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HYDRA : High-speed simulation architecture for precision spacecraft formation simulation

e Hierarchical Distributed Reconfigurable Architecture- is a scalable simulation architecture that provides flexibility and ease-of-use which take advantage of modern computation and communication hardware. It also provides the ability to implement distributed - or workstation - based simulations and high-fidelity real-time simulation from a common core. Originally designed to serve as a research platform for examining fundamental challenges in formation flying simulation for future space missions, it is also finding use in other missions and applications, all of which can take advantage of the underlying Object-Oriented structure to easily produce distributed simulations. Hydra automates the process of connecting disparate simulation components (Hydra Clients) through a client server architecture that uses high-level descriptions of data associated with each client to find and forge desirable connections (Hydra Services) at run time. Services communicate through the use of Connectors, which abstract messaging to provide single-interface access to any desired communication protocol, such as from shared-memory message passing to TCP/IP to ACE and COBRA. Hydra shares many features with the HLA, although providing more flexibility in connectivity services and behavior overriding.

formation flying↗

Dark Energy Survey Year 3 results: A 2.7% measurement of baryon acoustic oscillation distance scale at redshift 0.835

We present angular diameter measurements obtained by measuring the position of baryon acoustic oscillations (BAO) in an optimized sample of galaxies from the first three years of Dark Energy Survey data (DES Y3). The sample consists of 7 million galaxies distributed over a footprint of 4100 deg 2 with 0.6 < z photo < 1.1 and a typical redshift uncertainty of 0.03 ( 1 + z ) . The sample selection is the same as in the BAO measurement with the first year of DES data, but the analysis presented here uses three times the area, extends to higher redshift, and makes a number of improvements, including a fully analytical BAO template, the use of covariances from both theory and simulations, and an extensive preunblinding protocol. We used two different statistics; angular correlation function and power spectrum, and validate our pipeline with an ensemble of over 1500 realistic simulations. Both statistics yield compatible results. We combine the likelihoods derived from angular correlations and spherical harmonics to constrain the ratio of comoving angular diameter distance D M at the effective redshift of our sample to the sound horizon scale at the drag epoch. We obtain D M ( z eff = 0.835 ) / r d = 18.92 ± 0.51 , which is consistent with, but smaller than, the Planck prediction assuming flat Λ CDM , at the level of 2.3 σ . The analysis was performed blind and is robust to changes in a number of analysis choices. It represents the most precise BAO distance measurement from imaging data to date, and is competitive with the latest transverse ones from spectroscopic samples at z > 0.75 . When combined with DES 3 x 2 pt + SNIa , they lead to improvements in H 0 and Ω m constraints by ∼ 20 % .

79 ASTRONOMY AND ASTROPHYSICS↗

A Mathematical Analysis of an Example Delay Tolerant Network using the Theory of Sheaves

NASA’s High-Data Rate Architecture (HiDRA) project is working towards a general yet practical toolkit and knowledge base to help usher in the era of new technologies for space systems communications, such as optical links. The High-Rate Delay Tolerant Networking (HDTN) implementation falls under the umbrellas of both the toolkit and the knowledge base, as its advancements illuminate more general areas of Delay Tolerant Networking (DTN) that need growth. The goal of this paper is to explore the usage of particular mathematical machineries, namely temporal flow networks and sheaves, to identify fundamental, underlying structures in DTN for space systems. Satellites, space assets, ground stations, etc. give rise to a disconnected network, and it is the goal of DTN to glue disparate links together into a cohesive system, that is, a network. Depending on a given link, the latencies might be beyond that which the Transmission Control Protocol (TCP) can handle, and contact times might have one-way light times in excess of minute (sometimes significantly longer). Some links might be periodic (say, due to orbital mechanics) or they might not be. This diversity has made it difficult to probe the underlying structure. An immediate consequence is that DTNs in practice today are controlled by globally distributed contact plans (schedules), which are the input to the contact graph routing (CGR) algorithm. While this is effective for smaller networks, it will be very difficult to scale for future networks. Deeper and more rigorous theory is needed to bring DTN to the next evolutionary step. To this end, this paper introduces and suggests a mathematical framework for DTN, and applies it to a space network that is simulated using an orbital analysis toolkit. The tag-line for the structure known as sheaves is that they are the mathematically precise way of gluing local data together into unique, global data. If we consider routing, we see that networking is a “sheafy” science. We then discuss a simplified sheaf model, known as the cellular sheaf. The sheaf-theoretic analysis is presented and discussed, as it is hoped that this and related papers will help form the primordial ooze of DTN theory. Finally there is a section of future work suggesting follow-on research.

Delay Tolerant Networking↗

Rapid and high-throughput determination of sorghum ( Sorghum bicolor ) biomass composition using near infrared spectroscopy and chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum (Sorghum bicolor) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

09 BIOMASS FUELS↗

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗

The Advantages of Combining Morphological and Molecular Methods to Characterise Zooplankton Communities: A Case Study of the UNESCO Biosphere Reserve of the Berlengas Archipelago, Portugal

Understanding the ecological dynamics of zooplankton communities is crucial to precisely assessing the health of marine ecosystems and their management. Metabarcoding has contributed to a better understanding of biodiversity in marine environments. However, this methodology still requires protocol optimisation. Here, we used a complementary approach combining molecular and morphological identification methods to identify the zooplankton community inhabiting the Berlengas Archipelago, Portugal. The presence of non-indigenous species was also assessed. The results showed that the metabarcoding approach outperformed the classical morphological identification method, detecting more species with higher resolution. Nevertheless, the classical method was able to identify species that were not detected by the molecular approaches, probably due to a lack of reference data in the databases. The comparison between different molecular approaches showed that COI and bulk DNA gave better results than 18S rRNA and eDNA by detecting higher species diversity. However, complementarities were observed between them. Molecular tools also proved effective in identifying several potential non-indigenous species, identifying, for the first time, several potentially unreported NIS inhabiting the Portuguese marine ecosystems. Overall, our results confirmed the importance of combining both classical and molecular methods to obtain a more refined assessment of the zooplanktonic communities in marine environments.

Simões, Marco (ORCID:0000000179957304)↗

High-Precision Mapping of Diamond Crystal Strain Using Quantum Interferometry

Crystal-strain variation imposes significant limitations on many quantum sensing and information applications for solid-state defect qubits in diamond. Thus, the precision measurement and control of diamond crystal strain is a key challenge. Here, we report diamond strain measurements with a unique set of capabilities, including micron-scale spatial resolution, a millimeter-scale field of view, and a 2-order-of-magnitude improvement in volume-normalized sensitivity over previous work, reaching 5(2)×10 -8 /√Hzμm -3 (with spin-strain coupling coefficients representing the dominant systematic uncertainty). We use strain-sensitive spin-state interferometry on ensembles of nitrogen-vacancy (N-V) color centers in single-crystal bulk diamond with low strain gradients. This quantum interferometry technique provides insensitivity to magnetic-field inhomogeneity from the electronic and nuclear spin bath, thereby enabling long N-V–ensemble electronic spin dephasing times and enhanced strain sensitivity, as well as broadening the potential applications of the technique beyond isotopically enriched or high-purity diamond. We demonstrate the strain-sensitive measurement protocol first on a confocal scanning laser microscope, providing quantitative measurement of sensitivity as well as three-dimensional strain mapping; and second on a wide-field-imaging quantum diamond microscope. Our strain-microscopy technique enables fast, sensitive characterization for diamond material engineering and nanofabrication; as well as diamond-based sensing of strains applied externally, as in diamond anvil cells or embedded diamond stress sensors, or internally, as by crystal damage due to particle-induced nuclear recoils.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fiber-Optic Determination of N2, O2, and Fuel Vapor in the Ullage of Liquid-Fuel Tanks

A fiber-optic sensor system has been developed that can remotely measure the concentration of molecular oxygen (O2), nitrogen (N2), hydrocarbon vapor, and other gases (CO2, CO, H2O, chlorofluorocarbons, etc.) in the ullage of a liquid-fuel tank. The system provides an accurate and quantitative identification of the above gases with an accuracy of better than 1 percent by volume (for O2 or N2) in real-time (5 seconds). In an effort to prevent aircraft fuel tank fires or explosions similar to the tragic TWA Flight 800 explosion in 1996, OBIGGS are currently being developed for large commercial aircraft to prevent dangerous conditions from forming inside fuel tanks by providing an inerting gas blanket that is low in oxygen, thus preventing the ignition of the fuel/air mixture in the ullage. OBIGGS have been used in military aircraft for many years and are now standard equipment on some newer large commercial aircraft (such as the Boeing 787). Currently, OBIGGS are being developed for retrofitting to existing commercial aircraft fleets in response to pending mandates from the FAA. Most OBIGGS use an air separation module (ASM) that separates O2 from N2 to make nitrogen-enriched air from compressed air flow diverted from the engine (bleed air). Current OBIGGS systems do not have a closed-loop feedback control, in part, due to the lack of suitable process sensors that can reliably measure N2 or O2 and at the same time, do not constitute an inherent source of ignition. Thus, current OBIGGS operate with a high factor-of-safety dictated by process protocol to ensure adequate fuel-tank inerting. This approach is inherently inefficient as it consumes more engine bleed air than is necessary compared to a closed-loop controlled approach. The reduction of bleed air usage is important as it reduces fuel consumption, which translates to both increased flight range and lower operational costs. Numerous approaches to developing OBIGGS feedback-control sensors have been under development by many research groups and companies. However, the direct measurement of nitrogen (N2) is a challenge to most OBIGGS ullage sensors (such as tunable diode laser absorption) as they cannot measure N2 directly but depend on the measurement of oxygen (O2). The problem with a singular measure of O2, is that as the concentration (number density) of O2 decreases due to the inerting process or due to lower pressures from high altitudes, the precision and accuracy of the O2 measurement decreases. However, measuring O2 density in combination with N2 density (which is more abundant in air and in a N2-inerted fuel tank) can provide a much more accurate and reliable determination of the OBIGGS efficacy.

Nguyen, Quang-Viet↗

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum ↗

Using bursty announcements for detecting BGP routing anomalies

Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. Our research shows that BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods of infrequent activity. We hypothesize that we may use these bursty characteristics to detect anomalous routing incidents. In this work, we use manually verified ground truth metadata and volume of announcements as a baseline measure, and propose a burstiness measure that detects prior anomalous incidents with high recall and better precision than the volume baseline. We quantify the burstiness of inter-arrival times around the date and times of four large-scale incidents: the Indosat hijacking event in April 2014, the Telecom Malaysia leak in June 2015, the Bharti Airtel Ltd. hijack in November 2015, and the MainOne leak in November 2018; and three smaller scale incidents that led to traffic interception: the Belarusian traffic direction in February 2013, the Icelandic traffic direction in July 2013, and the Russian telecom that hijacked financial services in April 2017. Our method leverages the burstiness of disruptive update messages to detect these incidents. We describe limitations, open challenges, and how this method can be used for routing anomaly detection.

97 MATHEMATICS AND COMPUTING↗

Customer-Focused Key Performance Indicators for Electric Vehicle Charging

To systematically improve the public charging experience, EV charging industry stakeholders need to define and measure it precisely. Many stakeholders currently measure aspects of the charging experience, but they typically employ metrics that are either operational in nature, such as charger uptime and mean time between failures, or composite customer satisfaction indices. To improve the customer experience most effectively, the industry needs metrics that define the charging experience from the perspective of the customer, not business operations. Furthermore, industry practitioners need granular metrics to know what specific aspects of the charging experience need improvement. This report defines such customer-focused metrics, called key performance indicators (KPIs).

33 ADVANCED PROPULSION SYSTEMS↗

Fabrication and Modification of Nanoporous Silicon Particles

Silicon-based nanoporous particles as biodegradable drug carriers are advantageous in permeation, controlled release, and targeting. The use of biodegradable nanoporous silicon and silicon dioxide, with proper surface treatments, allows sustained drug release within the target site over a period of days, or even weeks, due to selective surface coating. A variety of surface treatment protocols are available for silicon-based particles to be stabilized, functionalized, or modified as required. Coated polyethylene glycol (PEG) chains showed the effective depression of both plasma protein adsorption and cell attachment to the modified surfaces, as well as the advantage of long circulating. Porous silicon particles are micromachined by lithography. Compared to the synthesis route of the nanomaterials, the advantages include: (1) the capability to make different shapes, not only spherical particles but also square, rectangular, or ellipse cross sections, etc.; (2) the capability for very precise dimension control; (3) the capacity for porosity and pore profile control; and (4) allowance of complex surface modification. The particle patterns as small as 60 nm can be fabricated using the state-of-the-art photolithography. The pores in silicon can be fabricated by exposing the silicon in an HF/ethanol solution and then subjecting the pores to an electrical current. The size and shape of the pores inside silicon can be adjusted by the doping of the silicon, electrical current application, the composition of the electrolyte solution, and etching time. The surface of the silicon particles can be modified by many means to provide targeted delivery and on-site permanence for extended release. Multiple active agents can be co-loaded into the particles. Because the surface modification of particles can be done on wafers before the mechanical release, asymmetrical surface modification is feasible. Starting from silicon wafers, a treatment, such as KOH dipping or reactive ion etching (RIE), may be applied to make the surface rough. This helps remove the nucleation layer. A protective layer is then deposited on the wafer. The protective layer, such as silicon nitride film or photoresist film, protects the wafer from electrochemical etching in an HF-based solution. A lithography technique is applied to pattern the particles onto the protective film. The undesired area of the protective film is removed, and the protective film on the back side of the wafer is also removed. Then the pattern is exposed to HF/surfactant solution, and a larger DC electrical current is applied to the wafers for a selected time. This step removes the nucleation layer. Then a DC current is applied to generate the nanopores. Next, a large electrical current is applied to generate a release layer. The particles are mechanically suspended in the solvent and collected by filtration or centrifuge.

Ferrari, Mauro↗

Theory of an Automatic Seepage Meter and Ramifications for Applications

A new approach for measuring fluxes across surface water—groundwater interfaces was recently proposed. The Automatic Seepage Meter (ASM) is equipped with a precise water level sensor and digital memory that analyzes water level time series in a vertical tube inserted into a streambed. The ability to infer flux values with high temporal resolution relies on an accurate interpretation of water level dynamics inside the tube. Here, we reduce the three-dimensional hydrodynamic problem that describes the ASM water level in a variety of field conditions to a single ordinary differential equation. This novel general analytical solution for estimating ASM responses is more comprehensive and flexible than previous approaches and is applicable to the entire range of field conditions, including steady or transient stream stages, evaporation, rainfall, and noise. For example, our analysis determines the timing of the nonmonotonic ASM response to a monotonic linear stream stage variation and explains previously used empirical parabolic approximation for estimating fluxes. We present algorithms for simultaneous inference of vertical interface flux and hydraulic conductivity values together with an example code. We quantify how the accuracy of parameter estimation depends on test duration and noise amplitude and propose how our analysis can be used to optimize field test protocols. On this basis, changing the ASM geometry by increasing the radius and decreasing tube insertion depth may enable ASM field test protocols that estimate interface flux and hydraulic conductivity faster while maintaining desired accuracy. Potential applications of joint parameter estimation are suggested.

47 OTHER INSTRUMENTATION↗

Cross-Cutting Flight Infrastructure Improvements on M2020

Mars2020 (M2020) was formulated as a mission that leveraged as much Mars Science Laboratory (MSL) heritage as possible, while focusing major new development efforts on the original and unique elements needed to accomplish the different mission objectives. Well publicized examples of high profile new developments include precision landing, the sampling and caching system, the specific instrument suite, improved mobility via Autonomous Navigation, and later the addition of the Ingenuity helicopter. Less well known are the refinements to the core flight infrastructure, primarily in the cross-cutting functions of Telecom, Avionics, Data Management, Communications Behaviors, and Parameter Management. These enhancements are introduced predominately via flight software, and represent increases in capability that justified their inclusion in an otherwise heritage-focused project environment.Perseverance’s cross-cutting flight infrastructure improvements fall into and across the following five categories. First is a trimming of the software footprint of infrastructure modules, in order to make room for memory demands elsewhere in the system. Second is the minimization of data volume to be downlinked, through various methods such as the incorporation of new compression options. Third is the maximization of the available downlink bandwidth for data, by curtailing content-less data (fill) and introducing an improved UHF proximity link protocol. Fourth is a reduction in vulnerabilities, through increased file system redundancy, robustness, and software process monitoring. Fifth is an increase in operations efficiency by lowering file system mount times, improving parallelism between simultaneous events, minimizing the time to recover from file system errors, streamlining the purging of obsolete data, and reducing the number of commands to service parameters by a factor of 100.Individually, none of the cross-cutting infrastructure improvements are likely to garner headlines, but collectively they appreciably improve the safety and operability of Perseverance over its predecessor. This paper will describe the improvements, their promise, and where applicable, their actual impact in operations.

Bohannon, Emily↗

Green Solvents for Precision Cleaning

Aerospace machinery used in liquid oxygen (LOX) fuel systems must be precision cleaned to achieve a very low level of non-volatile residue (< 1 mg0.1 m2), especially flammable residue. Traditionally chlorofluorocarbons (CFCs) have been used in the precision cleaning of LOX systems, specifically CFC 113 (C2Cl3F3). CFCs have been known to cause the depletion of ozone and in 1987, were banned by the Montreal Protocol due to health, safety and environmental concerns. This has now led to the development of new processes in the precision cleaning of aerospace components. An ideal solvent-replacement is non-flammable, environmentally benign, non-corrosive, inexpensive, effective and evaporates completely, leaving no residue. Highlighted is a green precision cleaning process, which is contaminant removal using supercritical carbon dioxide as the environmentally benign solvent. In this process, the contaminant is dissolved in carbon dioxide, and the parts are recovered at the end of the cleaning process completely dry and ready for use. Typical contaminants of aerospace components include hydrocarbon greases, hydraulic fluids, silicone fluids and greases, fluorocarbon fluids and greases and fingerprint oil. Metallic aerospace components range from small nuts and bolts to much larger parts, such as butterfly valves 18 in diameter. A fluorinated grease, Krytox, is investigated as a model contaminant in these preliminary studies, and aluminum coupons are employed as a model aerospace component. Preliminary studies are presented in which the experimental parameters are optimized for removal of Krytox from aluminum coupons in a stirred-batch process. The experimental conditions investigated are temperature, pressure, exposure time and impeller speed. Temperatures of 308 - 423 K, pressures in the range of 8.3 - 41.4 MPa, exposure times between 5 - 60 min and impeller speeds of 0 - 1000 rpm were investigated. Preliminary results showed up to 86 cleaning efficiency with the moderate processing conditions of 323 K, 13.8 MPa, 30 min and 750 rpm.

solvents↗

Bed Rest and Orthostatic-Hypotensive Intolerance

Orthostatic tolerance may be defined as the ability of humans to maintain cerebral perfusion and consciousness upon movement from a supine or sitting position to the upright posture; for example, subjects can stand suddenly or be tilted to the head-up body position. Similar but not identical physiological responses can be induced by positive G(sub Z) (head to foot) acceleration or exposure to lower body negative pressure (LBNP). The objective is to suddenly shift blood to the lower body to determine how effectively cardiovascular and neural-hormonal compensatory responses react to maintain blood pressure. In the most precise method for measuring tolerance, individuals would be stressed until they faint (syncope). However, the potential consequences and discomforts of such a test usually prohibit such a procedure so that few investigators actually induce syncope. In a more common approach, subjects are exposed to a given level of stress, for example, head-up tilt for 15 min, and any increases in heart rate or decreases in blood pressure are interpreted as indicators of progress toward syncope. Presumably, the greater the perturbation of heart rate and blood pressure, the closer to "tolerance," i.e., point of unconsciousness. Another more appropriate approach is to induce a progressively increasing hypotensive stress until pre-determined physiological responses or pre-syncopal symptoms appear. The physiological criteria may include a sudden drop in systolic blood pressure (greater than 25 mm/min), a sudden drop in heart rate (greater than 15 beats/min), or a systolic blood pressure less than 70 mmHg. The most common pre-syncopal symptoms include lightheadedness, stomach awareness or distress, feelings of warmth, tingly skin, and light to profuse sweating. Usually a combination of physiological responses and symptoms occurs such that, on different days, the tolerance time to the same orthostatic protocol is reproducible for a given individual. The assumption is that by taking subjects to near fainting, one can determine their tolerance. This latter pre-syncopal approach is better for estimating orthostatic or hypotensive tolerance than the former measurement of heart rate and blood pressure responses to a given stress. There is considerable variability in individual responses to orthostasis. For example, some subjects are "heart-rate responders" and have a pronounced cardiovascular response similar to that when performing moderately hard aerobic exercise, whereas others may experience pre-syncopal symptoms with very little increase in heart rate. Some individuals have a slow, gradual fall in blood pressure to orthostasis, and others have little change in blood pressure until a sudden precipitous fall in pressure occurs just prior to fainting. With both tilt and LBNP tests there is a low correlation between heart-rate or blood-pressure responses to a sub-tolerance stress as a measure of pre-syncopal limited orthostatic-hypotensive tolerance.

Schneider, Suzanne M.↗

Efficient, Predictive Tomography of Multi-Qubit Quantum Processors

After decades of R&D, quantum computers comprising more than 2 qubits are appearing. If this progress is to continue, the research community requires a capability for precise characterization (“tomography”) of these enlarged devices, which will enable benchmarking, improvement, and finally certification as mission-ready. As world leaders in characterization -- our gate set tomography (GST) method is the current state of the art – the project team is keenly aware that every existing protocol is either (1) catastrophically inefficient for more than 2 qubits, or (2) not rich enough to predict device behavior. GST scales poorly, while the popular randomized benchmarking technique only measures a single aggregated error probability. This project explored a new insight: that the combinatorial explosion plaguing standard GST could be avoided by using an ansatz of few-qubit interactions to build a complete, efficient model for multi-qubit errors. We developed this approach, prototyped it, and tested it on a cutting-edge quantum processor developed by Rigetti Quantum Computing (RQC), a US-based startup. We implemented our new models within Sandia’s PyGSTi open-source code, and tested them experimentally on the RQC device by probing crosstalk. We found two major results: first, our schema worked and is viable for further development; second, while the Rigetti device is indeed a “real” 8-qubit quantum processor, its behavior fluctuated significantly over time while we were experimenting with it and this drift made it difficult to fit our models of crosstalk to the data.

97 MATHEMATICS AND COMPUTING↗

Electric Drive Technologies Consortium (EDTC)/ Cost competitive, high-Performance, highly Reliable (CPR) Power Devices on 4H-SiC (Final Report)

4H-Silicon carbide (4H-SiC) is a wide bandgap semiconductor that offers superior material properties over silicon, including higher critical electric field, thermal conductivity, and electron saturation velocity. These advantages make 4H-SiC highly attractive for high-voltage, high-efficiency power electronics. However, realizing the full potential of SiC requires device technologies that are not only high-performing but also manufacturable and reliable under real-world operating conditions. This report summarizes the outcomes of a five-year R&D effort funded by the U.S. Department of Energy (DOE) under the Electric Drive Technologies Consortium (EDTC), focused on developing cost-competitive, high-performance, and highly reliable (CPR) power devices on 4H-SiC substrates. The program targeted scalable and manufacturable 1.2 kV-class SiC MOSFETs optimized for next-generation electric vehicles, renewable energy systems, and industrial power conversion. The project delivered transformative advancements in SiC power device performance and ruggedness. Particularly, Specific on-resistance (R on,sp ) was reduced by up to 37%, from ~4.0 m$\Omega \cdot$cm 2 in earlier designs to an industry-leading 2.40 m$\Omega \cdot$cm 2 , driven by optimized doping, refined JFET widths, and layout engineering. Breakdown voltages (BV) exceeded 1600 V, marking improvement over legacy baselines, and demonstrating the robustness of newly implemented junction profiles and edge terminations. Short-circuit withstand time (SCWT) saw a remarkable 4$\times$ increase, from ~2 $\mu$s to over 8 $\mu$s, achieved through the successful deployment of deep P-well structures (~1.8–2.0 $\mu$m) via channeling implantation. This innovative process breakthrough enabled precise junction formation without MeV-class implantation tools, reduced leakage under high field stress, and allowed even the shortest-channel devices (down to 0.3 $\mu$m) to achieve both high BV and excellent ruggedness—breaking the traditional trade-off between conduction efficiency and blocking capability. Several novel architectures pushed the performance envelope further. JBSFETs—featuring embedded Schottky portions—eliminated bipolar degradation and drastically reduced third-quadrant leakage, while Ladder MOSFETs introduced a clever orthogonal conduction path that achieved a 15.4% reduction in R on,sp over standard linear designs. Switching performance reached new benchmarks: short-channel devices showed a 31% reduction in total switching energy compared to 0.5 $\mu$m counterparts, while maintaining manageable gate drive requirements. Layout-optimized structures not only improved transconductance but also accelerated switching transitions, pointing to real-world benefits in converter-level efficiency. The devices also passed rigorous reliability validation. Stress-tested across TDDB, HTGB, HTRB, HVP, and burn-in, the devices screened under 30 V/10 hr and 43 V/1 s protocols consistently exhibited tighter lifetime distributions and long-term oxide robustness. These screening techniques proved effective in identifying latent defects and ensuring deployment-grade reliability. Meanwhile, advanced 3D TCAD simulations revealed and resolved electric field hotspots—particularly in HEXFET corners—where fields exceeding 4.8 MV/cm were mitigated through geometry-aware layout corrections. Overall, the results of this project demonstrate a manufacturable and scalable SiC power device platform that addresses key DOE performance targets for efficient, robust, and reliable 1.2kV 4H-SiC Power Devices. The developed technologies represent a meaningful step forward in the commercial readiness of high-voltage SiC solutions and provide a strong foundation for continued advancement in wide bandgap power electronics.

42 ENGINEERING↗