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At least 163 records · Page 9

Selective thermal neutron transmutation doping with Gd masks in GaN semiconductors

For the first time, selective neutron transmutation doping was successfully performed on GaN through Gd masks, showing the feasibility of patternable doping through neutron irradiations. In collaborating with Oak Ridge National Laboratory, GaN with Gd masks was irradiated by directional neutrons. By using the Gd properties with high neutron absorption cross-sections, it was confirmed that the area covered by Gd masks on GaN was completely shielded from neutrons, and the uncovered area was doped with the generated Ge and 14 C. Property differences were clearly identified in various ways when comparing the area exposed by neutrons and the area unexposed by neutrons. The discoloration by the ejected protons and elastic scattering of neutrons appeared only in the exposed area while the unexposed area remained the same as before irradiation. The aspect ratio of the patterned profile of GaN was estimated by comparing patterns on the front and backside. From energy dispersive X-ray spectroscopy spectra and secondary ion mass spectrometry measurement, the concentration difference between Ge and 14 C as well as the exact concentration of produced 14 C was also checked. Further, Schottky barrier diodes on the selectively doped GaN were fabricated and investigated to study the electrical properties.

42 ENGINEERING↗

Modeling of intense pulsed ion beam heated masked targets for extreme materials characterization

Intense, pulsed ion beams locally heat materials and deliver dense electronic excitations that can induce material modifications and phase transitions. Material properties can potentially be stabilized by rapid quenching. Pulsed ion beams with pulse lengths of order ns have recently become available for materials processing. Here, we optimize mask geometries for local modification of materials by intense ion pulses. The goal is to rapidly excite targets volumetrically to the point where a phase transition or local lattice reconstruction is induced followed by rapid cooling that stabilizes desired material's properties fast enough before the target is altered or damaged by, e.g., hydrodynamic expansion. By using a mask, the longitudinal dimension can be large compared to the transverse dimension, allowing the possibility of rapid transverse cooling. We performed HYDRA simulations that calculate peak temperatures for a series of excitation conditions and cooling rates of silicon targets with micro-structured masks and compare these to a simple analytical model. In conclusion, the model gives scaling laws that can guide the design of targets over a wide range of pulsed ion beam parameters.

36 MATERIALS SCIENCE↗

Active galactic nucleus and quasar science with aperture masking interferometry on the James Webb Space Telescope

Due to feedback from accretion onto supermassive black holes (SMBHs), active galactic nuclei (AGNs) are believed to play a key role in ΛCDM cosmology and galaxy formation. However, AGNs extreme luminosities and the small angular size of their accretion flows create a challenging imaging problem. We show that the James Webb Space Telescope's Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) Aperture Masking Interferometry (AMI) mode will enable true imaging (i.e., without any requirement of prior assumptions on source geometry) at ∼65 mas angular resolution at the centers of AGNs. This is advantageous for studying complex extended accretion flows around SMBHs and in other areas of angular-resolution-limited astrophysics. By simulating data sequences incorporating expected sources of noise, we demonstrate that JWST-NIRISS AMI mode can map extended structure at a pixel-to-pixel contrast of ∼10{sup –2} around an L = 7.5 point source, using short exposure times (minutes). Such images will test models of AGN feedback, fueling, and structure (complementary with ALMA observations), and are not currently supported by any ground-based IR interferometer or telescope. Binary point source contrast with NIRISS is ∼10{sup –4} (for observing binary nuclei in merging galaxies), significantly better than current ground-based optical or IR interferometry. JWST-NIRISS's seven-hole non-redundant mask has a throughput of 15%, and utilizes NIRISS's F277W (2.77 μm), F380M (3.8 μm), F430M (4.3 μm), and F480M (4.8 μm) filters. NIRISS's square pixels are 65 mas per side, with a field of view ∼2' × 2'. We also extrapolate our results to AGN science enabled by non-redundant masking on future 2.4 m and 16 m space telescopes working at long-UV to near-IR wavelengths.

79 ASTRONOMY AND ASTROPHYSICS↗

AN IMAGE-PLANE ALGORITHM FOR JWST'S NON-REDUNDANT APERTURE MASK DATA

The high angular resolution technique of non-redundant masking (NRM) or aperture masking interferometry (AMI) has yielded images of faint protoplanetary companions of nearby stars from the ground. AMI on James Webb Space Telescope (JWST)'s Near Infrared Imager and Slitless Spectrograph (NIRISS) has a lower thermal background than ground-based facilities and does not suffer from atmospheric instability. NIRISS AMI images are likely to have 90%-95% Strehl ratio between 2.77 and 4.8 μm. In this paper we quantify factors that limit the raw point source contrast of JWST NRM. We develop an analytic model of the NRM point spread function which includes different optical path delays (pistons) between mask holes and fit the model parameters with image plane data. It enables a straightforward way to exclude bad pixels, is suited to limited fields of view, and can incorporate effects such as intra-pixel sensitivity variations. We simulate various sources of noise to estimate their effect on the standard deviation of closure phase, σ{sub CP} (a proxy for binary point source contrast). If σ{sub CP} < 10{sup –4} radians—a contrast ratio of 10 mag—young accreting gas giant planets (e.g., in the nearby Taurus star-forming region) could be imaged with JWST NIRISS. We show the feasibility of using NIRISS' NRM with the sub-Nyquist sampled F277W, which would enable some exoplanet chemistry characterization. In the presence of small piston errors, the dominant sources of closure phase error (depending on pixel sampling, and filter bandwidth) are flat field errors and unmodeled variations in intra-pixel sensitivity. The in-flight stability of NIRISS will determine how well these errors can be calibrated by observing a point source. Our results help develop efficient observing strategies for space-based NRM.

79 ASTRONOMY AND ASTROPHYSICS↗

Validation of the DESI 2024 Lyman alpha forest BAL masking strategy

Broad absorption line quasars (BALs) exhibit blueshifted absorption relative to a number of their prominent broad emission features. These absorption features can contribute to quasar redshift errors and add absorption to the Lyman-α (Lyα) forest that is unrelated to large-scale structure. We present a detailed analysis of the impact of BALs on the Baryon Acoustic Oscillation (BAO) results with the Lyα forest from the first year of data from the Dark Energy Spectroscopic Instrument (DESI). The baseline strategy for the first year analysis is to mask all pixels associated with all BAL absorption features that fall within the wavelength region used to measure the forest. We explore a range of alternate masking strategies and demonstrate that these changes have minimal impact on the BAO measurements with both DESI data and synthetic data. This includes when we mask the BAL features associated with emission lines outside of the forest region to minimize their contribution to redshift errors. We identify differences in the properties of BALs in the synthetic datasets relative to the observational data, as well as use the synthetic observations to characterize the completeness of the BAL identification algorithm, and demonstrate that incompleteness and differences in the BALs between real and synthetic data also do not impact the BAO results for the Lyα forest.

Lyman alpha forest↗

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models

Abstract We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation invariant functions on sets. More generally, this work provides a step towards building large foundation models for HEP that can be generically pre-trained with self-supervised learning and later fine-tuned for a variety of down-stream tasks. In MPM, particles in a set are masked and the training objective is to recover their identity, as defined by a discretized token representation of a pre-trained vector quantized variational autoencoder. We study the efficacy of the method in samples of high energy jets at collider physics experiments, including studies on the impact of discretization, permutation invariance, and ordering. We also study the fine-tuning capability of the model, showing that it can be adapted to tasks such as supervised and weakly supervised jet classification, and that the model can transfer efficiently with small fine-tuning data sets to new classes and new data domains.

Heinrich, Lukas (ORCID:0000000240487584)↗

Understanding EUV mask blank surface roughness induced LWR and associated roughness requirement

Extreme ultraviolet lithography (EUVL) mask multi-layer (ML) blank surface roughness specification historically comes from blank defect inspection tool requirement. Later, new concerns on ML surface roughness induced wafer pattern line width roughness (LWR) arise. In this paper, we have studied wafer level pattern LWR as a function of EUVL mask surface roughness via High-NA Actinic Reticle Review Tool. We found that the blank surface roughness induced LWR at current blank roughness level is in the order of 0.5nm 3σ for NA=0.42 at the best focus. At defocus of ±40nm, the corresponding LWR will be 0.2nm higher. Further reducing EUVL mask blank surface roughness will increase the blank cost with limited benefit in improving the pattern LWR, provided that the intrinsic resist LWR is in the order of 1nm and above.

36 MATERIALS SCIENCE↗

WE-G-207-03: Mask Guided Image Reconstruction (MGIR): A Novel Method for Ultra-Low-Dose 3D and Enhanced 4D Cone-Beam Computer-Tomography

Purpose: Recently, compressed sensing (CS) based iterative reconstruction (IR) method is receiving attentions to reconstruct high quality cone beam computed tomography (CBCT) images using sparsely sampled or noisy projections. The aim of this study is to develop a novel baseline algorithm called Mask Guided Image Reconstruction (MGIR), which can provide superior image quality for both low-dose 3DCBCT and 4DCBCT under single mathematical framework. Methods: In MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions where anatomical structures are 1) within the priori-defined mask and 2) outside the mask. Then we update each part of images alternatively thorough solving minimization problems based on CS type IR. For low-dose 3DCBCT, the former region is defined as the anatomically complex region where it is focused to preserve edge information while latter region is defined as contrast uniform, and hence aggressively updated to remove noise/artifact. In 4DCBCT, the regions are separated as the common static part and moving part. Then, static volume and moving volumes were updated with global and phase sorted projection respectively, to optimize the image quality of both moving and static part simultaneously. Results: Examination of MGIR algorithm showed that high quality of both low-dose 3DCBCT and 4DCBCT images can be reconstructed without compromising the image resolution and imaging dose or scanning time respectively. For low-dose 3DCBCT, a clinical viable and high resolution head-and-neck image can be obtained while cutting the dose by 83%. In 4DCBCT, excellent quality 4DCBCT images could be reconstructed while requiring no more projection data and imaging dose than a typical clinical 3DCBCT scan. Conclusion: The results shown that the image quality of MGIR was superior compared to other published CS based IR algorithms for both 4DCBCT and low-dose 3DCBCT. This makes our MGIR algorithm potentially useful in various on-line clinical applications. Provisional Patent: UF#15476; WGS Ref. No. U1198.70067US00.

60 APPLIED LIFE SCIENCES↗

SU-D-BRA-02: Motion Assessment During Open Face Mask SRS Using CBCT and Surface Monitoring

Purpose: To assess the robustness of immobilization using open-face mask technology for linac-based stereotactic radiosurgery (SRS) with multiple non-coplanar arcs via repeated CBCT acquisition, with comparison to contemporaneous optical surface tracking data. Methods: 25 patients were treated in open faced masks with cranial SRS using 3–4 non-coplanar arcs. Repeated CBCT imaging was performed to verify the maintenance of proper patient positioning during treatment. Initial patient positioning was performed based on prescribed shifts and optical surface tracking. Positioning refinements employed rigid 3D-matching of the planning CT and CBCT images and were implemented via automated 6DOF couch control. CBCT imaging was repeated following the treatment of all non-transverse beams with associated couch kicks. Detected patient translations and rotations were recorded and automatically corrected. Optical surface tracking was applied throughout the treatments to monitor motion, and this contemporaneous patient positioning data was recorded to compare against CBCT data and 6DOF couch adjustments. Results: Initial patient positions were refined on average by translations of 3±1mm and rotations of ±0.9-degrees. Optical surface tracking corroborated couch corrections to within 1±1mm and ±0.4-degrees. Following treatment of the transverse and subsequent superior-oblique beam, average translations of 0.6±0.4mm and rotations of ±0.4-degrees were reported via CBCT, with optical surface tracking in agreement to within 1.1±0.6mm and ±0.6-degrees. Following treatment of the third beam, CBCT indicated additional translations of 0.4±0.2mm and rotations of ±0.3-degrees. Cumulative couch corrections resulted in 0.7 ± 0.4mm average magnitude translations and rotations of ±0.4-degrees. Conclusion: Based on CBCT measurements of patients during SRS, the open face mask maintained patient positioning to within 1.5mm and 1-degree with >95% confidence. Patient positioning determined by optical surface tracking agreed with CBCT assessment to within 1±1mm and ±0.6-degree rotations. These data support the use of 1–2mm PTV margins and repeated CBCT to maintain stereotactic positioning tolerances.

60 APPLIED LIFE SCIENCES↗

TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images

Purpose: The daily treatment MRIs acquired on MR-IGRT systems, like diagnostic MRIs, suffer from intensity inhomogeneity issue, associated with B1 and B0 inhomogeneities. An improved homomorphic unsharp mask (HUM) filtering method, automatic and robust body segmentation, and imaging field-of-view (FOV) detection methods were developed to compute the multiplicative slow-varying correction field and correct the intensity inhomogeneity. The goal is to improve and normalize the voxel intensity so that the images could be processed more accurately by quantitative methods (e.g., segmentation and registration) that require consistent image voxel intensity values. Methods: HUM methods have been widely used for years. A body mask is required, otherwise the body surface in the corrected image would be incorrectly bright due to the sudden intensity transition at the body surface. In this study, we developed an improved HUM-based correction method that includes three main components: 1) Robust body segmentation on the normalized image gradient map, 2) Robust FOV detection (needed for body segmentation) using region growing and morphologic filters, and 3) An effective implementation of HUM using repeated Gaussian convolution. Results: The proposed method was successfully tested on patient images of common anatomical sites (H/N, lung, abdomen and pelvis). Initial qualitative comparisons showed that this improved HUM method outperformed three recently published algorithms (FCM, LEMS, MICO) in both computation speed (by 50+ times) and robustness (in intermediate to severe inhomogeneity situations). Currently implemented in MATLAB, it takes 20 to 25 seconds to process a 3D MRI volume. Conclusion: Compared to more sophisticated MRI inhomogeneity correction algorithms, the improved HUM method is simple and effective. The inhomogeneity correction, body mask, and FOV detection methods developed in this study would be useful as preprocessing tools for many MRI-related research and clinical applications in radiotherapy. Authors have received research grants from ViewRay and Varian.

60 APPLIED LIFE SCIENCES↗

Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping

In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments. In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.

97 MATHEMATICS AND COMPUTING↗

Thermal FEA for Front End Fixed Mask (SST)

The purpose of this study was to determine the temperature of the Fixed Mask using heat loads of the U42 Undulator. Finite Element Analysis was conducted on the fixed mask, to determine the temperature distribution on it, for 500 milli-amp current for NSLS-II. The Fixed mask has the sine wave surface profile.

36 MATERIALS SCIENCE↗

Masked Symbol Modeling for Demodulation of Oversampled Baseband Communication Signals in Impulsive Noise-Dominated Channels

Recent breakthroughs in natural language processing show that attention mech- anism in Transformer networks, trained via masked-token prediction, enables models to capture the semantic context of the tokens and internalize the grammar of language. While the application of Transformers to communication systems is a burgeoning field, the notion of context within physical waveforms remains under-explored. This paper addresses that gap by re-examining inter-symbol con- tribution (ISC) caused by pulse-shaping overlap. Rather than treating ISC as a nuisance, we view it as a deterministic source of contextual information embedded in oversampled complex baseband signals. We propose Masked Symbol Model- ing (MSM), a framework for the physical (PHY) layer inspired by Bidirectional Encoder Representations from Transformers methodology. In MSM, a subset of symbol-aligned samples is randomly masked, and a Transformer predicts the missing symbol identifiers using the surrounding “in-between” samples. Through this objective, the model learns the latent syntax of complex baseband waveforms. We illustrate MSM’s potential by applying it to the task of demodulating sig- nals corrupted by impulsive noise, where the model infers corrupted segments by leveraging the learned context. Our results suggest a path toward receivers that interpret, rather than merely detect communication signals, opening new avenues for context-aware PHY layer design.

Bedir, Oguz↗

Merged RWP-WACR-ARSCL Cloud Mask and Cloud Type

The Merged RWP-WACR-ARSCL Cloud Mask and Cloud Type PI Data Product combines the RWP calibrated radar reflectivity data with the WACR-ARSCL dataset to improve cloud mask in precipitating clouds and to provide cloud-type profile classification. WACR-ARSCL cloud profiles during substantial precipitation period where severe attenuation affects accuracy of WACR cloud-top detections were replaced with RWP profiles. The merged RWP-WACR-ARSCL cloud mask is then used to produce cloud-type profile classification. The cloud-type classification includes a total of seven cloud types: shallow cumulus, congestus, deep convective clouds, altocumulus, altostratus, cirrostratus and cirrus. See the data description for more details about the dataset.

54 ENVIRONMENTAL SCIENCES↗

Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017

Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during summer 2017(July 22 to August 20). ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than &alpha; times the standard deviation (&sigma;m) of the data below the median plus the two points after are masked by ENA-AM.

54 ENVIRONMENTAL SCIENCES↗

Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Winter 2017

Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during Winter 2017(December 1-30). ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than &alpha; times the standard deviation (&sigma;m) of the data below the median plus the two points after are masked by ENA-AM.

54 ENVIRONMENTAL SCIENCES↗

Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Supplementary Facility (S01)

Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at the ENA supplementary site (S1) during summer (July 22 to August 20) 2017. ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than &alpha; times the standard deviation (&sigma;m) of the data below the median plus the two points after are masked by ENA-AM.

54 ENVIRONMENTAL SCIENCES↗

KAZR Hydrometeor and Insect Masks

The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.

54 ENVIRONMENTAL SCIENCES↗