Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userTeledyne H1RG, H2RG, and H4RG Noise Generator
36
0
0.0
(
0
)
Authors
Bernard J. Rauscher
Ask ChatGPT about the research
No Arabic abstract
This paper describes the near-infrared detector system noise generator (NG) that we wrote for the James Webb Space Telescope (JWST) Near Infrared Spectrograph (NIRSpec). NG simulates many important noise components including; (1) white read noise, (2) residual bias drifts, (3) pink $1/f$ noise, (4) alternating column noise, and (5) picture frame noise. By adjusting the input parameters, NG can simulate noise for Teledynes H1RG, H2RG, and H4RG detectors with and without Teledynes SIDECAR ASIC IR array controller. NG can be used as a starting point for simulating astronomical scenes by adding dark current, scattered light, and astronomical sources into the results from NG. NG is written in Python-3.4. The source code is freely available for download from http://jwst.nasa.gov/publications.html.
rate research
Read More
The Wide-Field Infrared Survey Telescope (WFIRST) will answer fundamental questions about the evolution of dark energy over time and expand the catalog of known exoplanets into new regions of parameter space. Using a Hubble-sized mirror and 18 newly developed HgCdTe 4K x 4K photodiode arrays (H4RG-10), WFIRST will measure the positions and shapes of hundreds of millions of galaxies, the light curves of thousands of supernovae, and the microlensing signals of over a thousand exoplanets toward the bulge of the Galaxy. These measurements require unprecedented sensitivity and characterization of the Wide Field Instrument (WFI), particularly its detectors. The WFIRST project undertook an extensive detector development program to create focal plane arrays that meet these science requirements. These prototype detectors have been characterized and their performance demonstrated in a relevant space-like environment (thermal vacuum, vibration, acoustic, and radiation testing), advancing the H4RG-10s technology readiness level (TRL) to TRL-6. We present the performance characteristics of these TRL-6 demonstration devices.
The brighter-fatter (BF) effect is a phenomenon (originally discovered in charge coupled devices) in which the size of the detector point spread function (PSF) increases with brightness. We present, for the first time, laboratory measurements demonstrating the existence of the effect in a Hawaii-2RG HgCdTe near infrared (NIR) detector. We use the Precision Projector Laboratory, a JPL facility for emulating astronomical observations with UV/VIS/NIR detectors, to project about 17,000 point sources onto the detector to stimulate the effect. After calibrating the detector for nonlinearity with flat-fields, we find evidence that charge is nonlinearly shifted from bright pixels to neighboring pixels during exposures of point sources, consistent with the existence of a BF-type effect. The Wide Field Infrared Survey Telescope (WFIRST) by NASA will use similar detectors to measure weak gravitational lensing from the shapes of hundreds of million of galaxies in the NIR. The WFIRST PSF size must be calibrated to approximately 0.1 percent to avoid biased inferences of dark matter and dark energy parameters; therefore further study and calibration of the BF effect in realistic images will be crucial.
In this research note, we present linemake, an open-source atomic and molecular line list generator. Rather than a replacement for a number of well-established atomic and molecular spectral databases, linemake aims to be a lightweight, easy-to-use tool to generate formatted and curated lists suitable for spectral synthesis work. We encourage users of linemake to understand the sources of their transition data and cite them as appropriate in published work. We provide the code, line database, and an extensive list of literature references in a GitHub repository (https://github.com/vmplacco/linemake), which will be updated regularly as new data become available.
We introduce a software generator for a class of emph{colored} (self-correlated) and emph{non-Gaussian} noise, whose statistics and spectrum depend upon only two parameters, $q$ and $tau$. Inspired by Tsallis nonextensive formulation of statistical physics, this so-called $q$-distribution is a handy source of self-correlated noise for a large variety of applications. The $q$-noise---which tends smoothly for $q=1$ to Ornstein--Uhlenbeck noise with autocorrelation $tau$---is generated via a stochastic differential equation, using the Heun method (a second order Runge--Kutta type integration scheme). The algorithm is implemented as a stand-alone library in texttt{c++}, available as open source in the texttt{Github} repository. The noises statistics can be chosen at will, by varying only parameter $q$: it has compact support for $q<1$ (sub-Gaussian regime) and finite variance up to $q=5/3$ (supra-Gaussian regime). Once $q$ has been fixed, the noises autocorrelation can be tuned up independently by means of parameter $tau$. This software provides a tool for modeling a large variety of real-world noise types, and is suitable to study the effects of correlation and deviations from the normal distribution in systems of stochastic differential equations which may be relevant for a wide variety of technological applications, as well as for the understanding of situations of biological interest. Applications illustrating how the noise statistics affects the response of a variety of nonlinear systems are briefly discussed. In many of these examples, the systems response turns out to be optimal for some $q eq1$.
We introduce the concepts of Poisson brackets for classical noise, and of canonically conjugate Wiener processes (symplectic noise). Phase space diffusions driven by these processes are considered and the general form of a stochastic process preserving the full (system and noise) Poisson structure is obtained. We show that, once the classical stochastic model is required to preserve the joint system and noise Poisson bracket, it has much in common with quantum markovian models.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
