We develop a novel algorithm for characterizing Deep Sub-Electron Read Noise (DSERN) image sensors. This algorithm is able to simultaneously compute maximum likelihood estimates of quanta exposure, ...conversion gain, bias, and read noise of DSERN pixels from a single sample of data with less uncertainty than the traditional photon transfer method. Methods for estimating the starting point of the algorithm are also provided to allow for automated analysis. Demonstration through Monte Carlo numerical experiments are carried out to show the effectiveness of the proposed technique. In support of the reproducible research effort, all of the simulation and analysis tools developed are available on the MathWorks file exchange 1.
The Photon Counting Histogram Expectation Maximization (PCH-EM) algorithm has recently been reported as a candidate method for the characterization of Deep Sub-Electron Read Noise (DSERN) image ...sensors. This work describes a comprehensive demonstration of the PCH-EM algorithm applied to a DSERN capable quanta image sensor. The results show that PCH-EM is able to characterize DSERN pixels for a large span of quanta exposure and read noise values. The per-pixel characterization results of the sensor are combined with the proposed Photon Counting Distribution (PCD) model to demonstrate the ability of PCH-EM to predict the ensemble distribution of the device. The agreement between experimental observations and model predictions demonstrates both the applicability of the PCD model in the DSERN regime as well as the ability of the PCH-EM algorithm to accurately estimate the underlying model parameters.
The new neutron time-of-flight facility (n_TOF) has been built at CERN and is now operational. The facility is intended for the measurement of neutron induced cross-sections of relevance to ...Accelerator Driven Systems (ADS) and to fundamental physics. Neutrons are produced by spallation of the
20
GeV/c
proton beam, delivered by the Proton Synchrotron (PS), on a massive target of pure lead. A measuring station is placed at
≈185
m
from the neutron producing target, allowing high-resolution measurements. The facility was successfully commissioned with two campaigns of measurements, in November 2000 and April 2001. The main interest was concentrated in the physical parameters of the installation (neutron fluence and resolution function), along with the target behavior and various safety-related aspects. These measurements confirmed the expectations from Monte Carlo simulations of the facility, thus allowing to initiate the foreseen physics program.
A new experimental approach to the famous problem of the anomalously slow Gamow-Teller (GT) transitions in the beta decay of the A=14 multiplet is presented. The GT strength distributions to excited ...states in 14C and 14O were studied in high-resolution (d,2He) and (3He,t) charge-exchange reactions on 14N. No-core shell-model calculations capable of reproducing the suppression of the beta decays predict a selective excitation of Jpi=2+ states. The experimental confirmation represents a validation of the assumptions about the underlying structure of the 14N ground state wave function. However, the fragmentation of the GT strength over three 2+ final states remains a fundamental issue not explained by the present no-core shell model using a 6homega model space, suggesting possibly the need to include cluster structure in these light nuclei in a consistent way.
Working from a Poisson-Gaussian noise model, a multisample extension of the photon counting histogram expectation-maximization (PCH-EM) algorithm is derived as a general-purpose alternative to the ...photon transfer (PT) method. This algorithm is derived from the same model, requires the same experimental data, and estimates the same sensor performance parameters as the time-tested PT method, all while obtaining lower uncertainty estimates. It is shown that as read noise becomes large, multiple data samples are necessary to capture enough information about the parameters of a device under test, justifying the need for a multisample extension. An estimation procedure is devised consisting of initial PT characterization followed by repeated iteration of PCH-EM to demonstrate the improvement in estimating uncertainty achievable with PCH-EM, particularly in the regime of deep subelectron read noise (DSERN). A statistical argument based on the information theoretic concept of sufficiency is formulated to explain how PT data reduction procedures discard information contained in raw sensor data, thus explaining why the proposed algorithm is able to obtain lower uncertainty estimates of key sensor performance parameters, such as read noise and conversion gain. Experimental data captured from a CMOS quanta image sensor with DSERN are then used to demonstrate the algorithm's usage and validate the underlying theory and statistical model. In support of the reproducible research effort, the code associated with this work can be obtained on the MathWorks file exchange (FEX) (Hendrickson et al., 2024).
The modulation transfer function (MTF) describes how an imaging system modifies the spatial frequency content of a scene. Many performance metrics and specification requirements are strongly ...dependent on the MTF as it provides information on the limiting resolution of the imaging
system. In this correspondence we will identify potential issues that can contribute uncertainty or bias into the MTF measurement, and suggest best practices to avoid such issues. Beginning with a full 2D derivation of the tilted edge measurement technique, we identify potential areas where
differences between laboratories can occur due to the setup, imaging system, measurement procedure, or the measurement processing. We show specific examples of how the system's nonuniformity (including defective pixels) can affect the observed MTF. Additionally, we show examples of target
to target variation and the effects of dynamic range. A summary table is provided on best practices to reduce the impact of the identified potential areas of difference. In support of the reproducible research effort, the Matlab functions associated with this work can be found on the Mathworks
file exchange 1.
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