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At least 1,693 records · Page 94

Pixel-to-pixel variation on a calibrated PILATUS3-based multi-energy soft x-ray detector

A multi-energy soft x-ray pin-hole camera based on the PILATUS3 100 K x-ray detector has recently been installed on the Madison Symmetric Torus. This photon-counting detector consists of a two-dimensional array of ∼100 000 pixels for which the photon lower-threshold cutoff energy Ec can be independently set for each pixel. This capability allows the measurement of plasma x-ray emissivity in multiple energy ranges with a unique combination of spatial and spectral resolution and the inference of a variety of important plasma properties (e.g., Te, nZ, Zeff). The energy dependence of each pixel is calibrated for the 1.6–6 keV range by scanning individual trimbit settings, while the detector is exposed to fluorescence emission from Ag, In, Mo, Ti, V, and Zr targets. The resulting data for each line are then fit to a characteristic “S-curve” which determines the mapping between the 64 possible trimbit settings for each pixel. The statistical variation of this calibration from pixel-to-pixel was explored, and it was found that the discreteness of trimbit settings results in an effective threshold resolution of ΔE < 100 eV. A separate calibration was performed for the 4–14 keV range, with a resolution of ΔE < 200 eV.

VanMeter, P. (ORCID:0000000244537948)↗

An x-ray optic calibration facility for high energy density diagnostics

A facility to calibrate x-ray imaging optics was built at Lawrence Livermore National Laboratory to support high energy density (HED) and inertial confinement fusion (ICF) diagnostics such as those at the National Ignition Facility and the Sandia Z-Machine. Calibration of the spectral reflectivity and resolution of these x-ray diagnostics enable absolute determination of the x-ray flux and wavelengths generated in the HED and ICF experiments. Measurement of the optic point spread function is used to determine spatial resolution of the optic. This facility was constructed to measure (1) the x-ray reflectivity to ±5% over a spectral range from 5 to 60 keV; (2) point spread functions with a resolution of 50 μm (currently) and 13 μm (future) in the image plane; and (3) optic distance relative to the x-ray source and detector to within ±100 μm in each dimension. Here, this article describes the capabilities of the calibration facility, concept of operations, and initial data from selected x-ray optics.

47 OTHER INSTRUMENTATION↗

Calibration of a versatile multi-energy soft x-ray diagnostic for WEST long pulse plasmas

A compact multi-energy soft x-ray diagnostic is being installed on the W Environment in Steady-state Tokamak (WEST), which was designed and built to test ITER-like tungsten plasma facing components in a long pulse (~1000 s) scenario. The diagnostic consists of a pinhole camera fielded with the PILATUS3 photon-counting Si-based detector (≲100 kpixel). The detector has sensitivity in the range 1.6–30 keV and enables energy discrimination, providing a higher energy resolution than conventional systems with metal foils and diodes with adequate space and time resolution (≲1 cm and 2 ms). The lower-absorption cut-off energy is set independently on each one of the ~100 kpixels, providing a unique opportunity to measure simultaneously the plasma emissivity in multiple energy ranges and deduce a variety of plasma parameters (e.g., T e , n Z , and ΔZ eff ). The energy dependence of each pixel is calibrated here over the range 3–22 keV. The detector is exposed to a variety of monochromatic sources—fluorescence emission from metallic targets—and for each pixel, the lower energy threshold is scanned to calibrate the energy dependence. The data are fit to a responsivity curve (“S-curve”) that determines the mapping between the possible detector settings and the energy response for each pixel. Here, the calibration is performed for three energy ranges: low (2.3–6 keV), medium (4.5–13.5 keV), and high (5.4–21 keV). We determine the achievable energy resolutions for the low, medium, and high energy ranges as 330 eV, 640 eV, and 950 eV, respectively. The main limitation for the energy resolution is found to be the finite width of the S-curve.

47 OTHER INSTRUMENTATION↗

In situ calibration of charged particle spectrometers on the OMEGA Laser Facility using 241 Am and 226 Ra sources

Charged particle spectrometry is a critical diagnostic to study inertial-confinement-fusion plasmas and high energy density plasmas. The OMEGA Laser Facility has two fixed magnetic charged particle spectrometers (CPSs) to measure MeV-ions. In situ calibration of these spectrometers was carried out using 241 Am and 226 Ra alpha emitters. The alpha emission spectrum from the sources was measured independently using surface-barrier detectors (SBDs). The energy dispersion and broadening of the CPS systems were determined by comparing the CPS measured alpha spectrum to that of the SBD. The calibration method significantly constrains the energy dispersion, which was previously obtained through the measurement of charged particle fusion products. Overall, a small shift of 100 keV was observed between previous and the calibration done in this work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. II. Bayesian model calibration

Dynamic shockless compression experiments provide the ability to explore material behavior at extreme pressures but relatively low temperatures. Typically, the data from these types of experiments are interpreted through an analytic method called Lagrangian analysis. Here, in this work, alternative analysis methods are explored using modern statistical methods. Specifically, Bayesian model calibration is applied to a new set of platinum data shocklessly compressed to 570 GPa. Several platinum equation-of-state models are evaluated, including traditional parametric forms as well as a novel non-parametric model concept. The results are compared to those in Paper I obtained by inverse Lagrangian analysis. The comparisons suggest that Bayesian calibration is not only a viable framework for precise quantification of the compression path, but also reveals insights pertaining to trade-offs surrounding model form selection, sensitivities of the relevant experimental uncertainties, and assumptions and limitations within Lagrangian analysis. The non-parametric model method, in particular, is found to give precise unbiased results and is expected to be useful over a wide range of applications. The calibration results in estimates of the platinum principal isentrope over the full range of experimental pressures to a standard error of 1.6%, which extends the results from Paper I while maintaining the high precision required for the platinum pressure standard.

Brown, Justin Lee↗

Calibration improvements expand filterscope diagnostic use

The filterscope diagnostic on DIII-D utilizes photomultiplier tubes to measure visible light emission from the plasma. The system has undergone a substantial upgrade since previous attempts to cross-calibrate the filterscope with other spectroscopic diagnostics were unsuccessful. The optics now utilize a dichroic mirror to initially split the light at nearly 99% transmission or reflectance for light below or above 550 nm. This allows the system to measure D α emission without degrading visible light emission from the plasma for wavelengths below 550 nm (to measure D β , D γ , W–I, C-III, etc.). Additional optimization of the optical components and calibration techniques reduce the error in the signal up to 10% in some channels compared to previous methods. Cross-calibration measurements with two other high resolution spectroscopic diagnostics now show excellent agreement for the first time. This expands the capabilities of the filterscope system allowing measurement of divertor detachment, emission profiles, edge-localized mode behavior, and plasma–wall interactions. Additionally, it enables direct comparisons against calculations from boundary plasma simulations. These were not possible before.

47 OTHER INSTRUMENTATION↗

Progress toward absolute calibrations of DC x-ray sources from 1 keV to >30 keV for Z diagnostics applications

Numerous x-ray diagnostics at the Z facility, time-resolved and time-integrated, would benefit from a local calibrated x-ray source. For many years, Z has used low-power Manson x-ray sources to provide some characterization information for components of Z diagnostics below 30 keV. More recently, we have acquired TruFocus x-ray sources, which operate at voltages up to 100 kV depending on the anode material and model. These DC sources have demonstrated good stability and repeatability. Absolute calibrations of either sources or detectors usually involve another calibrated detector from another source, which has not been readily available locally. Therefore, we have adopted the strategy of characterizing a sensitive semiconductor diode detector by controlling or inferring the active volume. This characterized detector is then used to scale the Manson x-ray spectral shape as measured by an Amptek energy-resolving detector. Here, the result agrees well with the modeled source spectrum. We can apply this technique to the TruFocus as well.

Crystal spectroscopy↗

Genetic algorithm-based geometry calibration for dynamic compression x-ray diffraction experiments

An important component of dynamic compression x-ray diffraction (XRD) experiment analysis is geometry calibration: proper data interpretation requires knowledge of the precise detector position and orientation and, if the experiment involves a single-crystal sample, knowledge of the lattice orientation. The determination of these parameters in the arbitrary three-dimensional (3D) scattering geometries often present in dynamic compression facilities is challenging, as the associated optimization problem can be highly nonlinear, nonsmooth, and discontinuous. We present a genetic algorithm-based approach for performing dynamic compression XRD calibrations that overcomes these obstacles. We provide details regarding the image processing, algorithm implementation, and open-source software deployment and demonstrate the capability of the approach to calibrate the detector and crystal parameters in 3D geometries. Notably, we demonstrate the solver’s capacity to find the crystal orientation without a priori rotation constraints.

Brown, Nathan P. [Sandia National Laboratories (SN↗

Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at different parameter settings. Using intelligent and adaptive selection of parameters to build the emulator can drastically improve the efficiency of the calibration process. The article proposes a sequential framework with a novel criterion for parameter selection that targets learning the posterior density of the parameters. The emergent behavior from this criterion is that exploration happens by selecting parameters in uncertain posterior regions while simultaneously exploitation happens by selecting parameters in regions of high posterior density. Furthermore, the advantages of the proposed method are illustrated using several simulation experiments and a nuclear physics reaction model.

97 MATHEMATICS AND COMPUTING↗

Photo-z outlier self-calibration in weak lensing surveys

Calibrating photometric redshift errors in weak lensing surveys with external data is extremely challenging. In this work, we show that both Gaussian and outlier photo-z parameters can be self-calibrated from the data alone. This comes at no cost for the neutrino masses, curvature and dark energy equation of state w0, but with a 65% degradation when both w0 and wa are varied. We perform a realistic forecast for the Vera Rubin Observatory (VRO) Legacy Survey of Space and Time (LSST) 3× 2 analysis, combining cosmic shear, projected galaxy clustering and galaxy - galaxy lensing. We confirm the importance of marginalizing over photo-z outliers. We examine a subset of internal cross-correlations, dubbed "null correlations", which are usually ignored in 3× 2 analyses. Despite contributing only ~ 10% of the total signal-to-noise, these null correlations improve the constraints on photo-z parameters by up to an order of magnitude. Using the same galaxy sample as sources and lenses dramatically improves the photo-z uncertainties too. Together, these methods add robustness to any claim of detected new Physics, and reduce the statistical errors on cosmology by 15% and 10% respectively. Finally, including CMB lensing from an experiment like Simons Observatory or CMB-S4 improves the cosmological and photo-z posterior constraints by about 10%, and further improves the robustness to systematics. To give intuition on the Fisher forecasts, we examine in detail several toy models that explain the origin of the photo-z self-calibration. Our Fisher code LaSSI (Large-Scale Structure Information), which includes the effect of Gaussian and outlier photo-z, shear multiplicative bias, linear galaxy bias, and extensions to LCDM, is publicly available at \href{https://github.com/EmmanuelSchaan/LaSSI}{https://github.com/EmmanuelSchaan/LaSSI}.

79 ASTRONOMY AND ASTROPHYSICS↗

In-flight polarization angle calibration for LiteBIRD: blind challenge and cosmological implications

We present a demonstration of the in-flight polarization angle calibration for the JAXA/ISAS second strategic large class mission, LiteBIRD, and estimate its impact on the measurement of the tensor-to-scalar ratio parameter, r, using simulated data. We generate a set of simulated sky maps with CMB and polarized foreground emission, and inject instrumental noise and polarization angle offsets to the 22 (partially overlapping) LiteBIRD frequency channels. Our in-flight angle calibration relies on nulling the EB cross correlation of the polarized signal in each channel. This calibration step has been carried out by two independent groups with a blind analysis, allowing an accuracy of the order of a few arc-minutes to be reached on the estimate of the angle offsets. Both the corrected and uncorrected multi-frequency maps are propagated through the foreground cleaning step, with the goal of computing clean CMB maps. We employ two component separation algorithms, the Bayesian-Separation of Components and Residuals Estimate Tool (B-SeCRET), and the Needlet Internal Linear Combination (NILC). We find that the recovered CMB maps obtained with algorithms that do not make any assumptions about the foreground properties, such as NILC, are only mildly affected by the angle miscalibration. However, polarization angle offsets strongly bias results obtained with the parametric fitting method. Once the miscalibration angles are corrected by EB nulling prior to the component separation, both component separation algorithms result in an unbiased estimation of the r parameter. While this work is motivated by the conceptual design study for LiteBIRD, its framework can be broadly applied to any CMB polarization experiment. In particular, the combination of simulation plus blind analysis provides a robust forecast by taking into account not only detector sensitivity but also systematic effects.

79 ASTRONOMY AND ASTROPHYSICS↗

Using AI to predict calibration constants for the central drift chamber in GlueX at Jefferson Lab

The AI for Experimental Controls project team at Jefferson Lab has developed an AI system to control and calibrate a large drift chamber system in near-real time. The AI system will monitor environmental and experimental variables to recommend voltage settings that maintain consistent dE/dx gain and optimal resolution throughout the experiment. At present, calibrations are performed after data have been recorded and require a considerable amount of time and attention from experts. The calibrations currently require multiple iterations and depend on accurate tracking information. Our approach uses environmental data, such as atmospheric pressure and gas temperature, and beam conditions, such as the flux of incident particles, as inputs to a Gaussian Process Regression (GPR) model. For the data taken during the GlueX 2020 run period, the GPR is able to predict the existing gain correction factors to within 3.5%. This talk will briefly describe the development, testing, and future plans for this system at Jefferson Lab.

Jeske, Torri↗

Calibration and validation of a spar-type floating offshore wind turbine model using the FAST dynamic simulation tool

In this study, high-quality computer simulations are required when designing floating wind turbines because of the complex dynamic responses that are inherent with a high number of degrees of freedom and variable metocean conditions. In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50 th scale in a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states. Wave basin tests with the spar attached to a scale model of the NREL 5-megawatt reference wind turbine were performed at the Maritime Research Institute Netherlands under the DeepCwind project. This project included free-decay tests, tests with steady or turbulent wind and still water (both periodic and irregular waves with no wind), and combined wind/wave tests. The resulting data from the 1/50th model was scaled using Froude scaling to full size and used to calibrate and validate a full-size simulated model in FAST. Results of the model calibration and validation include successes, subtleties, and limitations of both wave basin testing and FAST modeling capabilities.

17 WIND ENERGY↗

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

In this paper, we describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Long-term calibration and validation of stability of the Auger Engineering Radio Array using the diffuse Galactic radio emission

The Auger Engineering Radio Array (AERA) measures radio emission from high-energy extensive air showers. Consisting of 153 autonomous radio-detector stations spread over 17 km^2, it detects radio waves in the frequency range of 30 to 80 MHz. Accurate characterization of the detector response is crucial for proper interpretation of the collected data. Previously, this was achieved through laboratory measurements of the analog chain and simulations and measurements of the antenna's directional response. In this paper, we perform an absolute calibration using the continuously monitored sidereal modulation of the diffuse Galactic radio emission. Calibration is done by comparing the average frequency spectra recorded by the stations with predictions from seven different models of the full radio sky, accounting for the system response, which includes the antenna, filters, and amplifiers. The analysis of the calibration constants over a period of seven years shows no relevant and no significant ageing effect in the AERA antennas. This result confirms the long-term stability of the detector stations and demonstrates the possibility for a radio detector to effectively monitor ageing effects of other detectors operating over extended periods.

Antennas↗

Cryogenic single-port calibration for superconducting microwave resonator measurements

Superconducting circuit testing and materials loss characterization requires robust and reliable methods for the extraction of internal and coupling quality factors of microwave resonators. Additionally, a common method, imposed by limitations on the device design or experimental configuration, is the single-port reflection geometry, i.e. reflection-mode. However, impedance mismatches in cryogenic systems must be accounted for through calibration of the measurement chain while it is at low temperatures. In this paper, we demonstrate a data-based, single-port calibration using commercial microwave standards and a vector network analyzer with samples at millikelvin temperature in a dilution refrigerator, making this method useful for measurements of quantum phenomena. Finally, we cross reference our data-based, single-port calibration and reflection measurement with over-coupled 2D- and 3D-resonators against well established two-port techniques corroborating the validity of our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Calibrating Bayesian generative machine learning for Bayesiamplification

Recently, combinations of generative and Bayesian deep learning have been introduced in particle physics for both fast detector simulation and inference tasks. These neural networks aim to quantify the uncertainty on the generated distribution originating from limited training statistics. The interpretation of a distribution-wide uncertainty however remains ill-defined. We show a clear scheme for quantifying the calibration of Bayesian generative machine learning models. For a Continuous Normalizing Flow applied to a low-dimensional toy example, we evaluate the calibration of Bayesian uncertainties from either a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights, to gauge their behaviour on unsteady distribution edges. Well calibrated uncertainties can then be used to roughly estimate the number of uncorrelated truth samples that are equivalent to the generated sample and clearly indicate data amplification for smooth features of the distribution.

97 MATHEMATICS AND COMPUTING↗

Validation of selection function, sample contamination and mass calibration in galaxy cluster samples

ABSTRACT We construct and validate the selection function of the MARD-Y3 galaxy cluster sample. This sample was selected through optical follow-up of the 2nd ROSAT faint source catalogue with Dark Energy Survey year 3 data. The selection function is modelled by combining an empirically constructed X-ray selection function with an incompleteness model for the optical follow-up. We validate the joint selection function by testing the consistency of the constraints on the X-ray flux–mass and richness–mass scaling relation parameters derived from different sources of mass information: (1) cross-calibration using South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) clusters, (2) calibration using number counts in X-ray, in optical and in both X-ray and optical while marginalizing over cosmological parameters, and (3) other published analyses. We find that the constraints on the scaling relation from the number counts and SPT-SZ cross-calibration agree, indicating that our modelling of the selection function is adequate. Furthermore, we apply a largely cosmology independent method to validate selection functions via the computation of the probability of finding each cluster in the SPT-SZ sample in the MARD-Y3 sample and vice versa. This test reveals no clear evidence for MARD-Y3 contamination, SPT-SZ incompleteness or outlier fraction. Finally, we discuss the prospects of the techniques presented here to limit systematic selection effects in future cluster cosmological studies.

79 ASTRONOMY AND ASTROPHYSICS↗