Constant Fraction Discriminator Research Articles

Transformer-CNN hybrid network for improving PET time of flight prediction

Objective. In positron emission tomography (PET) reconstruction, the integration of time-of-flight (TOF) information, known as TOF-PET, has been a major research focus. Compared to traditional reconstruction methods, the introduction of TOF enhances the signal-to-noise ratio of images. Precision in TOF is measured by full width at half maximum (FWHM) and the offset from ground truth, referred to as coincidence time resolution (CTR) and bias. Approach. This study proposes a network combining transformer and convolutional neural network (CNN) to utilize TOF information from detector waveforms, using event waveform pairs as inputs. This approach integrates the global self-attention mechanism of Transformer, which focuses on temporal relationships, with the local receptive field of CNN. The combination of global and local information allows the network to assign greater weight to the rising edges of waveforms, thereby extracting valuable temporal information for precise TOF predictions. Experiments were conducted using lutetium yttrium oxyorthosilicate (LYSO) scintillators and silicon photomultiplier (SiPM) detectors. The network was trained and tested using the waveform datasets after cropping. Main results. Compared to the constant fraction discriminator (CFD), CNN, CNN with attention, long short-term memory (LSTM) and Transformer, our network achieved an average CTR of 189 ps, reducing it by 82 ps (more than 30%), 13 ps (6.4%), 12 ps (6.0%), 16 ps (7.8%) and 9 ps (4.6%), respectively. Additionally, a reduction of 10.3, 8.7, 6.7 and 4 ps in average bias was achieved compared to CNN, CNN with attention, LSTM and Transformer. Significance. This work demonstrates the potential of applying the Transformer for PET TOF estimation using real experimental data. Through the integration of both CNN and Transformer with local and global attention, it achieves optimal performance, thereby presenting a novel direction for future research in this field.

Hardware Acceleration of Digital Pulse Shape Analysis Using FPGAs.

The BC501A sensor is a liquid scintillator frequently used in nuclear physics for detecting fast neutrons. This paper describes a hardware implementation of digital pulse shape analysis (DPSA) for real-time analysis. DPSA is an algorithm that extracts the physically relevant parameters from the detected BC501A signals. The hardware solution is implemented in a MicroTCA system that provides the physical, mechanical, electrical, and cooling support for an AMC board (NAMC-ZYNQ-FMC) with a Xilinx ZYNQ Ultrascale-MP SoC. The Xilinx FPGA programmable logic implements a JESD204B interface to high-speed ADCs. The physical and datalink JESD204B layers are implemented using hardware description language (HDL), while the Xilinx high-level synthesis language (HLS) is used for the transport and application layers. The DPSA algorithm is a JESD204B application layer that includes a FIR filter and a constant fraction discriminator (CFD) function, a baseline calculation function, a peak detection function, and an energy calculation function. This architecture achieves an analysis mean time of less than 100 µs per signal with an FPGA resource utilization of about 50% of its most used resources. This paper presents a high-performance DPSA embedded system that interfaces with a 1 GS/s ADC and performs accurate calculations with relatively low latency.

A study for gamma attenuation behavior of polyimide (PI) film by MPPC

Although lead is a very good radiation shielding material, its toxicity has led researchers to find alternative materials instead of it. Moreover, as the use of Kapton polyimide (PI) film in nuclear power plants and space exploration increases, the need to reveal the radiation degradation properties of this material has come along. In this regard, in the present study, it is aimed to determine the mass and linear attenuation coefficients, half value layer, tenth value layer, mean free path and radiation protection efficiency attenuation parameters for this material, experimentally and theoretically, by using the gammas of the 133Ba radioisotope. Experimental gamma attenuation measurements were made by a spectrometer using a Hamamatsu multi pixel photon counter device with a silicon photomultiplier sensor. The constant fraction discrimination timing method was used to reduce the electronic noise of the spectrometer. The attenuation parameters determined experimentally by following two ways were compared with the theoretical ones obtained from the XCOM program.

The analog front end for FastRICH: an ASIC for the LHCb RICH detector upgrade

This work presents the analog circuitry of the FastRICH ASIC, a 16-channel ASIC, developed in a 65 nm CMOS technology specifically designed for the RICH detector at LHCb to readout detectors like Photomultiplier Tubes to be used at the LHC Run 4 and Silicon Photomultipliers candidates for Run 5. The front-end (FE) stage has an input impedance below 50 Ω and an input dynamic range from 5 μA to 5 mA with a power consumption of ∼5 mW/channel. The chip includes a Leading Edge Comparator (LED) and a Constant Fraction Discriminator (CFD) for time pick-off and a Time-to-Digital Converter (TDC) for digitization.

Constant Fraction Discriminator for NA62 experiment at CERN

A new Constant Fraction Discriminator with additionalTime over Threshold measurement capabilities will be presented.It operates in a wide dynamic range of 1:150, with an excellent timeresolution of better than 70 psover one order of magnitude of the input signals.It is highly customizable for different signal shapes and thresholds,using remotely-programmableparameters for Detector Control System commands.Two outputs, each in the Nuclear Instrumentation Module and Low VoltageDifferentialSignaling standards,provide a precise signal arrival time and Time over Thresholdinformation with programmable thresholds.The technical specification and performance measured with cosmic rays and in thehigh-intensity NA62 experiment will be reported.

Using Deep Neural Networks to Improve the Precision of Fast-Sampled Particle Timing Detectors

Measurements from particle timing detectors are often affected by the time walk effect caused by statistical fluctuations in the charge deposited by passing particles. The constant fraction discriminator (CFD) algorithm is frequently used to mitigate this effect both in test setups and in running experiments, such as the CMS-PPS system at the CERN’s LHC. The CFD is simple and effective but does not leverage all voltage samples in a time series. Its performance could be enhanced with deep neural networks, which are commonly used for time series analysis, including computing the particle arrival time. We evaluated various neural network architectures using data acquired at the test beam facility in the DESY-II synchrotron, where a precise MCP (MicroChannel Plate) detector was installed in addition to PPS diamond timing detectors. MCP measurements were used as a reference to train the networks and compare the results with the standard CFD method. Ultimately, we improved the timing precision by 8% to 23%, depending on the detector's readout channel. The best results were obtained using a UNet-based model, which outperformed classical convolutional networks and the multilayer perceptron.

Design and performance of the Fermilab Constant Fraction Discriminator ASIC

We present the design and performance characterization results of the novel Fermilab Constant Fraction Discriminator ASIC (FCFD) developed to readout low gain avalanche detector (LGAD) signals by directly using a constant fraction discriminator (CFD) to measure signal arrival time. Silicon detectors with time resolutions less than 30ps will play a critical role in future collider experiments, and LGADs have been demonstrated to provide the required time resolution and radiation tolerance for many such applications. The FCFD has a specially designed discriminator that is robust against amplitude variations of the signal from the LGAD that normally requires an additional correction step when using a traditional leading edge discriminator. The application of the CFD directly in the ASIC promises to be more reliable and reduces the complication of evolving time-walk corrections throughout the operational lifetime of the detector system. We will present a summary of the measured performance of the FCFD for input signals generated by internal charge injection, LGAD signals from an infrared laser, and LGAD signals from minimum-ionizing particles. The mean time response for LGAD signals with charge ranging between 5 and 26 fC has been measured to vary no more than 10ps, orders of magnitude more stable than an uncorrected leading edge discriminator based measurement, and effectively removes the need for any additional time-walk correction. The measured contribution to the time resolution from the FCFD ASIC is found to be 10ps for signals with charge above 20fC.

Fully Integrated Constant Fraction Discriminators (CFDs): Two Implementations in Submicrometer CMOS Technologies

Fully Integrated Constant Fraction Discriminators (CFDs): Two Implementations in Submicrometer CMOS Technologies

A Fast, Low-Jitter, and Low-Time-Walk Multi-Channel Front-End IC for Diamond and Silicon Radiation Detectors

This paper presents the design and implementation of a radiation-hardened analog front-end (AFE) integrated circuit (IC) developed for interfacing with solid state ionizing radiation detectors, providing accurate amplitude and time-of-arrival measurements. The AFE is designed for use in the Beam Conditions Monitor Prime (BCM’) of the ATLAS experiment at the Large Hadron Collider (LHC). The proposed AFE is comprised of four channels, allowing for re-configuration to operate as either a low-noise high-gain amplifier for beam luminosity measurements, or a high-linearity low-gain amplifier for beam abort functionality. Each of the AFE channels consists of a low noise trans-impedance amplifier (TIA) optimized for minimal jitter and amplitude noise, a second stage differential amplifier, followed by a fully differential Constant Fraction Discriminator (CFD) to provide an amplitude independent time pick-off with a wide dynamic range. The CFD utilizes a new all-pass filter delay topology and high-performance zero-crossing detector to minimize time-walk. The core of each AFE channel occupies an area of 0.06 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in a 65 nm CMOS technology and consumes 57 mW, including the drivers. The measured AFE chips achieve 1 ns pulse rise time, 130 electron baseline equivalent noise charge (ENC), and <25 ps RMS jitter at 1 fC input charge. To the authors’ best knowledge, this work demonstrates the lowest published time-walk of ±6 ps across 30 dB signal dynamic range. Furthermore, irradiated AFEs are shown to tolerate up to 225 Mrad total ionizing dose with no significant degradation in measured performance characteristics.

PMT Waveform Timing Analysis Using Machine Learning Method

The timing information carried by the PMT waveform is important when reconstructing the particle trajectory, especially in the application of time-of-flight detectors. The traditionally used timing methods, including the leading edge discrimination (LED) and the constant fraction discrimination (CFD), are easily realized in the circuit. Since the timing point of the signal should be determined by the whole signal waveform, the CFD and LED method cannot reach the best time resolution. With the development of fast analog-to-digital converter which makes the whole waveform available, more intelligent methods are developed to realize more precise timing. Former studies show that PMT-waveform-analysis model based on convolutional neural network can improve the coincidence time resolution (CTR) of a pair of PMTs by nearly 20%, but the limit of number of labels directly affects the CNN timing performance. In this paper, a new method based on CNN model is introduced for the timing of a pair of Cherenkov-detection MCP-PMTs. The results show a great improvement compared with the CFD method.

Systematic investigation of time walk and time resolution characteristics of CAEN digitizers V1730 and V1751 for application to fast-timing lifetime measurement

The timing performance of the integrated digital constant fraction discriminators of the two digitizer modules V1730 and V1751 from CAEN are systematically investigated with respect to fast-timing lifetime measurements. Systematic and parameter-dependent knowledge of the time walk behavior and the time resolution of the digital constant fraction discriminators is obtained. Understanding these dependencies is crucial for properly calibrating individual fast-timing systems and a comparable investigation of these digitizers was never conducted before. Reference is made to the existing analog standard for fast-timing techniques and recent digital developments. The study shows, that the timing performance of both modules is comparable to other digital fast-timing implementations and established fast-timing setups using analog constant fraction discriminators, but with the added benefit of digital processing. The peculiarities of the modules are pointed out and described. Both digitizer modules were found to be highly effective and user-friendly instruments for modern fast-timing requirements. Best parameter sets for both digitizers as well as best energy application ranges are provided.

Improving fast-timing time-walk calibration standards: Lifetime measurement of the 2[formula omitted] state in 152Gd

A 152Eu source was measured for 28 days using an experimental setup consisting of four LaBr3(Ce) detectors, connected to a CAEN V1730 digitizer, implementing online interpolation constant fraction discrimination for picosecond-precise timestamp determination. Using the definition of the time-walk curve, the lifetime of the 21+ (344 keV) state in 152Gd was re-measured, resulting in τ(21+)=46.9(3) ps. Compared to the previously adopted lifetime the uncertainty is reduced by an order of magnitude. This improved lifetime is of significant importance for electronic fast-timing lifetime measurements, and the impact on the systematic correction procedure and lifetime measurements in the low picosecond regime are discussed.

Correction method for walk error based on the shape of reflective surface in LiDAR

Walk error produced in light detection and ranging (LiDAR) based on the time-of-flight (TOF) leads to loss of ranging accuracy. Walk error, which is systematic and correctable, is mainly attributed to the distance to the target, reflectance, the shape of reflective surface, and so on. In particular, various shapes of received pulse based on the shape of reflective surface have a considerable effect on the ranging accuracy. In this paper an incoherent pulsed laser echo equation for different shapes of reflective surface is established and it is found that parameters that can represent various shapes of received pulse involve received pulse width and slew rate. A measurement method of pulse width and slew rate combining a constant fraction discriminator (CFD) principle with a time over threshold (TOT) is proposed. It is also found that the proposed method is more efficient in walk error correction than the TOT by obtaining walk error corrections corresponding to pulse width and slew rate and determining the corresponding 2D surface polynomial coefficients. The obtained polynomial coefficients are used to ensure the ranging accuracy of the LiDAR within ± 3 cm.

Study of timing performance parameters for a SiPM-based digital positron annihilation lifetime spectrometer

Abstract Positron annihilation lifetime spectroscopy (PALS) is a popular method for studying defects in materials. With the development of fast digital oscilloscopes and digitizers, the conventional analog positron annihilation lifetime (PAL) spectrometer is being replaced by a digital PAL spectrometer. Recently, newly conducted research has developed a PAL spectrometer using a silicon photomultiplier (SiPM) instead of a photomultiplier tube (PMT). Timing resolution of PAL spectrometer needs to be improved to identify the lifetimes of positrons. Many parameters affect the timing performance of a SiPM-based digital PAL spectrometer: bias voltage, pulse smoothing, and the constant fraction value of digital constant fraction discrimination (dCFD). Timing resolution depends on the radiation energy, but only a few studies have considered the energy difference of 1274 keV and 511 keV. In this study, we optimized the timing performance parameters of the SiPM-based digital PAL spectrometer by conducting the timing resolution measurements using two γ-ray sources (22Na and 60Co). With a 32 V bias voltage, 5th degree polynomial fitting method, and optimal constant fraction value, we optimized the timing resolution of our SiPM-based digital PAL spectrometer. Furthermore, the optimal constant fraction value depended on the γ-ray energy and we verified it by timing resolution measurement using 207Bi. We studied the reason why performance parameters have optimal conditions and the optimal constant fraction value varies depending on the γ-ray energy. With optimized performance parameters, we measured the lifetime spectrum of pure silicon to confirm the SiPM-based digital PAL spectrometer. The timing resolution function of the SiPM-based digital PAL spectrometer was 185.6 ps.

Upgrade of ASACUSA’s antihydrogen detector

The goal of the ASACUSA (Atomic Spectroscopy And Collisions Using Slow Antiprotons) CUSP experiment at CERN’s Antiproton Decelerator is to measure the ground state hyperfine splitting of antihydrogen in order to test whether CPT invariance is broken.The ASACUSA hodoscope is a detector consisting of two layers of 32 plastic scintillator bars individually read out by two serially connected silicon photomultipliers (SiPMs) on each end. Two additional layers for position resolution along the beam axis were scintillator fibres, which will now be replaced by scintillating tiles placed onto the existing bars and also read out by SiPMs. If the antiproton of antihydrogen annihilates in the centre of the hodoscope, particles (mostly pions) are produced and travel through the various layers of the detector and produce signals.The hodoscope was successfully used during the last data taking period at CERN. The necessary time resolution to discriminate between particles travelling through the detector from outside and particles produced in the centre of the detector was achieved by the use of waveform digitisers and software constant fraction discrimination. The disadvantage of this readout scheme was the slow readout speed, which was improved by two orders of magnitude. This was done by omitting the digitisers and replacing them with TDCs reading out the digital time-over-threshold (ToT) signal using leading edge discrimination.

The fast beam condition monitor as standalone luminometer of the CMS experiment at the HL-LHC

For the Phase-2 CMS upgrade for the High-Luminosity LHC, a luminosity uncertainty of 1% is targeted. To achieve this goal, measurements from multiple luminometers with orthogonal systematics are required. A standalone luminometer, the Fast Beam Condition Monitor (FBCM) is being designed for the online bunch-by-bunch luminosity measurement. The sampling time resolution of ∼0.7 ns also enables the measurement of beam-induced backgrounds. In this paper, the hardware architecture and the readout protocol of the FBCM are described. The expected performance with a simple behavioral model of the front-end comprising a constant fraction discriminator is discussed, although the final implementation in the ASIC is still under discussion. Simulation results show that the FBCM will provide the required statistical uncertainty and deviation from linearity by employing 336 silicon-pad sensors, each with an area of about 3 mm2. In addition, the front-end with sensitivity to as low as 6000 electrons will satisfy the longevity constraints for an exposure of 1 MeV neutron equivalent fluence of 3.5 × 1015 per cm2.

3D velocity map imaging of electrons with TPX3CAM.

We demonstrate three-dimensional velocity map imaging of low energy electrons using a TPX3CAM, where the three-dimensional momentum information [px, py, pz] is encoded in position and timing [x, y, t] of hits on the camera sensor. We make use of the camera sensor for the [x, y] information and a constant fraction discriminator and fast time to digital converter in the camera for the time information. We illustrate the capabilities of our apparatus by presenting above threshold ionization measurements of xenon, which produces well defined structures in the momentum resolved photoelectron yield.

Efficient Delay Correction for Total-Body PET Kinetic Modeling Using Pulse Timing Methods.

Quantitative kinetic modeling requires an input function. A noninvasive image-derived input function (IDIF) can be obtained from dynamic PET images. However, a robust IDIF location (e.g., aorta) may be far from a tissue of interest, particularly in total-body PET, introducing a time delay between the IDIF and the tissue. The standard practice of joint estimation (JE) of delay, along with model fitting, is computationally expensive. To improve the efficiency of delay correction for total-body PET parametric imaging, this study investigated the use of pulse timing methods to estimate and correct for delay. Methods: Simulation studies were performed with a range of delay values, frame lengths, and noise levels to test the tolerance of 2 pulse timing methods-leading edge (LE) and constant fraction discrimination and their thresholds. The methods were then applied to data from 21 subjects (14 healthy volunteers, 7 cancer patients) who underwent a 60-min dynamic total-body 18F-FDG PET acquisition. Region-of-interest kinetic analysis was performed and parametric images were generated to compare LE and JE methods of delay correction, as well as no delay correction. Results: Simulations demonstrated that a 10% LE threshold resulted in biases and SDs at tolerable levels for all noise levels tested, with 2-s frames. Pooled region-of-interest-based results (n = 154) showed strong agreement between LE (10% threshold) and JE methods in estimating delay (Pearson r = 0.96, P < 0.001) and the kinetic parameters vb (r = 0.96, P < 0.001), Ki (r = 1.00, P < 0.001), and K1 (r = 0.97, P < 0.001). When tissues with minimal delay were excluded from pooled analyses, there were reductions in vb (69.4%) and K1 (4.8%) when delay correction was not performed. Similar results were obtained for parametric images; additionally, lesion Ki contrast was improved overall with LE and JE delay correction compared with no delay correction and Patlak analysis. Conclusion: This study demonstrated the importance of delay correction in total-body PET. LE delay correction can be an efficient surrogate for JE, requiring a fraction of the computational time and allowing for rapid delay correction across more than 106 voxels in total-body PET datasets.

Tip-timing accuracy improvement using optical fiber bundle probe with GRIN lens under varying blade tip clearance

The blade tip-timing (BTT) method has become the industry standard in blade vibration measurement. It monitors blade vibration based on the different times of arrival (ToAs) between blade vibration and not. The optical fiber bundle (OFB) probe is widely used to obtain ToA because of its small size, fast response, and high tip-timing accuracy. ToA is usually obtained by comparing the received signal with a fixed threshold level. However, the varying blade tip clearance (BTC) will affect the received signal, which directly causes the tip-timing error. We propose an optical fiber probe with GRIN lens, which eliminates the tip-timing error caused by varying BTC through the constant-fraction discrimination (CFD) method. The model of the OFB probe with GRIN lens is first established. Model analysis indicates that ToA obtained by the proposed method is constant no matter how BTC changes. Finally, the accuracy of the model and the effectiveness of the method are verified by two experiments. When BTC varied from 1.5 to 3.5 mm, the maximum tip-timing errors of OFB probe without and with GRIN lens were 181.12 μs and 10.44 μs, respectively.

Neural network-featured timing systems for radiation detectors: performance evaluation based on bound analysis

Waveform sampling systems are used pervasively in the design of front end electronics for radiation detection. The introduction of new feature extraction algorithms (eg. neural networks) to waveform sampling has the great potential to substantially improve the performance and enrich the capability. To analyze the limits of such algorithms and thus illuminate the direction of resolution optimization, in this paper we systematically simulate the detection procedure of contemporary radiation detectors with an emphasis on pulse timing. Neural networks and variants of constant fraction discrimination are studied in a wide range of analog channel frequency and noise level. Furthermore, we propose an estimation of multivariate Cramér Rao lower bound within the model using intrinsic-extrinsic parametrization and prior information. Two case studies (single photon detection and shashlik-type calorimeter) verify the reliability of the proposed method and show it works as a useful guideline when assessing the abilities of various feature extraction algorithms.