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![6.10. Generation of random telegraph noise (left) and of 1/f noise (right) by trapping-detrapping. Adapted from Compagnoni et al. [53].](profile/Veljko-Radeka/publication/253528840/figure/fig2/AS:11431281105916385@1670520293259/10-Generation-of-random-telegraph-noise-left-and-of-1-f-noise-right-by.png)
6.10. Generation of random telegraph noise (left) and of 1/f noise (right) by trapping-detrapping. Adapted from Compagnoni et al. [53].
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This document is part of Part 1 'Principles and Methods' of Subvolume B 'Detectors for Particles and Radiation' of Volume 21 'Elementary Particles' of Landolt-Börnstein - Group I 'Elementary Particles, Nuclei and Atoms'. It contains the Section '3.6 Signal Processing for Particle Detectors' of Chapter '3 Particle Detectors and Detector Systems' wit...
Citations
... It is worthwhile to note that this component is a combination of detector and FEE interplay because, if the noise source is located within the reset device, the noise is induced and determined by the detector through . In case the charge preamplifier employs a pulsed reset a=0; however pulsed reset preamplifiers can suffer from an additional noise contribution known as kTC noise, arising from the sampling of the thermal noise of the switch resistance on the feedback capacitance at the end of the reset phase [35], and can suffer also from stability issues that might result in similar fluctuations on the output baseline level [36]. These noise contributions can however be removed by filtering the low-frequency band of the noise spectrum, which can be done using an AC coupling or timevariant filtering techniques such as correlated double sampling (CDS) [35]. ...
... In case the charge preamplifier employs a pulsed reset a=0; however pulsed reset preamplifiers can suffer from an additional noise contribution known as kTC noise, arising from the sampling of the thermal noise of the switch resistance on the feedback capacitance at the end of the reset phase [35], and can suffer also from stability issues that might result in similar fluctuations on the output baseline level [36]. These noise contributions can however be removed by filtering the low-frequency band of the noise spectrum, which can be done using an AC coupling or timevariant filtering techniques such as correlated double sampling (CDS) [35]. ...
The electronic noise is a key-issue during the phases of design, integration and characterization of a detection system for ionizing radiation, as it determines both its ultimate and actual performances. The precise identification and quantification of all noise sources and associated components allow to implement specific strategies for their control and minimization during the system design and manufacturing phases, to disentangle all noise contributions, and to verify their correspondence with the expectations during the system characterization. An effective approach to the electronic noise problem requires to consider in detail all the parts of the detection system but it is not so rare to still observe that the
electronic noise
is erroneously confused or interpreted as the
noise of the electronics
or as the quadratic sum of the electronics’ and detector’s noise, usually reducing the latter to that one associated to its dark current only. In this paper, a detailed analysis of the noise model of a radiation detection system employing a semiconductor detector is presented using a unified approach which takes into account all sources and causes of electronic noise and their reciprocal interaction. The noise related to the generation, transport and loss of the signal charge in the detector are analyzed in detail and, in particular, the charge trapping and detrapping processes, showing how their contributions could be not negligible even in detectors based on high purity semiconductors. The unified approach allows to disclose the interplay between the detector, the interconnection and the front-end electronics showing that some noise contributions cannot be attributed exclusively to a single part, but it is correct to refer to them as system noises. Several examples taken from experimental data are presented and discussed and a method to determine the dielectric noise introduced by the interconnection and the detector is described. The concept of
Equivalent Noise Energy
is formalized revealing how it is useful to compare systems employing detectors made with different semiconductors and eventually affected by charge trapping. The analysis is developed assuming semiconductor detectors but can be easily applied to system using other types of radiation detectors.
... The shaping circuit [20] receives the signals produced by the active calorimeter material and generates a typical pulse shape in its output. Among the benefits of such an operation are to increase the signal-to-noise ratio and have a standard pulse (with controlled width, amplitude, and shape) to better cope with the analog-to-digital converter (ADC) specifications (sampling frequency, input signal range, etc.) [21]. After signal acquisition and digitization, at the trigger or analysis level, the digital information from the calorimeter cells may be used to recover the sampled energy amplitude and estimate the particle time-of-flight by using specific energy estimation strategies [22]. ...
Calorimeters play an important role in high-energy physics
experiments. Their design includes electronic instrumentation, signal processing chain, computing infrastructure, and also a good understanding of their response to particle showers produced by the interaction of incoming particles. This is usually supported by full simulation frameworks developed for specific experiments so that their access is restricted to the collaboration members only. Such restrictions limit the general-purpose developments that aim to propose innovative approaches to signal processing, which may include machine learning and advanced stochastic signal processing models. This work presents the Lorenzetti Showers, a general-purpose framework that mainly targets supporting novel signal reconstruction and triggering strategies using segmented calorimeter information. This framework fully incorporates developments down to the signal processing chain level (signal shaping, energy estimation, and noise mitigation techniques) to allow advanced signal processing approaches in modern calorimetry and triggering systems. The developed framework is flexible enough to be extended in different directions. For instance, it can become a tool for the phenomenology community to go beyond the usual detector design and physics process generation approaches.
https://authors.elsevier.com/a/1gX3e2OInn%7EDa
... A test pulse capacitance C inj has been implemented on-chip to inject a known charge at the input of the CSA to evaluate the performance of the readout chain. The shaper performs correlated-doublesampling (CDS), reducing the low-frequency and kT/C noise introduced by the synchronous reset mechanism [8]. In order to achieve high framerates, a sample-and-hold channel buffer is necessary to allow integrate-while-read operation. ...
... The shaper performs Correlated-Double-Sampling (CDS), reducing the low-frequency and kT/C noise introduced by the synchronous reset mechanism [4]. In order to achieve high framerates, a sample-and-hold channel buffer is necessary to allow integrate-while-read operation. ...
... • " f parallel" noise which arises from thermal fluctuations in the dielectric components such as the circuit boards and wire carrier boards. Upon integration on the input capacitance this noise acts as a series 1/ f noise [21]. By design, this noise is much lower than other sources. ...
... The ENC is defined as the number of instantaneously collected electrons required so that their peak ADC count is equal to the root mean square (RMS) of the noise measured, also in the units of ADC counts. The ENC from the noise sources listed above can be approximated as [21,22]: ...
... A 2 =0.9 and A 3 =1.0 [21]. ...
The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.
The operation of large arrays of silicon photomultipliers (SiPMs) in tanks of noble liquids requires low-noise, low-power front-end amplifiers, able to operate reliably in the cryogenic environment. A suitable amplifier needs to be paired with a proper SiPM ganging scheme, meaning the series/parallel combination of SiPMs at its input. This article presents a simple model to estimate the ganging scheme that gives the best signal-to-noise ratio (S/N) once the basic electrical characteristics of the SiPM and amplifier are known. To prove the validity of the model, we used an amplifier based on discrete components, which achieves a white voltage noise in the 0.25–0.37 nV/
$\surd $
Hz range at liquid nitrogen temperature, while drawing 2–5 mW of power. Combined with the optimal ganging scheme obtained with the model, the amplifier demonstrated excellent single photon sensitivity up to
$96\,\,6 \times 6$
mm2 SiPMs (total area 34.6 cm2, S/N
$\simeq ~8$
–11). The measured results are in a good match with calculated values, predicting the possibility of achieving a clear separation of photoelectron peaks also with larger areas.
In the quest to study the fundamental nature of matter and the universe, high-energy physics (HEP) experiments often operate in extreme conditions that lie well outside the standard operating range of integrated circuits (ICs). Two prominent examples of such extreme environments are 1) the irradiation levels experienced at high luminosity colliders and 2) operation at cryogenic temperatures [1]. Cryogenic electronics is a broad term that encompasses circuits operating at temperatures below the standard operating limit (−55 °C in the case of military grade electronics), all of the way down to millikelvin, as in the case of superconducting circuits. Cryogenic circuits have a long history [2] and have found applications in a broad spectrum of applications, such as infrared focal plane arrays, positron emission tomography, and quantum science. While CMOS circuits have been reliably operated at deep-cryogenic temperatures (< 4.2 K), this article focuses on applications down to liquid nitrogen (77 K) and provides an overview of the design considerations, benefits, and unique challenges pertaining to cryogenic CMOS ICs for large HEP experiments.
In very-high-spatial-resolution gamma-ray imaging applications, such as preclinical PET and SPECT, estimation of 3D interaction location inside the detector crystal can be used to minimize parallax error in the imaging system. In this work, we investigate the effect of bias voltage setting on depth-of-interaction (DOI) estimates for a semiconductor detector with a double-sided strip geometry. We first examine the statistical properties of the signals and develop expressions for likelihoods for given gamma-ray interaction positions. We use Fisher Information to quantify how well (in terms of variance) the measured signals can be used for DOI estimation with different bias-voltage settings. We performed measurements of detector response versus 3D position as a function of applied bias voltage by scanning with highly collimated synchrotron radiation at the Advanced Photon Source at Argonne National Laboratory. Experimental and theoretical results show that the optimum bias setting depends on whether or not the estimated event position will include the depth of interaction. We also found that for this detector geometry, the z-resolution changes with depth.
Discrete-time filters represent a promising solution for pulse-processing in high-energy physics experiments due to their flexibility, reliability, and their capability to synthesize weighting functions with virtually any shape. One of the major concerns when designing one of these filters is to calculate the filter parameters that maximize the signal-to-noise ratio. The classic way to address this problem is to perform the noise analysis using a continuous-time domain approach based on the weighting function concept. However, when addressing the problem from an inadequate time domain, the analysis is not insightful and the resulting expressions are complex and difficult to use for design purposes. In this work, a mathematical framework for a design-oriented analysis of discrete-time filters in the discrete-time domain is presented. This analysis is based on treating the sampled noise as a discrete-time signal, which can be manipulated to obtain a closed-form expression for the front-end noise, suitable for computer automatic evaluation and filter optimization procedures. An example of the optimum filter formulation and computation is presented, in addition to several conclusions about optimum digital filtering.
We present an Application Specific Integrated Circuit (ASIC) for high resolution X-ray spectrometers (XRS) in radiation harsh environment (such as Jovian system). The ASIC was designed to read out signals from low resistivity pixelated Silicon-Drift-Detectors (SDD) to ensure radiation hardness. The readout is done by wire-bonding the anodes to the inputs of the ASIC. The ASIC dissipates 32 mW and provides 16 channels of low-noise charge amplification, high-order shaping with baseline stabilization, discrimination, pile-up rejection, and peak detection with analog memory. The readout is sparse and based on a custom low-power tri-stable low-voltage differential signaling digital interface. A unit of 64 SDD pixels, read out by four ASICs, covers an area of 12.8 cm2, and dissipates less than 20 mW/cm2. The ASICs were powered on and irradiated using a beam line with 203 MeV protons, to total doses ranging from 0.25 Mrad to 12 Mrad. Performance degradation due to radiation-induced leakage current was observed to peak around 2 Mrad dose. Critical contributors to the degradation were identified through simulation and measurements, and corresponding circuitry was thus modified to address the issues. Measurements on the radiation-resistant design have shown excellent radiation resistance at total doses ranging from 1 to 8 Mrad.
