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At least 73 records · Page 4

Dwarf galaxies with ionizing radiation feedback. II. Spatially resolved star formation relation

We investigate the spatially resolved star formation relation using a galactic disk formed in a comprehensive high-resolution (3.8 pc) simulation. Our new implementation of stellar feedback includes ionizing radiation as well as supernova explosions, and we handle ionizing radiation by solving the radiative transfer equation rather than by a subgrid model. Photoheating by stellar radiation stabilizes gas against Jeans fragmentation, reducing the star formation rate (SFR). Because we have self-consistently calculated the location of ionized gas, we are able to make simulated, spatially resolved observations of star formation tracers, such as Hα emission. We can also observe how stellar feedback manifests itself in the correlation between ionized and molecular gas. Applying our techniques to the disk in a galactic halo of 2.3 × 10{sup 11} M {sub ☉}, we find that the correlation between SFR density (estimated from mock Hα emission) and H{sub 2} density shows large scatter, especially at high resolutions of ≲75 pc that are comparable to the size of giant molecular clouds (GMCs). This is because an aperture of GMC size captures only particular stages of GMC evolution and because Hα traces hot gas around star-forming regions and is displaced from the H{sub 2} peaks themselves. By examining the evolving environment around star clusters, we speculate that the breakdown of the traditional star formation laws of the Kennicutt-Schmidt type at small scales is further aided by a combination of stars drifting from their birthplaces and molecular clouds being dispersed via stellar feedback.

79 ASTRONOMY AND ASTROPHYSICS↗

Baryon acoustic oscillation, Hubble parameter, and angular size measurement constraints on the Hubble constant, dark energy dynamics, and spatial curvature

ABSTRACT In this paper, we use all available baryon acoustic oscillation, Hubble parameter, and quasar angular size data to constrain six dark energy cosmological models, both spatially flat and non-flat. Depending on the model and data combination considered, these data mildly favour closed spatial hypersurfaces (by as much as 1.7σ) and dark energy dynamics (up to a little over 2σ) over a cosmological constant Λ. The data also favour, at 1.8σ to 3.4σ, depending on the model and data combination, a lower Hubble constant than what is measured from the local expansion rate.

79 ASTRONOMY AND ASTROPHYSICS↗

Embedding spatial decomposition in parareal in time power system simulation

We propose an approach for combining two decompositions in power system simulation, temporal and spatial, with a goal to achieve faster simulation time than utilizing either one of them alone. The proposed approach builds upon the structure of the Parareal algorithm for temporal decomposition and explores an efficient way of embedding the spatial decomposition into its coarse and fine solutions. This introduces two types of simultaneous parallelism in power system simulations - parallelism between system areas and between coarse integration intervals for time integration. The results from the application of the proposed approach are shown on a two-area system comprised of the IEEE 16-machine, 68-bus, and the IEEE 50-machine, 145-bus system.

Duan, Nan↗

Stationary Spatial Charging Demand Distribution for Commercial Electric Vehicles in Urban Area

The electric vehicle (EV) is an increasingly popu- lar mobility solution today. It is especially appealing for urban commercial usage including serving commuters and delivering goods. Commercial EVs, defined as electric taxi fleets in this paper, contribute a lot to the energy consumption and emission. One critical component to facilitate the adoption of EVs is to provide sufficient charging infrastructures for road users to alleviate the range anxiety. In this study, we develop an analytical model to profile the stationary spatial distribution of charging demand for any given fleet of commercial EVs, which serves as the necessary input for planning the location of charging infrastructures. Our model considers the movement of EVs as a random walk, with the underlying Markov process driven by the spatial demand that the commercial EV fleet needs to serve. We then define the electricity consumption and charging models and develop the probability distribution that an EV may need to recharge its battery at any given location in the city, based on the stationary distribution of the random walk process. We calibrate the performance parameters of EVs from the trip record and present numerical experiments based on New York City taxi trip data and compare the solution from simulation with our analytical solution. The result shows that analytical solution is quite close to the simulation result. This paper provides insights to the city agencies and private companies to make charging infrastructure location planning.

Qian, Xinwu↗

A Novel Spatial-Temporal Variational Quantum Circuit to Enable Deep Learning on NISQ Devices

Quantum computing presents a promising approach for machine learning with its capability for extremely parallel computation in high-dimension through superposition and entanglement. Despite its potential, existing quantum learning algorithms, such as Variational Quantum Circuits (VQCs), face challenges in handling more complex datasets, particularly those that are not linearly separable. What’s more, it encounters the deployability issue, making the learning models suffer a drastic accuracy drop after deploying them to the actual quantum devices. To overcome these limitations, this paper proposes a novel spatial-temporal design, namely “ST-VQC”, to integrate nonlinearity in quantum learning and improve the robustness of the learning model to noise. Specifically, ST-VQC can extract spatial features via a novel block-based encoding quantum sub-circuit coupled with a layer-wise computation quantum sub-circuit to enable temporal-wise deep learning. Additionally, a SWAP-Free physical circuit design is devised to improve robustness. These designs bring a number of hyperparameters. After a systematic analysis of the design space for each design component, an automated optimization framework is proposed to generate the ST-VQC quantum circuit. The proposed ST-VQC has been evaluated on two IBM quantum processors, ibm-cairo with 27 qubits and ibmq-lima with 7 qubits to assess its effectiveness. The results of the evaluation on the standard dataset for binary classification show that ST-VQC can achieve over 30% accuracy improvement compared with existing VQCs on actual quantum computers. Moreover, on a non-linear synthetic dataset, the STVQC outperforms a linear classifier by 27.9%, while the linear classifier using classical computing outperforms the existing VQC by 15.58%.

Li, Jinyang↗

Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization

Purpose: Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patient's electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition. Methods: The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method, which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization. Results: 4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patient's left ventricular ejection fraction. Conclusions: 4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Discrete models of fluids: spatial averaging, closure and model reduction

We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Hardy, and Murdoch-Bedeaux. We also consider a simpler linear averaging originally developed in large eddy simulation of turbulence. We present several simple but representative examples of spatially averaged ODEs, where the closure error can be analyzed. Based on this analysis we suggest a general strategy for reducing the relative error of approximate closure. For problems with periodic highly oscillatory material parameters we propose a spectral boosting technique that augments the standard deconvolution and helps to correctly account for dispersion effects. We also conduct several numerical experiments, one of which is a complete mesoscale simulation of a stratified two-fluid flow in a channel. In this simulation, the operation count per coarse time step scales sublinearly with the number of particles.

Multiscale modeling, discrete models, fluid flow↗

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗

Comparisons of Temporal and Spatial Trends in the Spatially Complete Global Spectral Surface Albedos Products

Five years of spatially complete snow-free land surface albedo data have been prepared using high quality white-sky and black-sky land surface albedo observations (MOD43B3) from the MODIS instrument aboard NASA's Terra satellite platform. The data were generated using an updated ecosystem-dependent temporal interpolation technique. In this paper, we describe the refinements in the technique and the creation of a spatially complete snow-free five-year aggregate climatology product. This paper also describes an error analysis of the interpolation technique. The filled albedo products are examined through comparisons of temporal and spatial trends for pixels that have been filled versus pixels that have been retained in the original MOD43B3 values. The variability in the trends showcase how the filling technique maintains the pixel-level spatial, spectral, and temporal integrity of the MOD43B3 data. These comparisons are made for both a single-year of filled data, year 2002, and for the five-year aggregate climatology product.

Moody, Eric G.↗

Spatial Correlation Structures in SMAP Near-Surface Soil Moisture (How Spatially Correlated are the Temporal Variations of Soil Moisture at Different Locations? and Why Is This of Interest?)

Spatial correlation structures can describe the degree to which soil moisture at a specified location co-varies in time with that at other, remote locations. Using four years of warm season SMAP Level 2 near-surface soil moisture data, we compute these spatial correlation structures for points across North America. The character of these structures is seen to differ geographically; the structures found for the west-central US, for example, are significantly more spatially extensive. We then demonstrate how these structures can potentially be used to reconstruct soil moisture fields during the pre-SMAP era. In this exercise, we consider as "truth" the soil moistures produced in a long-term offline land surface model simulation (1980-2014) that utilizes precipitation forcing based on a high density of precipitation gauges. Then, for a given location within the continent, we construct an"estimated" soil moisture time series based solely on historical soil moisture information simulated at least 300 km distant from the location, using the SMAP-based spatial correlation structures to determine how to make best use of the remote information. The reconstructed soil moistures are found to have significant skill relative to the assumed truth, suggesting that the same approach, when applied in areas of low rain gauge density (i.e., in areas for which historically simulated soil moistures are necessarily inaccurate), could provide useful historical soil moisture estimates through the SMAP-guided extraction of relevant information from neighboring gauged regions.

Koster, Randal↗

Spatial–spectral Schroedinger embedding for target detection in hyperspectral imagery

In this work, the Schroedinger eigenmaps (SE) algorithm using spatial and spectral information has been applied to supervised classification of hyperspectral imagery (HSI). We have previously introduced the use of SE in spectral target detection problems. The original SE-based target detector was built on the spectral information encoded in the Laplacian and Schroedinger operators. The original SE-based detector is extended such that spatial connectivity of target-like pixels is explored and encoded into the Schroedinger operator using a “knowledge propagation” scheme. The modified SE-based detector is applied to two HSI data sets that share similar target materials. Receiver operating characteristic curves and rates of detection and false alarm at object level are used as quantitative metrics to assess the detector. In addition, the Schroedinger embedding performance in target detection is compared against the performances of principal component embedding and the Laplacian embedding. Finally, results show that the SE-based detector with spatial–spectral features outperforms the other considered approaches.

36 MATERIALS SCIENCE↗

Accounting for connectivity alters the apparent roles of spatial and environmental processes on metacommunity assembly

Understanding the relative contributions of spatial and environmental processes on community assembly is a central question in ecology. Despite this long-standing interest, our understanding of how landscape structure may drive spatial processes of community assembly remains poorly understood in part because of the challenge of tracking community assembly across landscapes and quantifying key aspects of landscapes that may impact assembly processes. Here, we examined the roles of spatial and environmental processes on structuring assemblies of ants in 72 cleared patches embedded within a forested landscape.

60 APPLIED LIFE SCIENCES↗

Spatially Resolved Mapping of Three-Dimensional Molecular Orientations with ~2 nm Spatial Resolution through Tip-Enhanced Raman Scattering

We record local optical field images of silver nanocubes (75 nm) using tip-enhanced Raman (TER) spectral imaging. The images that we observe are consistent with several recent reports from our group, but here, we demonstrate sub-2 nm spatial resolution in local optical field nanoimaging under ambient laboratory conditions. This is achieved by scanning the substrate (nanocube on Si) relative to a 4-thiobenzonitrile (TBN)-functionalized Ag-coated TER probe. The spatial resolution that we obtain necessitates that only a few molecules govern the recorded optical response; molecular orientation becomes an important consideration in such measurements. We model the orientation through geometry optimization of a TBN molecule chemisorbed onto an Ag79 cluster (sphere with a ~1 nm diameter). Using the computed orientation of the cluster-bound molecule, we then model the optical response using formalism that accounts for the orientation of the molecule relative to vector components of the local optical fields. We find optimal agreement between experiment and theory. In effect, this work reveals the parallels between single-molecule Raman scattering and high-spatial-resolution TER spectroscopy, even when the images themselves cannot be used to visualize a single molecule in real space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing Density and Spatial Distribution of Trap States in Ta 3 N 5 Thin Films for Rational Defect Passivation

Tantalum nitride (Ta 3 N 5 ) has gained significant attention as a potential photoanode material, yet it has been challenged by material quality issues. Defect-induced trap states are detrimental to the performance of any semiconductor material. Beyond influencing the performance of Ta 3 N 5 films, defects can also accelerate the degradation in water during desired electrochemical applications. Defect passivation has provided an enormous boost to the development of many semiconductor materials but is currently in its infancy for Ta 3 N 5 . This is in part due to a lack of experimental understanding regarding the spatial and energetic distribution of trap states throughout Ta 3 N 5 thin films. Here, we employ drive-level capacitance profiling (DLCP) to experimentally resolve the spatial and energetic distribution of trap states throughout Ta 3 N 5 thin films. The density of deeper energetic traps is found to reach ∼2.5 to 6 × 10 22 cm –3 at the interfaces of neat Ta 3 N 5 thin films, over an order of magnitude greater than the bulk. In addition to the spatial profile of deep trap states, we report neat Ta 3 N 5 thin films to be highly n-type in nature, owning a free carrier density of ∼9.74 × 10 17 cm –3 . This information, coupled with the present understanding of native oxide layers on Ta 3 N 5 , has facilitated the rational design of a targeted passivation strategy that simultaneously provides a means for catalyst immobilization. Loading catalyst via silatrane moieties suppresses the density of defects at the surface of Ta 3 N 5 thin films by two orders of magnitude, while also reducing the free carrier density of films by over one order of magnitude, effectively dedoping the films to ∼2.40 × 10 16 cm –3 . The surface passivation of Ta 3 N 5 films translates to suppressed defect-induced trapping and recombination of photoexcited carriers, as determined through absorption, photoluminescence, and transient photovoltage. Here, this illustrates how developing a deeper understanding of the distribution and influence of defects in Ta 3 N 5 thin films has the potential to guide future works and ultimately accelerate the integration and development of high-performance Ta 3 N 5 thin film devices.

defect passivation↗

Spatially addressable design of gradient index structures through spatial light modulator based holographic lithography

In this paper, we present an achievable gradient refractive index in bi-continuous holographic structures that are formed through five-beam interference. We further present a theoretic approach for the realization of gradient index devices by engineering the phases of the interfering beams with a pixelated spatial light modulator. As an example, the design concept of a gradient index Luneburg lens is verified through full-wave electromagnetic simulations. These five beams with desired phases can be generated through programming gray level super-cells in a diffractive spatial light modulator. As a proof-of-concept, gradient index structures are demonstrated using synthesized and gradient phase patterns displayed in the spatial light modulator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optical generation of a spatially variant two-dimensional lattice structure by using a phase only spatial light modulator

We propose a simple and straightforward method to generate spatially variant lattice structures by optical interference lithography method. Using this method, it is possible to independently vary the orientation and period of the two-dimensional lattice. The method consists of two steps which are: numerical synthesis of corresponding phase mask by employing a two-dimensional integrated gradient calculations and experimental implementation of synthesized phase mask by making use of a phase only spatial light modulator in an optical 4f Fourier filtering setup. As a working example, we provide the experimental fabrication of a spatially variant square lattice structure which has the possibility to guide a Gaussian beam through a 90° bend by photonic crystal self-collimation phenomena. The method is digitally reconfigurable, is completely scalable, and could be extended to other kind of lattices as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ultra-short longitudinal spatial coherence length of laser light with the combined effect of spatial, angular, and temporal diversity

We demonstrate ultra-high axial-resolution topography and tomography of multilayered objects using pseudo thermal light source, i.e., laser. The longitudinal spatial coherence (LSC) length of light was significantly reduced by synthesizing a pseudo thermal source with the combined effect of spatial, angular, and temporal diversity. Thus, generating a low spatially coherent (i.e., broad angular frequency spectrum) light source having narrow temporal frequency spectrum. The LSC length was reduced less than 10 μm using a very low magnification lens. Experimental results of optical sectioning of multilayer objects with high axial-resolution of the order of 4 μm was achieved which is comparable to broadband light source. The present system does not require any dispersion compensation optical system for biological samples as a highly monochromatic light source is used.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗