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This course will present an overview of measurement processes, and statistical evaluation of both measurements and equipment performance. In addition, this course will address some of the actions to take to minimize the sources of error in count room operations. This course will prepare the student with the skills necessary for RCT qualification.
A multi-detector γ-ray spectroscopy system including 3 high-purity germanium (HPGe) detectors has been developed at the Nuclear Counting Facility at Lawrence Livermore National Laboratory. This system operates not only in conventional singles γ-ray detection mode but also incorporates features like coincidence and anti-coincidence techniques. These advanced detection modes can significantly enhance the system’s sensitivity, making it a powerful tool for isotope identification and quantification, especially for complex samples with high background and overlapping peaks. In this re port, we present a comprehensive performance characterization of the Multi-Coincident Bismuth Oxide Spectrometer (MCBOS) using a variety of sample types, including 60 Co, 48 Sc, and mixed fission product samples. Each sample provides unique tests for the MCBOS capabilities. Additionally, a GEANT4 model of the MCBOS has been generated to aid with the characterization of the system.
In 1973, SRNL acquired the armor plate from the USS Antietam (CV-36) and began planning the Underground Counting Facility (UCF). • The UCF was constructed in 1982
BACKGROUND: Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors’ limited areas. OBJECTIVE: This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems. METHODS: Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT. RESULTS: Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method. CONCLUSION: Apart from the computational cost, we concluded that the method was easy to implement and robust.
Tassel counts provide valuable information related to flowering and yield prediction in maize, but are expensive and time-consuming to acquire via traditional manual approaches. High-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs), coupled with advanced machine learning approaches, including deep learning (DL), provides a new capability for monitoring flowering. In this article, three state-of-the-art DL techniques, CenterNet based on point annotation, task-aware spatial disentanglement (TSD), and detecting objects with recursive feature pyramids and switchable atrous convolution (DetectoRS) based on bounding box annotation, are modified to improve their performance for this application and evaluated for tassel detection relative to Tasselnetv2+. The dataset for the experiments is comprised of RGB images of maize tassels from plant breeding experiments, which vary in size, complexity, and overlap. Results show that the point annotations are more accurate and simpler to acquire than the bounding boxes, and bounding box-based approaches are more sensitive to the size of the bounding boxes and background than point-based approaches. Overall, CenterNet has high accuracy in comparison to the other techniques, but DetectoRS can better detect early-stage tassels. The results for these experiments were more robust than Tasselnetv2+, which is sensitive to the number of tassels in the image.
Most lidars used for cloud observations have the range resolution of about 10 m, so they are incapable of resolving submeter-scale processes that are crucial to cloud evolution. This article describes a prototype of a ground-based, vertically pointing, time-gated, time-correlated single-photon-counting lidar (referred to as the T2 lidar) developed to explore atmospheric clouds at range resolution two orders of magnitude finer than traditional atmospheric lidars. The T2 lidar emits green-light pulses (532 nm) at a repetition rate of 20.6 kHz and a pulse width of ∼650 ps, which enables the observation of aerosol and cloud layers at heights from a few hundred meters to 7.28 km above the ground level at range resolution down to 10 cm. In addition, a digital delay pulse generator controls the detector to only receive photons for a short period after each laser pulse. This time-gated technique blocks photons arriving from regions outside the target zone, thus significantly reducing the noise level and allowing observation even inside clouds. Initial observations show that the T2 lidar can detect sharp cloud boundaries and fine structures near the cloud base. Such refined measurements of cloud structure could lead to an improved understanding of microphysical processes such as droplet activation, entrainment and mixing, and precipitation.
Abstract We show the improvement to cosmological constraints from galaxy cluster surveys with the addition of cosmic microwave background (CMB)-cluster lensing data. We explore the cosmological implications of adding mass information from the 3.1 σ detection of gravitational lensing of the CMB by galaxy clusters to the Sunyaev–Zel’dovich (SZ) selected galaxy cluster sample from the 2500 deg 2 SPT-SZ survey and targeted optical and X-ray follow-up data. In the ΛCDM model, the combination of the cluster sample with the Planck power spectrum measurements prefers σ 8 Ω m / 0.3 0.5 = 0.831 ± 0.020 . Adding the cluster data reduces the uncertainty on this quantity by a factor of 1.4, which is unchanged whether the 3.1 σ CMB-cluster lensing measurement is included or not. We then forecast the impact of CMB-cluster lensing measurements with future cluster catalogs. Adding CMB-cluster lensing measurements to the SZ cluster catalog of the ongoing SPT-3G survey is expected to improve the expected constraint on the dark energy equation of state w by a factor of 1.3 to σ ( w ) = 0.19. We find the largest improvements from CMB-cluster lensing measurements to be for σ 8 , where adding CMB-cluster lensing data to the cluster number counts reduces the expected uncertainty on σ 8 by respective factors of 2.4 and 3.6 for SPT-3G and CMB-S4.
Abstract We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z = 0.1 to 0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey. In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab , which enables the rapid, precise prediction of CiC for any HOD model available in halotools . This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in z ∼ 0.15 samples with limiting absolute magnitude M r < −20.0 and M r < −20.5 samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter M r < −21.0 sample at z ∼ 0.25 (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at z ∼ 0.15. We provide our constraints for each threshold sample’s characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.
We present a supervised learning method to perform photoelectron counting in PMT- based dark matter search experiments and show that it is possible to achieve better accuracy and precision compared to standard Bayesian statistics methods.
A method for measuring mRNA copies in intact bacterial cells by fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) is presented. Unlike conventional single molecule FISH, where the presence of a transcript is determined by fluorescence intensity, fliFISH relies on On-Off duty cycles of photo-switching dyes to set a predetermined threshold for distinguishing true signals from background noise. The method provides a quantitative approach for detecting and counting true mRNA copies and rejecting false signals with high accuracy.
The purpose of a nondestructive assay is to accurately verify the declared mass of special nuclear material (SNM) samples in a limited amount of time. One measurement modality is neutron multiplicity counting (NMC), which relates time-correlated neutron detection rates to the mass of SNM present. Traditional theory assumes point-like sources, which can be ill-posed for kilogram-quantity, bulk samples. Recent theory was developed to improve NMC accuracy for non-point-like samples. This work preliminarily examines the theory with measured data. The OSCAR prototype (a 3-by-4 array of 5.08-cm-thick, 5.08-cm-diameter trans-stilbene organic scintillators) measures configurations of 29.41-49.00 kg of highly enriched uranium (93wt% 235 U). Adjusted factorial moments for the emitted neutron multiplicity distributions are used to account for the shape and type of SNM being measured.
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We study the superconfomal index of four-dimensional toric quiver gauge theories using a Bethe Ansatz approach recently applied by Benini and Milan. Relying on a particular set of solutions to the corresponding Bethe Ansatz equations we evaluate the superconformal index in the large N limit, thus avoiding to take any Cardy-like limit. We present explicit results for theories arising as a stack of N D 3 branes at the tip of toric Calabi-Yau cones: the conifold theory, the suspended pinch point gauge theory, the first del Pezzo theory and Y p,q quiver gauge theories. For a suitable choice of the chemical potentials of the theory we find agreement with predictions made for the same theories in the Cardy-like limit. However, for other regions of the domain of chemical potentials the superconformal index is modified and consequently the associated black hole entropy receives corrections. We work out explicitly the simple case of the conifold theory.
We study the large N expansion of twisted partition functions of 3d N = 2 superconformal field theories arising from N M5-branes wrapped on a hyperbolic 3- manifold, M 3 . Via the 3d-3d correspondence, the partition functions of these 3d N = 2 superconformal field theories are related to simple topological invariants on the 3-manifold. The partition functions can be expressed using only classical and one-loop perturbative invariants of PSL(N, C) Chern-Simons theory around irreducible flat connections on M 3 . Using mathematical results on the asymptotics of the invariants, we compute the twisted partition functions in the large N limit including perturbative corrections to all orders in 1/N . Surprisingly, the perturbative expansion terminates at finite order. The leading part of the partition function is of order N 3 and agrees with the Bekenstein-Hawking entropy of the dual black holes. The subleading part, in particular the log N -terms in the field theory partition function is found to precisely match the one-loop quantum corrections in the dual eleven dimensional supergravity. The field theory results of other terms in 1/N provide a stringent prediction for higher order corrections in the holographic dual, which is M-theory.
Transition-edge sensor microcalorimeters have found success as X-ray detectors at synchrotron light-sources, due to a unique combination of high collecting area and good energy resolution. However, the upcoming generation of free-electron lasers (FELs), such as the Linac Coherent Light Source II, is designed to deliver more than 10 10 photons in a 100 fs pulse at a 100 kHz rate, potentially leading to severe pulse-pileup issues. Here we will demonstrate that, for most relevant science cases, it is possible to mitigate pulse pile-up using simple X-ray filters in a way that takes advantage of the substantial increase in X-ray flux at modern FELs.