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At least 343 records · Page 19

R Coronae Borealis Star Evolution: Simulating 3D Merger Events to 1D Stellar Evolution Including Large-scale Nucleosynthesis

R Coronae Borealis (RCB) stars are rare hydrogen-deficient carbon-rich variable supergiants thought to be the result of dynamically unstable white dwarf mergers. In this article, we attempt to model RCB stars through all the relevant timescales by simulating a merger event in Octo-tiger, a 3D adaptive mesh refinement (AMR) hydrodynamics code, and mapping the post-merger object into MESA, a 1D stellar evolution code. We then post-process the nucleosynthesis on a much larger nuclear reaction network to study the enhancement of s-process elements. We present models that match observations or previous studies in most surface abundances, isotopic ratios, early evolution, and lifetimes. We also observe similar mixing behavior to previous modeling attempts that result in the partial He-burning products visible on the surface in observations. However, we do note that our subsolar models lack any enhancement in s-process elements, which we attribute to a lack of hydrogen in the envelope. We also find that the 16 O/ 18 O isotopic ratio is very sensitive to initial hydrogen abundance and increases outside of the acceptable range with a hydrogen mass fraction greater than 10 -4 .

79 ASTRONOMY AND ASTROPHYSICS↗

Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts (Short Paper)

Population modeling requires clear definitions of socioeconomic status (SES) to ensure overall estimate accuracy and locate potentially underserved subpopulations. This presents a challenge as SES can be measured in myriad ways and for divergent purposes, and the data required to calculate these metrics may be lacking, particularly in low and middle income countries (LMICs). To support more refined SES measurement, we explore improvements upon the Demographic and Health Survey’s (DHS) Wealth Index (DHS-WI) using alternative characterizations of SES based on multiple correspondence analysis (MCA) and hierarchical clustering. We produce the MCA-derived metrics first on a full suite of household economic, demographic, and dwelling variables, then on a reduced set of occupant-only SES characteristics. We explore the utility of these metrics relative to DHS-WI based on their ability to 1) differentiate DHS household types and 2) identify mixtures of SES levels within DHS samples and mapped at high spatial resolution. We find that our full suite MCA yields more clearly defined SES segments and that our reduced MCA delineates occupant SES most clearly, suggesting potential pathways to improve upon the DHS-WI in future population modeling efforts for LMICs.

Cunningham, Angela↗

High Carrier Lifetimes in Epitaxial Germanium-Tin/Al(In)As Heterostructures with Variable Tin Compositions

Group IV-based germanium-tin (Ge1-ySny) compositional materials have recently shown great promise for infrared detection, light emission and ultra-low power transistors. High carrier lifetimes are desirable for enhancing the detection limit and efficiency of photodetectors, low threshold current density in lasers, and low tunneling barrier height by lowering defects and dislocations at the heterointerface of a source and a channel. Here, carrier lifetimes in epitaxial germanium (Ge) and variable tin (Sn) compositional Ge1-ySny materials were experimentally determined on GaAs substrates using the contactless microwave photoconductive decay (u-PCD) technique at an excitation wavelength of 1500 nm. Sharp (2 x 2) reflection high energy electron diffraction patterns and low surface roughness were observed from the surface of the Ge0.97Sn0.03 epilayer. X-ray rocking curves from Ge0.97Sn0.03 and Ge0.94Sn0.06 layers demonstrated the pseudomorphic and lattice-matched growth on AlAs and In0.12Al0.88As buffers, respectively, further substantiated by reciprocal space maps and abrupt heterointerfaces evident from the presence of Pendellosung oscillations. High effective carrier lifetimes of 150 ns to 450 ns were measured for Ge1-ySny epilayers as a function of Sn composition, surface roughness, growth temperature, and layer thickness. The observed increase in the carrier lifetime with an increasing Ge layer thickness and a reducing surface roughness, by incorporating Sn, were explained. The enhancement of the carrier lifetime with an increasing Sn concentration was achieved by controlling the defects with lattice-matched Ge0.94Sn0.06/In0.12Al0.88As heterointerfaces or the pseudomorphic growth of Ge0.94Sn0.06 on GaAs. Therefore, our monolithic integration of variable Sn alloy compositional Ge1-ySny materials with high carrier lifetimes opens avenues to realize electronic and optoelectronic devices.

carrier lifetimes↗

CMIP6 Models Underestimate the Holton‐Tan Effect

Abstract The teleconnection between the Quasi‐Biennial Oscillation (QBO) and the Arctic polar vortex is investigated using Coupled Model Intercomparison Project 6 (CMIP6) models. Output from 14 CMIP6 models is compared with reanalysis, three experiments with prescribed QBOs, one of which has no free polar stratospheric variability, and transient experiments in which a QBO is prescribed in runs previously devoid of a QBO. Each CMIP6 model underestimates the Holton‐Tan effect (HTE), the weakening of the polar vortex expected with QBO easterlies in the tropical lower stratosphere. To establish why, potential vorticity maps are used to investigate longitudinal variations in the teleconnection. Prescribing easterly QBO in the transient experiments promotes more high‐latitude planetary wave breaking by influencing the mid‐latitude stratospheric circulation, particularly over Asia. CMIP6 models that better simulate this response over Asia better simulate the HTE. These models also have stronger 10 hPa QBO westerlies.

54 ENVIRONMENTAL SCIENCES↗

Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.

54 ENVIRONMENTAL SCIENCES↗

Learning effective SDEs from Brownian dynamic simulations of colloidal particles

We construct a reduced, data-driven, parameter dependent effective stochastic differential equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian dynamics simulations. We use diffusion maps (a manifold learning algorithm) to identify a set of useful latent observables. In this latent space we identify an eSDE using a deep learning architecture inspired by numerical stochastic integrators and compare it with the traditional Kramers–Moyal expansion estimation. We show that the obtained variables and the learned dynamics accurately encode the physics of the Brownian dynamic simulations. We further illustrate that our reduced model captures the dynamics of corresponding experimental data. Further, our dimension reduction/reduced model identification approach can be easily ported to a broad class of particle systems dynamics experiments/models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hantavirus is Associated With Open Developed Areas and Arid Climates, Highlighting Increased Risk in the Western United States

In the United States, hantaviruses can cause hantavirus pulmonary syndrome (HPS) in humans, an acute respiratory illness with a high mortality rate. Most people contract HPS from exposure to infected rodent excrement. The interannual dynamics of hantavirus transmission are tied to both environmental and human-related factors, including changes in annual climate conditions, rodent populations, and the built environment in which humans are more likely to be exposed. Similar environmental conditions and socioeconomic factors also likely determine the long-term risk of hantavirus exposure. Here, we use ecological niche models and human cases of HPS in the U.S. from 1993 to 2022 to assess hantavirus risk using four socioeconomic variables, 17 land use variables, one variable of rodent richness, and seven climate variables to determine both the geographical locations of highest exposure risk and leading environmental predictors. We found that areas with higher relative risk tend to be where it is drier, higher social vulnerability, increased rodent richness, and more open to low levels of development—this largely mapped to the western U.S. We found evidence that fringe ecosystems may be important areas of hantavirus transmission, similar to other emerging diseases. Increased rodent richness was associated with increased hantavirus risk, warranting further investigation into how the abundance and community composition of rodents could impact long-term risk. These risk maps can help public health officials develop plans for mitigating hantavirus, especially for the most susceptible populations. They can also be used to further investigate regions estimated to be at high risk for hantavirus where disease cases have not been as common but may be underreported.

54 ENVIRONMENTAL SCIENCES↗

Genesis: A Compiler Framework for Hamiltonian Simulation on Hybrid CV-DV Quantum Computers

We introduce Genesis, the first compiler designed to support Hamiltonian Simulation on hybrid continuous-variable (CV) and discrete-variable (DV) quantum computing systems. Genesis is a two-level compilation system. At the first level, it decomposes an input Hamiltonian into basis gates using the native instruction set of the target hybrid CV-DV quantum computer. At the second level, it tackles the mapping and routing of qumodes/qubits to implement long-range interactions for the gates decomposed from the first level. Rather than a typical implementation that relies on SWAP primitives similar to qubit-based (or DV-only) systems, we propose an integrated design of connectivity-aware gate synthesis and beamsplitter SWAP insertion tailored for hybrid CV-DV systems. We also introduce an OpenQASM-like domain-specific language (DSL) named CVDV-QASM to represent Hamiltonian in terms of Pauli-exponentials and basic gate sequences from the hybrid CVDV gate set. Genesis has successfully compiled several important Hamiltonians, including the Bose-Hubbard model, Z2−Higgs model, Hubbard-Holstein model, Heisenberg model and Electron-vibration coupling Hamiltonians, which are critical in domains like quantum field theory, condensed matter physics, and quantum chemistry. Our implementation is available at Genesis-CVDV-Compiler https://github.com/ruadapt/Genesis-CVDV-Compiler

Chen, Henry↗

Orbital Motion, Variability, and Masses in the T Tauri Triple System

We present results from adaptive optics imaging of the T Tauri triple system obtained at the Keck and Gemini Observatories in 2015−2019. We fit the orbital motion of T Tau Sb relative to Sa and model the astrometric motion of their center of mass relative to T Tau N. Using the distance measured by Gaia, we derived dynamical masses of M{sub Sa}=2.05±0.14 M {sub ⊙} and M {sub Sb} = 0.43 ± 0.06 M{sub ⊙}. The precision in the masses is expected to improve with continued observations that map the motion through a complete orbital period; this is particularly important as the system approaches periastron passage in 2023. Based on published properties and recent evolutionary tracks, we estimate a mass of ∼2 M {sub ⊙} for T Tau N, suggesting that T Tau N is similar in mass to T Tau Sa. Narrowband infrared photometry shows that T Tau N remained relatively constant between late 2017 and early 2019 with an average value of K = 5.54 ± 0.07 mag. Using T Tau N to calibrate relative flux measurements since 2015, we found that T Tau Sa varied dramatically between 7.0 and 8.8 mag in the K band over timescales of a few months, while T Tau Sb faded steadily from 8.5 to 11.1 mag in the K band. Over the 27 yr orbital period of the T Tau S binary, both components have shown 3–4 mag of variability in the K band, relative to T Tau N.

79 ASTRONOMY AND ASTROPHYSICS↗

Dedicated beam position monitor pair for model-independent lattice characterization at NSLS-II

This paper reports recent lattice characterization results obtained at the National Synchrotron Light Source II (NSLS-II) storage ring, conducted without reliance on a lattice model. A pair of beam position monitors (BPMs) with bunch-by-bunch (B$\times$B) resolution, were recently installed in a section of the storage ring free of magnetic fields. The new BPM pair measured the beam, or bunch’s transverse Poincaré map precisely after the beam was excited. Linear one-turn-matrices (OTM) were then derived, and from these, the 4-dimensional coupled Twiss parameters were extracted at the locations of the BPM pair. By normalizing beam oscillation amplitudes with the Twiss parameters, the global action-variables were obtained. Additionally, these action-variables facilitated the measurement of the local Twiss parameters observed by other BPMs independent on lattice model. This method is general, and particularly useful in certain scenarios such as a round beam mode in a diffraction-limited light source ring. We applied it to assess both weakly and strongly coupled lattices at the NSLS-II ring. Through analysis of the strongly coupled lattice, the quadrupole tilt errors were estimated to be less than 400 μrad. Utilizing the BPMs’ B$\times$B resolution, for the first time we observed the variations of the linear lattice along a long bunch-train.

36 MATERIALS SCIENCE↗

Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Abstract We develop a physics‐informed machine learning approach for large‐scale data assimilation and parameter estimation and apply it for estimating transmissivity and hydraulic head in the two‐dimensional steady‐state subsurface flow model of the Hanford Site given synthetic measurements of said variables. In our approach, we extend the physics‐informed conditional Karhunen‐Loéve expansion (PICKLE) method to modeling subsurface flow with unknown flux (Neumann) and varying head (time‐dependent Dirichlet) boundary conditions. We demonstrate that the PICKLE method is comparable in accuracy with the standard maximum a posteriori (MAP) method, but is significantly faster than MAP for large‐scale problems. Both methods use a mesh to discretize the computational domain. In MAP, the parameters and states are discretized on the mesh; therefore, the size of the MAP parameter estimation problem directly depends on the mesh size. In PICKLE, the mesh is used to evaluate the residuals of the governing equation, while the parameters and states are approximated by the truncated conditional Karhunen‐Loéve expansions with the number of parameters controlled by the smoothness of the parameter and state fields, and not by the mesh size. For a considered example, we demonstrate that the computational cost of PICKLE increases near linearly (as N 1.15 ) with the number of grid nodes N , while that of MAP increases much faster (as N 3.28 ). We also show that once trained for one set of Dirichlet boundary conditions (i.e., one river stage), the PICKLE method provides accurate estimates of the hydraulic head for any value of the Dirichlet boundary conditions (i.e., for any river stage).

97 MATHEMATICS AND COMPUTING↗

Analysis of Control Behavior in Eco-Driving Speed Optimization Using Pontryagin’s Minimum Principle

The energy efficiency of autonomous vehicles can be improved by selecting an optimized speed profile. Energy savings can be maximized by performing control optimization with knowledge of the powertrain characteristics and future driving conditions. Previous studies have shown that Pontryagin’s minimum principle (PMP) performs well in vehicle speed optimization problems. Building on the methods proposed in previous studies, the contribution of this study is to derive meaningful observations from the concepts and results of PMP to enhance the understanding of the control problem. In particular, the switching behavior of the control mode is analyzed with supportive variables, such as ξ and mv, which dictates the changes in the control modes. Additionally, the existence of the singular control is analyzed, which helps in understanding the cruise driving in the control problem. Finally, we obtain several solutions that satisfy various boundary conditions along with a map of the reachable states, and discuss the impact of cruise driving. This is helpful for designing practical control concepts for real-world applications based on this map. Previous studies have contributed significantly to this control problem; however, this study provides a better understanding of the issue and offers guidance and inspiration for future real-world applications based on these meaningful observations.

33 ADVANCED PROPULSION SYSTEMS↗

Using multimodal X-ray computed tomography to advance 3D petrography: A non-destructive investigation of olivine inside a carbonaceous chondrite

Rocks form in three dimensions through time and studying them provides information from inside dynamic systems we cannot otherwise observe. Yet how we typically access the interior of the rocks themselves to gain that information may limit our understanding and influence how we reconstruct the processes that formed them. Here, we demonstrate combined non-destructive 3D X-ray imaging techniques that produce quantitative densitometric and crystallographic maps of entire individual grains inside a rock. Olivine grains throughout a sample of the carbonaceous chondrite Northwest Africa (NWA) 11346 were each characterized by size, shape, composition, zoning intensity, and crystallographic orientation. The addition of 3D crystallographic mapping to calibrated 3D densitometric analysis—used to calculate chemical composition—demonstrates a fully non-destructive petrographic method and provides unique insight. For instance, in our case, using crystallographic data to delineate individual grains and then measuring the 3D size, shape, and composition of each distinguishes variably reset relict grains from those later crystallized after a melting event. Intersection in a 2D slice could not have led to this interpretation because the integration of three-dimensional size, rounding, composition, location, and crystallographic orientation measured from each grain forms the key patterns. Multimodal laboratory X-ray imaging has strong potential to advance 3D petrography.

36 MATERIALS SCIENCE↗

Dedicated beam position monitor pair for model-independent lattice characterization at NSLS-II

This paper reports recent lattice characterization results obtained at the National Synchrotron Light Source II (NSLS-II) storage ring, conducted without reliance on a lattice model. A pair of beam position monitors (BPMs) with bunch-by-bunch (B×B) resolution, were recently installed in a section of the storage ring free of magnetic fields. The new BPM pair measured the beam, or bunch’s transverse Poincar´e map precisely after the beam was excited. Linear one-turn-matrices (OTM) were then derived, and from these, the 4-dimensional coupled Twiss parameters were extracted at the locations of the BPM pair. By normalizing beam oscillation amplitudes with the Twiss parameters, the global action-variables were obtained. These action-variables facilitated the measurement of the local Twiss parameters observed by other BPMs independent on lattice model. This method is general, and particularly useful in certain scenarios such as a round beam mode in a diffraction-limited light source ring. We applied it to assess both weakly and strongly coupled lattices at the NSLS-II ring. Through analysis of the strongly coupled lattice, the quadrupole tilt errors were estimated to be less than 400 µrad. Utilizing the BPMs’ B×B resolution, for the first time we observed the variations of the linear lattice along a long bunch-train.

43 PARTICLE ACCELERATORS↗

Magnetohydrodynamic Control of Interfacial Degradation in Lithium-Ion Batteries for Fast Charging Applications

Interfacial anodic degradation in graphitic materials under fast charging conditions causes severe performance loss and safety hazard in lithium ion batteries. We present a novel method for minimizing the growth of these aging mechanism by application of an external magnetic field. Under magnetic field, paramagnetic lithium ions experience a magnetohydrodynamic force, which rotates the perpendicularly diffusing species and homogenizes the ionic transport. This phenomenon minimizes the overpotential hotspots at the anode/separator interface, consequently reducing SEI growth, lithium plating, and interfacial fracture. In situ electrochemical measurements indicate an improvement in capacity for lithium cobalt oxide/graphite pouch cell (20 mAh) charged from 1–5 C under an applied field of 1.8 kG, with a maximum capacity gain of 22% at 5C. Post-mortem FE-SEM and EDS mapping shows that samples charged with magnetic field have a reduced lithium deposition at 3C and a complete suppression of interfacial fracture at 5C. At 5C, a 24% reduction in the lithium content is observed by performing XPS on the anodic interfacial film. Finally, fast charging performance under variable magnetic field strengths indicate a saturation behavior in capacity at high fields (>2 kG), thereby limiting the field and consequent energy requirements to obtain maximum capacity gain under extreme conditions.

electromagnetism↗

Terahertz Nano-Imaging of Electronic Strip Heterogeneity in a Dirac Semimetal

Emerging topological semimetals offer promise of realizing topological electronics enabled by terahertz (THz) current persistent against impurity scattering. Yet most fundamental issues remain on how to image nanoscale conductivity inhomogeneity. Here in this paper we show noninvasive and contactless conductivity mapping at THz-nm limit of electronic heterogeneity and nanostrip junctions in a Dirac material ZrTe 5 . A clear Dirac Fermion density transition, manifested as the exclusive THz conductivity contrast, is quantitatively analyzed and profiled on both sides of the junction. This also allows the determination of variable junction width of ~25–220 nm, depending on the THz conductivity contrast of adjacent strips. The unique THz-nm contrast is absent in mid-infrared nano-imaging measurements since topological semimetals with small Fermi pockets exhibit a better matching of their plasma frequency and scattering rate to the THz spectral region. The first-principles calculations provide two compelling implications: the conductivity nanocontrast can be induced by a small anisotropic strain, even less than 0.5%, due to an extreme strain sensitivity in ZrTe 5 ; A nanoscale topological phase transition is realized across some junctions induced by the strain, between strong topological insulators (TIs) and weak TIs/Dirac semimetals (DSMs).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

From boundary data to bound states. Part II. Scattering angle to dynamical invariants (with twist)

We recently introduced in [9] a boundary-to-bound dictionary between gravitational scattering data and observables for bound states of non-spinning bodies. In this paper, we elaborate further on this holographic map. We start by deriving the following — remarkably simple — formula relating the periastron advance to the scattering angle: $ΔΦ(J,ε)=χ(J,ε)+χ(-J,ε)$, via analytic continuation in angular momentum and binding energy. Using explicit expressions from [9], we confirm its validity to all orders in the Post-Minkowskian (PM) expansion. Furthermore, we reconstruct the radial action for the bound state directly from the knowledge of the scattering angle. The radial action enables us to write compact expressions for dynamical invariants in terms of the deflection angle to all PM orders, which can also be written as a function of the PM-expanded amplitude. As an example, we reproduce our result in [9] for the periastron advance, and compute the radial and azimuthal frequencies and redshift variable to two-loops. Agreement is found in the overlap between PM and Post-Newtonian (PN) schemes. Last but not least, we initiate the study of our dictionary including spin. We demonstrate that the same relation between deflection angle and periastron advance applies for aligned-spin contributions, with J the (canonical) total angular momentum. Explicit checks are performed to display perfect agreement using state-of-the-art PN results in the literature. Using the map between test- and two-body dynamics, we also compute the periastron advance up to quadratic order in spin, to one-loop and to all orders in velocity. We conclude with a discussion on the generalized ‘impetus formula’ for spinning bodies and black holes as ‘elementary particles’. Our findings here and in [9] imply that the deflection angle already encodes vast amount of physical information for bound orbits, encouraging independent derivations using numerical and/or self-force methodologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs

Coarse-grained reconfigurable arrays (CGRAs) provide higher flexibility than application-specific integrated circuits (ASICs) and higher efficiency than fine-grained reconfigurable devices such as Field Programmable Gate Arrays (FPGAs). However, CGRAs are generally designed to support offloading of a single kernel. While their design, based on communicating functional units, appears to naturally suit data streaming applications composed of multiple cooperating kernels, current approaches only statically partition the resources across application kernels. However, emerging streaming applications at the edge (scientific instruments, sensor networks, network processing) perform much more than digital signal processing and often are data and input dependent. This leads to extremely variable kernel execution times, severely impacting the throughput of the entire pipeline if resources are only statically allocated. Therefore, in this paper, we propose DRIPS — a coarse-grained, dynamically, and partially reconfigurable array for data-dependent streaming applications. We present a unified compiler framework to facilitate the mapping of a given streaming application onto the DRIPS CGRA architecture. The experimental results show that DRIPS achieves an average throughput improvement of 1.46$\times$ across a set of representative applications over a statically partitioned solution. The additional area overhead to enable dynamic rebalancing consumes 16.34% of the entire area for a 5x5 CGRA prototype.

Tan, Cheng↗