A comparative study of methods to estimate conversion gain in sub-electron and multi-electron read noise regimes

Of all sensor performance parameters, the conversion gain is arguably the most fundamental as it describes the conversion of photoelectrons at the sensor input into digital numbers at the output. Due in part to the emergence of deep sub-electron read noise image sensors in recent years, the literature has seen a resurgence of papers detailing methods for estimating conversion gain in both the sub-electron and multi-electron read noise regimes. Each of the proposed methods work from identical noise models but nevertheless yield diverse procedures for estimating conversion gain. Here, an overview of the proposed methods is provided along with an investigation into their assumptions, uncertainty, and measurement requirements. A sensitivity analysis is conducted using synthetic data for a variety of different sensor configurations. Specifically, the dependence of the conversion gain estimate uncertainty on the magnitude of read noise and quanta exposure is explored. Guidance into the trade-offs between the different methods is provided so that experimenters understand which method is optimal for their application. In support of the reproducible research effort, the MATLAB functions associated with this work can be found on the Mathworks file exchange.Comment: 14 pages, 7 figures, SPIE DCS 202

Photon Counting Histogram Expectation Maximization Algorithm for Characterization of Deep Sub-Electron Read Noise Sensors

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].Comment: 8 pages, 6 figure

Impact of Gene-Gender Effects of Adrenergic Polymorphisms on Hypothalamic-Pituitary-Adrenal Axis Activity in Depressed Patients

Objective: There is overwhelming evidence that activation of the hypothalamic-pituitary-adrenal (HPA) system plays a major role in depression and cardiovascular disease in genetically susceptible individuals. We hypothesized that due to the multiple interactions between the sympathetic and the HPA systems via adrenoceptors, polymorphisms in these genes could have an impact on HPA axis activity in major depression. Methods: Using the dexamethasone/corticotrophin-releasing hormone (DEX/CRH) test, we investigated the association of alpha 2-adrenoceptor (ADRA2A -1291C -> G) and the beta 2-adrenoceptor gene (ADRB2 Arg16Gly) in 189 patients with major depression during the acute state of the disease and after remission. Results: Male ADRA2A -1291G allele homozygotes showed significant pretreatment HPA axis hyperactivity, with increased adrenocorticotropin (ACTH; F = 4.9, d.f. = 2, p = 0.009) and cortisol responses (F = 6.4, d.f. = 2, p = 0.003). In contrast, female ADRB2 Arg/Arg homozygotes had increased pretreatment ACTH (F = 7.17, d.f. = 2, p = 0.001) and cortisol (F = 8.95, d.f. = 2, p = 0.000) levels. Interestingly, in the respective genotypes, the stress hormones remained elevated in the second DEX/CRH test, despite a reduction in depressive symptoms. Conclusions: This study provides evidence that, depending on gender and polymorphisms, there is continuous HPA axis overdrive in a proportion of patients irrespective of the status of depression. Considering the importance of stress hormones for cardiovascular disorders, our data might suggest that these patients are at high risk of comorbidity between depression and cardiovascular disorders. Copyright (c) 2008 S. Karger AG, Base

On the optimal measurement of conversion gain in the presence of dark noise

Working from a model of Gaussian pixel noise, we present and unify over twenty-five years of developments in the statistical analysis of the photon transfer conversion gain measurement. We then study a two-sample estimator of the conversion gain that accounts for the general case of non-negligible dark noise. The moments of this estimator are ill-defined (their integral representations diverge) and so we propose a method for assigning pseudomoments, which are shown to agree with actual sample moments under mild conditions. A definition of optimal sample size pairs for this two-sample estimator is proposed and used to find approximate optimal sample size pairs that allow experimenters to achieve a predetermined measurement uncertainty with as little data as possible. The conditions under which these approximations hold are also discussed. Design and control of experiment procedures are developed and used to optimally estimate a per-pixel conversion gain map of a real image sensor. Experimental results show excellent agreement with theoretical predictions and are backed up with Monte Carlo simulation. The per-pixel conversion gain estimates are then applied in a demonstration of per-pixel read noise estimation of the same image sensor. The results of this work open the door to a comprehensive pixel-level adaptation of the photon transfer method.Comment: 16 pages, 5 figure

AROUSING FEAR IN DENTAL HEALTH EDUCATION * , †

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65851/1/j.1752-7325.1965.tb00484.x.pd

Experimental Verification of PCH-EM Algorithm for Characterizing DSERN Image Sensors

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.Comment: 8 pages, 9 figure

K-band spectroscopy of pre-cataclysmic variables

Aims. There exists now substantial evidence for abundance anomalies in a number of cataclysmic variables (CVs), indicating that the photosphere of the secondary star incorporates thermonuclear processed material. However, the spectral energy distribution in CVs is usually dominated by the radiation produced by the accretion process, severely hindering an investigation of the stellar components. On the other hand, depending on how the secondary star has acquired such material, the above mentioned abundance anomalies could also be present in pre-CVs, i.e. detached white/red dwarf binaries that will eventually evolve into CVs, but have not yet started mass transfer, and therefore allow for an unobstructed view on the secondary star at infrared wavelengths. Methods. We have taken K-band spectroscopy of a sample of 13 pre-CVs in order to examine them for anomalous chemical abundances. In particular, we study the strength of the 12CO and 13CO absorption bands that have been found diminished and enhanced, respectively, in similar studies of CVs. Results. All our systems show CO abundances that are within the range observed for single stars. The weakest 12CO bands with respect to the spectral type are found in the pre-CV BPM 71214, although on a much smaller scale than observed in CVs. Furthermore there is no evidence for enhanced 13CO. Taking into account that our sample is subject to the present observational bias that favours the discovery of young pre-CVs with secondary stars of late spectral types, we can conclude the following: 1) our study provides observational proof that the CO anomalies discovered in certain CVs are not due to any material acquired during the common envelope phase, and 2) if the CO anomalies in certain CVs are not due to accretion of processed material during nova outburst, then the progenitors of these CVs are of a significantly different type than the currently known sample of pre-CVs