatment planning system Acuros and electron Monte Carlo algorithms are used for calculating dose expected in various irradiation geometries. ResultsThe single diode detector has an angular dependence between −1.1% and +1.2% and a buildup of 0.6 mm water equivalence. Measurements of dose at 0.3, 0.5, 1.0 and 1.5 cm depth from oblique static beams and from intensity modulated radiation therapy (IMRT) delivered beams agree with planning system calculations within ±1.5%. ConclusionsA clinically useable dose detector can be fabricated from a PIN type photodiode. This diode detector can be used to measure dose at the surface of a patient under a bolus if one is used. Measurements agree with calculations for static fields at oblique angles as well as rotational IMRT delivered beams.

Development of a readout electronic prototype system for the MWDC at the ETF in HIRFL-CSR

This paper proposes and implements a readout electronic prototype system for a Multi-Wire Drift Chamber (MWDC) detector. This system includes Front-End Electronics (FEE), Sub_Data Acquisition (Sub_DAQ), and Common Data Acquisition Unit (CDAU). Based on a self-developed Application-Specific Integrated Circuit (ASIC) chip, the FEE amplifies and reshapes the detector signals before transmitting them via a high-density micro-coaxial cable to the Sub_DAQ. The Sub_DAQ, based on a Field-Programmable Gate Array (FPGA), was designed to process MWDC signals. The Sub_DAQ can perform an analogue-to-digital conversion, online data processing, and package transmission before transmitting the data to the CDAU via a high-speed optical fibre link. The CDAU gathered data, online processed the data, and then transmitted the data to the computer via the PCIe 3.0 interface. This paper will discuss the design process, the implementation, and the initial test results of the readout electronic prototype system.

A pile noise experiment in the reference core of the nuclear research reactor LR-0

For safety reasons, it is important to simulate precisely the kinetic behavior of light water nuclear reactors (LWR) in nominal or incidental situations. In the point kinetic approximation, a few integral parameters allow describing the reactor’s behavior. It is of interest to measure those parameters, such as the delayed neutron fraction and delayed neutron abundances, in low power research reactors loaded with benchmarked fuel configurations to compare with simulations results. In this context, Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) and Centrum Výzkumu Řež (CVŘ) have been collaborating towards measuring the delayed neutron fraction of LR-0, a VVER-type research reactor operated by CVŘ. This paper presents the first estimation of the delayed neutron fraction of the reactor loaded with six fuel assemblies, arranged in a small hexagonal lattice with a center cavity accessible for instrumentation. This configuration was chosen because it was very close to the so-called reference configuration with seven fuel assemblies, the one that was benchmarked in the NEA IRPheP Handbook. The measurement was performed in July 2021 using the CEA-developed acquisition system SPECTRON dedicated to pile noise experiments. Pile noise refer to a set of techniques which focus on the correlations induced by the fission process in the signals of neutron detectors. The experimental campaign was designed to meet two objectives: first to provide an estimation of the delayed neutron fraction; second to study the impact of the location of the neutron detectors on the quality of the results. Two fission chambers were used, one was fixed and located in the core center and the second was placed in various locations in the reflector. Several configurations were tested with the mobile detector progressively moved up to 20 cm from the closest fuel element. The reactor fission rate was obtained thanks to gamma spectrometry on metal foils (gold, nickel and iron). Simulations with TRIPOLI-4® and JEFF33 libraries were performed to convert the saturated activities into fission rates. The delayed neutron fraction was estimated at 782 ± 10 pcm and the generation time was measured at 39.1 ± 0.5 μs. The uncertainty balance is as follows: 2 % associated to the Diven factor and 1.5 % associated to the core’s integral fission rate and 0.5% for the statistical uncertainty. The reproducibility of the experiments was found very good, with a negligible dispersion amongst experiments (0.2 %). These results are valuable complements to the characterization of LR-0 reference neutron benchmark field.

Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

FIB/SEM tomography represents an indispensable tool for the characterization of three-dimensional nanostructures in battery research and many other fields. However, contrast and 3D classification/reconstruction problems occur in many cases, which strongly limits the applicability of the technique especially on porous materials, like those used for electrode materials in batteries or fuel cells. Distinguishing the different components like active Li storage particles and carbon/binder materials is difficult and often prevents a reliable quantitative analysis of image data, or may even lead to wrong conclusions about structure-property relationships. In this contribution, we present a novel approach for data classification in three-dimensional image data obtained by FIB/SEM tomography and its applications to NMC battery electrode materials. We use two different image signals, namely the signal of the angled SE2 chamber detector and the Inlens detector signal, combine both signals and train a random forest, i.e. a particular machine learning algorithm. We demonstrate that this approach can overcome current limitations of existing techniques suitable for multi-phase measurements and that it allows for quantitative data reconstruction even where current state-of the art techniques fail, or demand for large training sets. This approach may yield as guideline for future research using FIB/SEM tomography.

Distinguishing a stochastic gravitational-wave signal from correlated noise with joint parameter estimation: Fisher analysis for ground-based detectors

Search sensitivity to a stochastic gravitational-wave background (SGWB) is enhanced by cross-correlating detector signals. However, one of the most serious concerns is the environmental noise correlated between detectors. The global electromagnetic fields on the Earth, known as Schumann resonances, produce the correlated noise through the instrumental magnetic couplings. In this paper, we study the detectability of a SGWB in the presence of the correlated magnetic noise, using the Fisher analysis based on the analytical model of the correlated magnetic noise. We find that there is no significant degeneracy between the SGWB and noise parameters. Marginalizing over the correlated noise parameters degrades the constraint on each SGWB parameter by a factor of $\ensuremath{\sim}2$ at most in the four-detector case, irrespective of the strength of the magnetic coupling. We also confirm that the forecast results are robust against the variation of correlated noise parameters and can vary up to 40% in the realistic range of the coupling parameters for the second-generation detectors. However, ignoring the correlated noise in parameter estimation generally leads to a biased constraint on the SGWB parameters. If the coupling strength is twice as large as expected, this could result in a serious bias.