Generalized Computer Techniques for the Solution of Contour-map Problems
Generalized computer techniques for solving contour map problems
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Generalized computer techniques for solving contour map problems
Isothermal and isophotic atlas of moon contours through lunation
Lamellar phases frequently contain structural imperfections that significantly affect their behaviors and properties. Our previous research successfully reconstructed real-space configurations of defective lamellar phases from diffuse scattering patterns, indicating the presence of phase vortices as a potential method for identifying topological defects disrupting the smectic ordering. Here, this report presents a mathematical framework using regularized wave fields to represent defective lamellar structures in real space. Phase singularities, resulting from the interference of random waves and indicating lamellar order disruption, are identified through a contour integral. These wave fields, derived from coherent scattering in reciprocal space, were validated via computational benchmarks analyzing small-angle neutron scattering data from AOT surfactant solutions, facilitating further statistical analysis of the defects. Our study highlights the potential to extract meaningful information about topological defects in lyotropic phases by inversely analyzing experimentally measured two-point static correlations. Our method allows for detailed structural analysis of various lyotropic phases, both particulate and nonparticulate, in their quiescent states and facilitates quantitative investigation of defects’ role in phase transitions. By integrating small-angle scattering, deep learning, and vortex tangle analysis, our comprehensive approach shows promise in addressing complex challenges in the structural analysis of soft matter systems.
We propose a new method to investigate the existence and location of the conjectured high-temperature critical point of strongly interacting matter via contours of constant entropy density. By approximating these lines as a power series in the baryon chemical potential 𝜇 𝐵 , one can extrapolate them from first-principle results at zero net-baryon density, and use them to locate the quantum chromodynamics (QCD) critical point, including the associated first-order and spinodal lines. As a proof of principle, we employ currently available continuum-extrapolated lattice data from the Wuppertal-Budapest collaboration to find a critical point at a temperature and a baryon chemical potential of 𝑇 𝑐 = 114.3 ± 6.9 MeV and 𝜇 𝐵,𝑐 = 602.1 ± 62.1 MeV, respectively, at expansion order 𝒪(𝜇$^{2}_{𝐵}$). We advocate for a more precise determination of the required expansion coefficients via lattice QCD simulations as a means of pinpointing the location of the critical endpoint in the phase diagram of strongly interacting matter.
We show how contour deformations may be used to control the sign problem of lattice Monte Carlo calculations with nonholomorphic Boltzmann factors. Such actions arise naturally in quantum mechanical scattering problems. The approach is demonstrated in conjunction with the holomorphic gradient flow. As our central example we compute the real-time evolution of a particle in a one-dimensional analog of the Yukawa potential. Published by the American Physical Society 2024
Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate for data arising from distributions with heavier or lighter tails. We study a general family of elliptically contoured (EC) TV distributions and derive its characterizations, moments, marginal, and conditional distributions. We describe procedures for maximum likelihood estimation from data that are (1) uncorrelated draws from an EC distribution, (2) from a scale mixture of the TVN distribution, and (3) from an underlying but unknown EC distribution, for which we extend Tyler’s robust estimator. A detailed simulation study highlights the benefits of choosing an EC distribution over the TVN for heavier-tailed data. We develop TV classification rules using discriminant analysis and EC errors and show that they better predict cats and dogs from images in the Animal Faces-HQ dataset than the TVN-based rules. A novel tensor-on-tensor regression and TV analysis of variance (TANOVA) framework under EC errors is also demonstrated to better characterize gender, age, and ethnic origin than the usual TVN-based TANOVA in the celebrated labeled faces of the wild dataset.
The joint contour location method is an active learning technique that identifies input configurations that return pre-specified values of multiple independent computer experiments simultaneously. This code works with both Gaussian Processes and Deep Gaussian Processes
Pattern variations in supersonic jet flow through contoured nozzles under overexpansion conditions studied by schlieren photos and static pressures
A polychart contour plotter is used to reduce the data from all 19 antenna pattern charts to a one-chart form.
Hypersonic real-gas inviscid nozzle contours for nitrogen with tabulated flow properties for boundary layer effect calculation
Radar sensor system for acquisition of lunar surface data - Lunar contour mapping system
Data unfolding techniques for contoured semiconductor neutron spectrometer
Effects of boattail area contouring and simulated turbojet exhaust on loading and fuselage-tail component drag of twin-engine fighter-type airplane model
Design of optimized three-dimensional thrust nozzle contours
Topological approach to obtain ground track of aircraft using height over terrain and contour map
Optimum thrust nozzle contours for chemically reacting gas flows, obtaining set of partial differential equations for gas dynamic properties
Geometrical parameters, loading, and condition of momentlessness of radial guy net in hanging roof with momentless contour ring
Equilibrium, compatibility, and contour equations for bending in rectangular flexible plate rigidly clamped to elastic ribs