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At least 1,261 records · Page 70

Stochastic reconstructions of spectral functions: Application to lattice QCD

Here, we present a detailed study of the applications of two stochastic approaches, stochastic optimization method (SOM) and stochastic analytical inference (SAI), to extract spectral functions from Euclidean correlation functions. SOM has the advantage that it does not require prior information. On the other hand, SAI is a more generalized method based on Bayesian inference. Under mean field approximation SAI reduces to the often-used maximum entropy method (MEM), and for a specific choice of the prior SAI becomes equivalent to SOM. To test the applicability of these two stochastic methods to lattice QCD, Firstly, we apply these methods to various reasonably chosen model correlation functions, and present detailed comparisons of the reconstructed spectral functions obtained from SOM, SAI and MEM. Next, we present similar studies for charmonia correlation functions obtained from lattice QCD computations using clover-improved Wilson fermions on large, fine, isotropic lattices at 0:75 and 1:5 T c , T c being the deconfinement transition temperature of a pure gluon plasma. We find that SAI and SOM give consistent results to MEM at these two temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Boltzmann-conserving classical dynamics in quantum time-correlation functions: “Matsubara dynamics”

We show that a single change in the derivation of the linearized semiclassical-initial value representation (LSC-IVR or “classical Wigner approximation”) results in a classical dynamics which conserves the quantum Boltzmann distribution. We rederive the (standard) LSC-IVR approach by writing the (exact) quantum time-correlation function in terms of the normal modes of a free ring-polymer (i.e., a discrete imaginary-time Feynman path), taking the limit that the number of polymer beads N → ∞, such that the lowest normal-mode frequencies take their “Matsubara” values. The change we propose is to truncate the quantum Liouvillian, not explicitly in powers of ħ{sup 2} at ħ{sup 0} (which gives back the standard LSC-IVR approximation), but in the normal-mode derivatives corresponding to the lowest Matsubara frequencies. The resulting “Matsubara” dynamics is inherently classical (since all terms O(ħ{sup 2}) disappear from the Matsubara Liouvillian in the limit N → ∞) and conserves the quantum Boltzmann distribution because the Matsubara Hamiltonian is symmetric with respect to imaginary-time translation. Numerical tests show that the Matsubara approximation to the quantum time-correlation function converges with respect to the number of modes and gives better agreement than LSC-IVR with the exact quantum result. Matsubara dynamics is too computationally expensive to be applied to complex systems, but its further approximation may lead to practical methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Efficient analysis of small-angle scattering curves for large biomolecular assemblies using Monte Carlo methods

Structure elucidation from small-angle scattering curves of large biomolecular assemblies is notoriously challenging. This is because the simulation of high-resolution features in the structure of large macromolecular assemblies, such as de novo protein assemblies, is computationally demanding when it needs to cover a broad range of length scales. Conventional methods, such as the numerical approximation to the Debye equation or the use of spherical harmonics, do not scale well as the size of the assembly increases, which limits their application to small structures (e.g. individual proteins). This work explores the effectiveness of a Monte Carlo method to simulate and fit scattering curves for large biomolecular assemblies spanning over ranges covering atomic and molecular detail (e.g. spacing and orientation of proteins in an assembly) as well as large-scale (hundreds of nanometres) features. Owing to its speed and scalability, it can be combined with a fitting algorithm to extract structural features from experimental small-angle scattering curves in biomolecular assemblies that are otherwise intractable for interpretation. This work first demonstrates the effectiveness of the tool using experimental small-angle X-ray scattering (SAXS) data from tile-like proteins that assemble into 1D tube-like macromolecular structures. Here, the diameter distribution of tubes is extracted from SAXS fits, and this is quantitatively compared with distributions from electron microscopy. SAXS data are also obtained from 2D sheet-like protein assemblies, and the proposed method is used to quantify structural features such as the separation distance between protein building blocks and the flexing of the sheet. An open-source implementation of the methodology is provided for use in a broad range of biological systems involving multi-scale scattering analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Homogenization method based on the inverse problem

We present a method for deriving homogeneous multi-group cross sections to replace a heterogeneous region's multi-group cross sections; providing that the fluxes and the currents on the external boundary, and the region averaged fluxes are preserved. The method is developed using diffusion approximation to the neutron transport equation in a symmetrical slab geometry. Assuming that the boundary fluxes are given, two response matrices (RMs) can be defined. The first derives the boundary current from the boundary flux, the second derives the flux integral over the region from the boundary flux. Assuming that these RMs are known, we present a formula which reconstructs the multi-group cross-section matrix and the diffusion coefficients from the RMs of a homogeneous slab. Applying this formula to the RMs of a slab with multiple homogeneous regions yields a homogenization method; which produce such homogenized multi-group cross sections and homogenized diffusion coefficients, that the fluxes and the currents on the external boundary, and the region averaged fluxes are preserved. The method is based on the determination of the eigenvalues and the eigenvectors of the RMs. We reproduce the four-group cross section matrix and the diffusion constants from the RMs in numerical examples. We give conditions for replacing a heterogeneous region by a homogeneous one so that the boundary current and the region-averaged flux are preserved for a given boundary flux. (authors)

97 MATHEMATICS AND COMPUTING↗

Precise and direct method for the measurement of the torsion spring constant of the atomic force microscopy cantilevers

A direct method for the evaluation of the torsional spring constants of the atomic force microscope cantilevers is presented in this paper. The method uses a nanoindenter to apply forces at the long axis of the cantilever and in the certain distance from it. The torque vs torsion relation is then evaluated by the comparison of the results of the indentations experiments at different positions on the cantilever. Next, this relation is used for the precise determination of the torsional spring constant of the cantilever. The statistical analysis shows that the standard deviation of the calibration measurements is equal to approximately 1%. Furthermore, a simple method for calibration of the photodetector’s lateral response is proposed. The overall procedure of the lateral calibration constant determination has the accuracy approximately equal to 10%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dual-map framework for noise characterization of quantum computers

In order to understand the capabilities and limitations of quantum computers, it is necessary to develop methods that efficiently characterize and benchmark error channels present on these devices. In this paper, we present a method that faithfully reconstructs a marginal (local) approximation of the effective noise (MATEN) channel, that acts as a single layer at the end of the circuit. We first introduce a dual-map framework that allows us to analytically derive expectation values of observables with respect to noisy circuits. These findings are supported by numerical simulations of the quantum approximate optimization algorithm (QAOA) that also justify the MATEN, even in the presence of nonlocal errors that occur during a circuit. Finally, we demonstrate the performance of the method on Rigetti's Aspen-11 quantum computer for QAOA circuits up to six qubits, successfully predicting the observed measurements on a majority of the qubits.

Sud, James↗

Rate constants of chemical reactions from semiclassical transition state theory in full and one dimension

Semiclassical Transition State Theory (SCTST), a method for calculating rate constants of chemical reactions, offers gains in computational efficiency relative to more accurate quantum scattering methods. In full-dimensional (FD) SCTST, reaction probabilities are calculated from third and fourth potential derivatives along all vibrational degrees of freedom. However, the computational cost of FD SCTST scales unfavorably with system size, which prohibits its application to larger systems. In this study, the accuracy and efficiency of 1-D SCTST, in which only third and fourth derivatives along the reaction mode are used, are investigated in comparison to those of FD SCTST. Potential derivatives are obtained from numerical ab initio Hessian matrix calculations at the MP2/cc-pVTZ level of theory, and Richardson extrapolation is applied to improve the accuracy of these derivatives. Reaction barriers are calculated at the CCSD(T)/cc-pVTZ level. Results from FD SCTST agree with results from previous theoretical and experimental studies when Richardson extrapolation is applied. Results from our implementation of 1-D SCTST, which uses only 4 single-point MP2/cc-pVTZ energy calculations in addition to those for conventional TST, agree with FD results to within a factor of 5 at 250 K. This degree of agreement and the efficiency of the 1-D method suggest its potential as a means of approximating rate constants for systems too large for existing quantum scattering methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Least-Squares-Based Weak Galerkin Finite Element Method for Second Order Elliptic Equations

Here, in this article, we introduce a least-squares-based weak Galerkin finite element method for the second order elliptic equation. This new method is shown to provide very accurate numerical approximations for both the primal and the flux variables. In contrast to other existing least-squares finite element methods, this new method allows us to use discontinuous approximating functions on finite element partitions consisting of arbitrary polygon/polyhedron shapes. We also develop a Schur complement algorithm for the resulting discretization problem by eliminating all the unknowns that represent the solution information in the interior of each element. Optimal order error estimates for both the primal and the flux variables are established. An extensive set of numerical experiments are conducted to demonstrate the robustness, reliability, flexibility, and accuracy of the least-squares-based weak Galerkin finite element method. Finally, the numerical examples cover a wide range of applied problems, including singularly perturbed reaction-diffusion equations and the flow of fluid in porous media with strong anisotropy and heterogeneity.

nite element methods↗

A radial basis function Galerkin method for inhomogeneous nonlocal diffusion

We introduce a discretization for a nonlocal diffusion problem using a localized basis of radial basis functions. The stiffness matrix entries are assembled by a special quadrature routine unique to the localized basis. Combining the quadrature method with the localized basis produces a well-conditioned, sparse, symmetric positive definite stiffness matrix. We demonstrate that both the continuum and discrete problems are well-posed and present numerical results for the convergence behavior of the radial basis function method. As a result, we explore approximating the solution to anisotropic differential equations by solving anisotropic nonlocal integral equations using the radial basis function method.

97 MATHEMATICS AND COMPUTING↗

EquilTheTA: Thermodynamic and transport properties of complex equilibrium plasmas

EquilTheTA (EQUILibrium for plasma THErmodynamics and Transport Applications) is a web-based software which calculates chemical equilibrium product concentrations from any set of reactants and determines thermodynamic and transport properties for the product mixture in wide temperature and pressure ranges. The program calculates chemical equilibrium by using a hierarchical approach, thermodynamic properties and transport coefficients starting from recent and accurate databases of atomic and molecular energy levels and collision integrals. In the calculations, Debye length and cut-off are consistently updated and virial corrections (up to third order) can be considered. Transport coefficients are calculated by using high order approximations of the Chapman-Enskog method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On the ground state calculation of a many-body system using a self-consistent basis and quasi-Monte Carlo: An application to water hexamer

Given a quantum many-body system, the Self-Consistent Phonons (SCP) method provides an optimal harmonic approximation by minimizing the free energy. In particular, the SCP estimate for the vibrational ground state (zero temperature) appears to be surprisingly accurate. We explore the possibility of going beyond the SCP approximation by considering the system Hamiltonian evaluated in the harmonic eigenbasis of the SCP Hamiltonian. It appears that the SCP ground state is already uncoupled to all singly- and doubly-excited basis functions. So, in order to improve the SCP result at least triply-excited states must be included, which then reduces the error in the ground state estimate substantially. For a multidimensional system two numerical challenges arise, namely, evaluation of the potential energy matrix elements in the harmonic basis, and handling and diagonalizing the resulting Hamiltonian matrix, whose size grows rapidly with the dimensionality of the system. Using the example of water hexamer we demonstrate that such calculation is feasible, i.e., constructing and diagonalizing the Hamiltonian matrix in a triply-excited SCP basis, without any additional assumptions or approximations. Our results indicate particularly that the ground state energy differences between different isomers (e.g., cage and prism) of water hexamer are already quite accurate within the SCP approximation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-Level Transport Methods with Independent Discretization

In this proposal, we introduce two-level nonlinear iteration methods for the transport equation in 1D slab geometry approximated by means of the linear discontinuous finite element method (LDFEM). We develop transport schemes based on the quasidiffusion (QD) method in which the low-order QD (LOQD) equations are discretized by the linear continuous finite element method (LCFEM). This requires a mapping of the LCFEM low-order solution to the LDFEM high-order solution to define the scattering term. Several mappings are proposed and analyzed. Another suggested transport discretization scheme is based on the step characteristics for the transport equation and LCFEM for the LOQD equations. We also develop new nonlinear synthetic acceleration (NSA) methods based on the LCFEM discretization of the QD equation. To gain iterative stability, the NSA algorithms are combined with the nonlinear Krylov acceleration method. We present numerical results that demonstrate performance and basic properties of the proposed discretization schemes and iterative solution methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multiphysics Degradation Modeling of Energy Storage Materials via RKPM with a Neural Network-Enhancement

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

electro-chemo-mechanical coupling↗

First principles study of the structural, elastic, electronic and phonon properties of CdX{sub 2}O{sub 4} (X=Al, Ga, In) spinel-type oxides

We have performed ab-initio calculations of the structural, electronic, elastic and dynamical properties for the spinel compounds CdX{sub 2}O{sub 4} (X=Al, Ga, In) using the plane wave pseudo-potential method within the generalized gradient approximation (GGA). The calculated lattice parameters, elastic constants for these compounds are in good agreement with the previous calculated values. The computed direct band gaps of CdAl{sub 2}O{sub 4}, CdGa{sub 2}O{sub 4} and CdIn{sub 2}O{sub 4} are 2.90 eV, 1.92 eV and 1.16 eV, respectively. The lattice vibrations were calculated by direct method. The calculated phonon dispersion curves show that all compounds are dynamically stable in the spinel structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Lattice QED in an external magnetic field: Evidence for dynamical chiral symmetry breaking

We simulate quantum electrodynamics (QED) in a strong constant homogeneous external magnetic field on a Euclidean space-time lattice using the rational hybrid Monte Carlo method, developed for simulating lattice quantum chromodynamics (QCD). Our primary goal is to measure the chiral condensate in the limit when the input electron mass m is zero. We observe a nonzero value, indicating that the external magnetic field catalyzes chiral symmetry breaking as predicted by approximate truncated Schwinger-Dyson methods. Such behavior is associated with dominance by the lowest Landau level which causes the effective dimensional reduction from 3 + 1 dimensions to 1 + 1 dimensions for charged particles (electrons and positrons) where the attractive forces of QED can produce chiral symmetry breaking with a dynamical electron mass and associated chiral condensate. Since our lattice simulations use bare (lattice) parameters, while the Schwinger-Dyson analyses work with renormalized quantities, direct numerical comparison will require renormalization of our lattice results. Published by the American Physical Society 2024

Kogut, J. B. (ORCID:000000030151548X)↗

Photonic band structures of one-dimensional photonic crystals doped with plasma

The photonic band structures (PBSs) of oblique incidence propagation in one-dimensional plasma-doped photonic crystals (PCs) are investigated carefully. When the lattice constant of plasma-doped PCs is less than the incident wavelength, the PC becomes anisotropic. Therefore, the dielectric constant of PC is converted into a complex tensor dielectric constant. This determines the PBSs of PCs. In the present paper, one-dimensional PCs are taken as an example to study both normal and absorption PBSs. Using both the effective medium approximation and the transfer matrix method, we can derive the dispersion relation for PCs. The dependence of the plasma filling factor on the effective dielectric constant and PBSs is calculated and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Variational Nodal Approach to 2D/1D Pin Resolved Neutron Transport for Pressurized Water Reactors

A two-dimensional/one-dimensional (2D/1D) variational nodal approach is presented for pressurized water reactor core calculations without fuel-moderator homogenization. A 2D/1D approximation to the within-group neutron transport equation is derived and converted to an even-parity form. The corresponding nodal functional is presented and discretized to obtain response matrix equations. Within the nodes, finite elements in the x-y plane and orthogonal functions in z are used to approximate the spatial flux distribution. On the radial interfaces, orthogonal polynomials are employed; on the axial interfaces, piecewise constants corresponding to the finite elements eliminate the interface homogenization that has been a challenge for method of characteristics (MOC)-based 2D/1D approximations. The angular discretization utilizes an even-parity integral method within the nodes, and low-order spherical harmonics (P N ) on the axial interfaces. The x-y surfaces are treated with high-order P N combined with quasi-reflected interface conditions. Furthermore, the method is applied to the C5G7 benchmark problems and compared to Monte Carlo reference calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Operator inference for non-intrusive model reduction with quadratic manifolds

This paper proposes a novel approach for learning a data-driven quadratic manifold from high-dimensional data, then employing this quadratic manifold to derive efficient physics-based reduced-order models. The key ingredient of the approach is a polynomial mapping between high-dimensional states and a low-dimensional embedding. This mapping consists of two parts: a representation in a linear subspace (computed in this work using the proper orthogonal decomposition) and a quadratic component. The approach can be viewed as a form of data-driven closure modeling, since the quadratic component introduces directions into the approximation that lie in the orthogonal complement of the linear subspace, but without introducing any additional degrees of freedom to the low-dimensional representation. Combining the quadratic manifold approximation with the operator inference method for projection-based model reduction leads to a scalable non-intrusive approach for learning reduced-order models of dynamical systems. Further, applying the new approach to transport-dominated systems of partial differential equations illustrates the gains in efficiency that can be achieved over approximation in a linear subspace.

42 ENGINEERING↗