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At least 1,081 records · Page 60

Challenges and transformative opportunities in superconductor vortex physics

In superconductors, the motion of vortices introduces unwanted dissipation that is disruptive to applications. Fortunately, material defects can immobilize vortices, acting as vortex pinning centers, which engenders dramatic improvements in superconductor material properties and device operation. This has motivated decades of research into developing methods of tailoring the disorder landscape in superconductors to increase the strength of vortex pinning. Yet, efficacious materials engineering still eludes us. The electromagnetic properties of real (disordered) superconducting materials cannot yet be reliably predicted, such that designing superconductors for applications remains a largely inefficient process of trial and error. This is ultimately due to large gaps in our knowledge of vortex dynamics: the field is challenged by the extremely complex interplay between vortex elasticity, vortex-vortex interactions, and material disorder. Here, we review obstacles and recent successes in understanding and controlling vortex dynamics in superconducting materials and devices. We further identify major open questions and discuss opportunities for transformative research in the field. This includes improving our understanding of vortex creep, determining and reaching the ceiling for the critical current, advanced microscopy to garner accurate structure-property relationships, frontiers in predictive simulations and the benefits of artificial intelligence, as well as controlling and exploiting vortices in quantum information applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A hybrid neural architecture: Online attosecond x-ray characterization

The emergence of high-repetition-rate x-ray free-electron lasers (XFELs), such as SLAC’s LCLS-II, serves as our canonical example for autonomous controls that necessitate high-throughput diagnostics paired with streaming computational pipelines capable of single-shot analysis with extremely low latency. We present the deterministic characterization with an integrated parallelizable hybrid resolver architecture, a hybrid machine learning framework designed for fast, accurate analysis of XFEL diagnostics using angular streaking-based sinogram images. This architecture integrates convolutional neural networks and bidirectional long short-term memory models to denoise input, identify x-ray sub-spike features, and extract sub-spike relative delays with sub-30 attosecond temporal resolution. Deployed on low-latency hardware, it achieves over 10 kHz throughput with 168.3 μs inference latency, indicating scalability to 14 kHz with field-programmable gate array integration. By transforming regression tasks into classification problems and leveraging optimized error encoding, we achieve high precision with low-latency performance that is critical for real-time streaming event selection and experimental control feedback signals. This represents a key development in real-time control pipelines for next-generation autonomous science, generally, and high repetition-rate x-ray experiments in particular.

Accelerator Physics (physics.acc-ph)↗

Augmenting a Simulation Campaign for Hybrid Computer Model and Field Data Experiments

The Kennedy and O’Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its “knobs” (calibration inputs) to best match observations from a real physical/field experiment and correct for any modeling bias (second GP) when predicting under new field conditions (design inputs). There are well-established methods for placement of design inputs for data-efficient planning of a simulation campaign in isolation, that is, without field data: space-filling, or via criterion like minimum integrated mean-squared prediction error (IMSPE). Analogues within the coupled GP KOH framework are mostly absent from the literature. Here, in this study, we derive a closed form IMSPE criterion for sequentially acquiring new simulator data for KOH. We illustrate how acquisitions space-fill in design space, but concentrate in calibration space. Closed form IMSPE precipitates a closed-form gradient for efficient numerical optimization. We demonstrate that our KOH-IMSPE strategy leads to a more efficient simulation campaign on benchmark problems, and conclude with a showcase on an application to equilibrium concentrations of rare earth elements for a liquid–liquid extraction reaction.

97 MATHEMATICS AND COMPUTING↗

THE MASSIVE STAR POPULATION IN M101. I. THE IDENTIFICATION AND SPATIAL DISTRIBUTION OF THE VISUALLY LUMINOUS STARS

An increasing number of non-terminal giant eruptions are being observed by modern supernova and transient surveys. But very little is known about the origin of these giant eruptions and their progenitors, many of which are presumably very massive, evolved stars. Motivated by the small number of progenitors positively associated with these giant eruptions, we have begun a survey of the evolved massive star populations in nearby galaxies. The nearby, nearly face-on, giant spiral M101 is an excellent laboratory for studying a large population of very massive stars. In this paper, we present BVI photometry obtained from archival HST/ACS Wide Field Camera images of M101. We have produced a catalog of luminous stars with photometric errors <10% for V < 24.5 and 50% completeness down to V ∼ 26.5 even in regions of high stellar crowding. Using color and luminosity criteria, we have identified candidate luminous OB-type stars and blue supergiants, yellow supergiants, and red supergiants for future observation. We examine their spatial distributions across the face of M101 and find that the ratio of blue to red supergiants decreases by two orders of magnitude over the radial extent of M101 corresponding to 0.5 dex in metallicity. We discuss the resolved stellar content in the giant star-forming complexes NGC 5458, 5453, 5461, 5451, 5462, and 5449 and discuss their color-magnitude diagrams in conjunction with the spatial distribution of the stars to determine their spatio-temporal formation histories.

79 ASTRONOMY AND ASTROPHYSICS↗

BraggNN : fast X-ray Bragg peak analysis using deep learning

X-ray diffraction based microscopy techniques such as high-energy diffraction microscopy (HEDM) rely on knowledge of the position of diffraction peaks with high precision. These positions are typically computed by fitting the observed intensities in detector data to a theoretical peak shape such as pseudo-Voigt. As experiments become more complex and detector technologies evolve, the computational cost of such peak-shape fitting becomes the biggest hurdle to the rapid analysis required for real-time feedback in experiments. To this end, we propose BraggNN, a deep-learning based method that can determine peak positions much more rapidly than conventional pseudo-Voigt peak fitting. When applied to a test dataset, peak center-of-mass positions obtained from BraggNN deviate less than 0.29 and 0.57 pixels for 75 and 95% of the peaks, respectively, from positions obtained using conventional pseudo-Voigt fitting (Euclidean distance). When applied to a real experimental dataset and using grain positions from near-field HEDM reconstruction as ground-truth, grain positions using BraggNN result in 15% smaller errors compared with those calculated using pseudo-Voigt. Recent advances in deep-learning method implementations and special-purpose model inference accelerators allow BraggNN to deliver enormous performance improvements relative to the conventional method, running, for example, more than 200 times faster on a consumer-class GPU card with out-of-the-box software.

36 MATERIALS SCIENCE↗

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network - that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest-in the sense of electrical distance - from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for realtime operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

distribution service transformer↗

A new open‐path eddy covariance method for nitrous oxide and other trace gases that minimizes temperature corrections

Abstract Low‐power, open‐path gas sensors enable eddy covariance (EC) flux measurements in remote areas without line power. However, open‐path flux measurements are sensitive to fluctuations in air temperature, pressure, and humidity. Laser‐based, open‐path sensors with the needed sensitivity for trace gases like methane (CH 4 ) and nitrous oxide (N 2 O) are impacted by additional spectroscopic effects. Corrections for these effects, especially those related to temperature fluctuations, often exceed the flux of gases, leading to large uncertainties in the associated fluxes. For example, the density and spectroscopic corrections arising from temperature fluctuations can be one or two orders of magnitude greater than background N 2 O fluxes. Consequently, measuring background fluxes with laser‐based, open‐path sensors is extremely challenging, particularly for N 2 O and gases with similar high‐precision requirements. We demonstrate a new laser‐based, open‐path N 2 O sensor and a general approach applicable to other gases that minimizes temperature‐related corrections for EC flux measurements. The method identifies absorption lines with spectroscopic effects in the opposite direction of density effects from temperature and, thus, density and spectroscopic effects nearly cancel one another. The new open‐path N 2 O sensor was tested at a corn ( Zea mays L.) field in Southwestern Michigan, United States. The sensor had an optimal precision of 0.1 ppbv at 10 Hz and power consumption of 50 W. Field trials showed that temperature‐related corrections were 6% of density corrections, reducing EC random errors by 20‐fold compared to previously examined lines. Measured open‐path N 2 O EC fluxes showed excellent agreement with those made with static chambers ( m = 1.0 ± 0.3; r 2 = .96). More generally, we identified absorption lines for CO 2 and CH 4 flux measurements that can reduce the temperature‐related corrections by 10–100 times compared to existing open‐path sensors. The proposed method provides a new direction for future open‐path sensors, facilitating the expansion of accurate EC flux measurements.

47 OTHER INSTRUMENTATION↗

A simplified approach to characterizing a kilovoltage source spectrum for accurate dose computation

Purpose: To investigate and validate the clinical feasibility of using half-value layer (HVL) and peak tube potential (kVp) for characterizing a kilovoltage (kV) source spectrum for the purpose of computing kV x-ray dose accrued from imaging procedures. To use this approach to characterize a Varian Registered-Sign On-Board Imager Registered-Sign (OBI) source and perform experimental validation of a novel in-house hybrid dose computation algorithm for kV x-rays. Methods: We characterized the spectrum of an imaging kV x-ray source using the HVL and the kVp as the sole beam quality identifiers using third-party freeware Spektr to generate the spectra. We studied the sensitivity of our dose computation algorithm to uncertainties in the beam's HVL and kVp by systematically varying these spectral parameters. To validate our approach experimentally, we characterized the spectrum of a Varian Registered-Sign OBI system by measuring the HVL using a Farmer-type Capintec ion chamber (0.06 cc) in air and compared dose calculations using our computationally validated in-house kV dose calculation code to measured percent depth-dose and transverse dose profiles for 80, 100, and 125 kVp open beams in a homogeneous phantom and a heterogeneous phantom comprising tissue, lung, and bone equivalent materials. Results: The sensitivity analysis of the beam quality parameters (i.e., HVL, kVp, and field size) on dose computation accuracy shows that typical measurement uncertainties in the HVL and kVp ({+-}0.2 mm Al and {+-}2 kVp, respectively) source characterization parameters lead to dose computation errors of less than 2%. Furthermore, for an open beam with no added filtration, HVL variations affect dose computation accuracy by less than 1% for a 125 kVp beam when field size is varied from 5 Multiplication-Sign 5 cm{sup 2} to 40 Multiplication-Sign 40 cm{sup 2}. The central axis depth dose calculations and experimental measurements for the 80, 100, and 125 kVp energies agreed within 2% for the homogeneous and heterogeneous block phantoms, and agreement for the transverse dose profiles was within 6%. Conclusions: The HVL and kVp are sufficient for characterizing a kV x-ray source spectrum for accurate dose computation. As these parameters can be easily and accurately measured, they provide for a clinically feasible approach to characterizing a kV energy spectrum to be used for patient specific x-ray dose computations. Furthermore, these results provide experimental validation of our novel hybrid dose computation algorithm.

61 RADIATION PROTECTION AND DOSIMETRY↗

$xy$ Position Reconstruction in DarkSide-50

The DarkSide-50 experiment seeks to directly detect dark matter in a liquid argon time projection chamber. In this dissertation, I present an algorithm of my design that determines the position of particle interactions with the liquid argon. This position reconstruction algorithm will be used by DarkSide-50 to reject backgrounds, particularly backgrounds from radioactive elements on the detector surface. The position reconstruction algorithm functions by constructing light response functions (LRFs) that map locations in the detector to the expected distribution of signal in DarkSide-50's 38 photomultiplier tubes. Accurate LRFs cannot be produced by simulations of DarkSide-50's optics because such simulations are known to be awed. Instead, this algorithm constructs LRFs using an iterative process driven by data. Initial, awed LRFs are produced using simulated events but then used to produce new LRFs from data events. Multiple generations of LRFs are created from data with each generation driven to better satisfy a known feature of the detector: the dominant argon-39 background is uniformly distributed. I also discuss a method of discriminating against surface background as an alternative to the common approach of ducialization. This method considers the di erence in goodnessof- t between the best- t reconstructed position and the best- t position at the detector's surface. I conclude by presenting results on the performance and validity of this algorithm, including some discussion of reconstruction errors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Lagrangian particle tracking applied to high-speed tomographic particle imaging velocimetry

We are investigating the accuracy of Lagrangian analysis of time-resolved, 3D velocity measurements in turbulent flames obtained using high-speed tomographic particle image velocimetry (TPIV). A particle-tracking algorithm was implemented in MATLAB to extract Lagrangian statistics from the velocity fields. The accuracy of Lagrangian statistics depends on the accuracy of the estimated particle trajectories. Errors associated with the spatial and temporal resolutions of high-speed TPIV experiments were evaluated using a direct numerical simulation (DNS) of an isotropic turbulent flow. LPT was then implemented onto TPIV measurements of a laminar counterflow flame. Results calculated with LPT were compared to known results of quantities measured with an Eulerian approach.

47 OTHER INSTRUMENTATION↗

Inspecta Annual Technical Report

Sandia National Laboratories (SNL) is designing and developing an Artificial Intelligence (AI)-enabled smart digital assistant (SDA), Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant). The goal is to provide inspectors an in-field digital assistant that can perform tasks identified as tedious, challenging, or prone to human error. During 2021, we defined the requirements for Inspecta based on reviews of International Atomic Energy Agency (IAEA) publications and interviews with former IAEA inspectors. We then mapped the requirements to current commercial or open-source technical capabilities to provide a development path for an initial Inspecta prototype while highlighting potential research and development tasks. We selected a highimpact inspection task that could be performed by an early Inspecta prototype and are developing the initial architecture, including hardware platform. This paper describes the methodology for selecting an initial task scenario, the first set of Inspecta skills needed to assist with that task scenario and finally the design and development of Inspecta’s architecture and platform.

42 ENGINEERING↗

Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions

Abstract. We apply airborne measurements across three seasons (summer, winter and spring 2017–2018) in a multi-inversion framework to quantify methane emissions from the US Corn Belt and Upper Midwest, a key agricultural and wetland source region. Combing our seasonal results with prior fall values we find that wetlands are the largest regional methane source (32 %, 20 [16–23] Gg/d), while livestock (enteric/manure; 25 %, 15 [14–17] Gg/d) are the largest anthropogenic source. Natural gas/petroleum, waste/landfills, and coal mines collectively make up the remainder. Optimized fluxes improve model agreement with independent datasets within and beyond the study timeframe. Inversions reveal coherent and seasonally dependent spatial errors in the WetCHARTs ensemble mean wetland emissions, with an underestimate for the Prairie Pothole region but an overestimate for Great Lakes coastal wetlands. Wetland extent and emission temperature dependence have the largest influence on prediction accuracy; better representation of coupled soil temperature–hydrology effects is therefore needed. Our optimized regional livestock emissions agree well with the Gridded EPA estimates during spring (to within 7 %) but are ∼ 25 % higher during summer and winter. Spatial analysis further shows good top-down and bottom-up agreement for beef facilities (with mainly enteric emissions) but larger (∼ 30 %) seasonal discrepancies for dairies and hog farms (with > 40 % manure emissions). Findings thus support bottom-up enteric emission estimates but suggest errors for manure; we propose that the latter reflects inadequate treatment of management factors including field application. Overall, our results confirm the importance of intensive animal agriculture for regional methane emissions, implying substantial mitigation opportunities through improved management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancing the Sensitivity to New Physics in the top-antitop Invariant Mass Distribution

We propose selection cuts on the LHC t{bar t} production sample which should enhance the sensitivity to New Physics signals in the study of the t{bar t} invariant mass distribution. We show that selecting events in which the t{bar t} object has little transverse and large longitudinal momentum enlarges the quark-fusion fraction of the sample and therefore increases its sensitivity to New Physics which couples to quarks and not to gluons. We find that systematic error bars play a fundamental role and assume a simple model for them. We check how a non-visible new particle would become visible after the selection cuts enhance its resonance bump. A final realistic analysis should be done by the experimental groups with a correct evaluation of the systematic error bars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy

Purpose: Rating both a lung segmentation algorithm and a deformable image registration (DIR) algorithm for subsequent lung computed tomography (CT) images by different evaluation techniques. Furthermore, investigating the relative performance and the correlation of the different evaluation techniques to address their potential value in a clinical setting. Methods: Two to seven subsequent CT images (69 in total) of 15 lung cancer patients were acquired prior, during, and after radiochemotherapy. Automated lung segmentations were compared to manually adapted contours. DIR between the first and all following CT images was performed with a fast algorithm specialized for lung tissue registration, requiring the lung segmentation as input. DIR results were evaluated based on landmark distances, lung contour metrics, and vector field inconsistencies in different subvolumes defined by eroding the lung contour. Correlations between the results from the three methods were evaluated. Results: Automated lung contour segmentation was satisfactory in 18 cases (26%), failed in 6 cases (9%), and required manual correction in 45 cases (66%). Initial and corrected contours had large overlap but showed strong local deviations. Landmark-based DIR evaluation revealed high accuracy compared to CT resolution with an average error of 2.9 mm. Contour metrics of deformed contours were largely satisfactory. The median vector length of inconsistency vector fields was 0.9 mm in the lung volume and slightly smaller for the eroded volumes. There was no clear correlation between the three evaluation approaches. Conclusions: Automatic lung segmentation remains challenging but can assist the manual delineation process. Proven by three techniques, the inspected DIR algorithm delivers reliable results for the lung CT data sets acquired at different time points. Clinical application of DIR demands a fast DIR evaluation to identify unacceptable results, for instance, by combining different automated DIR evaluation methods.

60 APPLIED LIFE SCIENCES↗

SU-E-T-392: Evaluation of Ion Chamber/film and Log File Based QA to Detect Delivery Errors

Purpose: Ion chamber and film (ICAF) is a method used to verify patient dose prior to treatment. More recently, log file based QA has been shown as an alternative for measurement based QA. In this study, we delivered VMAT plans with and without errors to determine if ICAF and/or log file based QA was able to detect the errors. Methods: Using two VMAT patients, the original treatment plan plus 7 additional plans with delivery errors introduced were generated and delivered. The erroneous plans had gantry, collimator, MLC, gantry and collimator, collimator and MLC, MLC and gantry, and gantry, collimator, and MLC errors. The gantry and collimator errors were off by 4{sup 0} for one of the two arcs. The MLC error introduced was one in which the opening aperture didn’t move throughout the delivery of the field. For each delivery, an ICAF measurement was made as well as a dose comparison based upon log files. Passing criteria to evaluate the plans were ion chamber less and 5% and film 90% of pixels pass the 3mm/3% gamma analysis(GA). For log file analysis 90% of voxels pass the 3mm/3% 3D GA and beam parameters match what was in the plan. Results: Two original plans were delivered and passed both ICAF and log file base QA. Both ICAF and log file QA met the dosimetry criteria on 4 of the 12 erroneous cases analyzed (2 cases were not analyzed). For the log file analysis, all 12 erroneous plans alerted a mismatch in delivery versus what was planned. The 8 plans that didn’t meet criteria all had MLC errors. Conclusion: Our study demonstrates that log file based pre-treatment QA was able to detect small errors that may not be detected using an ICAF and both methods of were able to detect larger delivery errors.

60 APPLIED LIFE SCIENCES↗

FFA@CEBAF beam transport error and tolerance simulation studies

The Continuous Electron Beam Accelerator Facility (CEBAF) is a 12 GeV recirculating electron accelerator at the Thomas Jefferson National Accelerator Facility (JLAB). Major upgrades to the accelerator are being investigated which include a new 650 MeV injection beamline and state-of-the-art fixed-field alternating (FFA) gradient recirculation arcs. The upgrade will extend the energy of the electron beam to over 20 GeV. In this paper, we provide an error and tolerance simulation study of the amended beam optics transport of the existing accelerator tuned for 22 GeV operation. The study is conducted with the particle tracking codes elegant and Bmad in two parts. In the first part, we treat each section of the accelerator (electromagnetic arcs and linacs) modularly with ideal conditions at the beginning. The second part is a pseudo start-to-end (S2E) simulation with accumulated errors propagating from one beamline to the next.

Accelerator Physics↗

An Immersed Boundary method with divergence-free velocity interpolation and force spreading

The Immersed Boundary (IB) method is a mathematical framework for constructing robust numerical methods to study fluid–structure interaction in problems involving an elastic structure immersed in a viscous fluid. The IB formulation uses an Eulerian representation of the fluid and a Lagrangian representation of the structure. The Lagrangian and Eulerian frames are coupled by integral transforms with delta function kernels. The discretized IB equations use approximations to these transforms with regularized delta function kernels to interpolate the fluid velocity to the structure, and to spread structural forces to the fluid. It is well-known that the conventional IB method can suffer from poor volume conservation since the interpolated Lagrangian velocity field is not generally divergence-free, and so this can cause spurious volume changes. In practice, the lack of volume conservation is especially pronounced for cases where there are large pressure differences across thin structural boundaries. The aim of this paper is to greatly reduce the volume error of the IB method by introducing velocity-interpolation and force-spreading schemes with the properties that the interpolated velocity field in which the structure moves is at least $\mathscr{C}$ 1 and satisfies a continuous divergence-free condition, and that the force-spreading operator is the adjoint of the velocity-interpolation operator. We confirm through numerical experiments in two and three spatial dimensions that this new IB method is able to achieve substantial improvement in volume conservation compared to other existing IB methods, at the expense of a modest increase in the computational cost. Further, the new method provides smoother Lagrangian forces (tractions) than traditional IB methods. Finally, the method presented here is restricted to periodic computational domains. Its generalization to non-periodic domains is important future work.

97 MATHEMATICS AND COMPUTING↗