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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A numerical Poisson solver with improved radial solutions for a self-consistent locally scaled self-interaction correction method

Abstract The universal applicability of density functional approximations is limited by self-interaction error made by these functionals. Recently, a novel one-electron self-interaction-correction (SIC) method that uses an iso-orbital indicator to apply the SIC at each point in space by scaling the exchange-correlation and Coulomb energy densities was proposed. The locally scaled SIC (LSIC) method is exact for the one-electron densities, and unlike the well-known Perdew–Zunger SIC (PZSIC) method recovers the uniform electron gas limit of the uncorrected density functional approximation, and reduces to PZSIC method as a special case when isoorbital indicator is set to the unity. Here, we present a numerical scheme that we have adopted to evaluate the Coulomb potential of the electron density scaled by the iso-orbital indicator required for the self-consistent LSIC calculations. After analyzing the behavior of the finite difference method (FDM) and the green function solution to the radial part of the Poisson equation, we adopt a hybrid approach that uses the FDM for the Coulomb potential due to the monopole and the GF for all higher-order terms. The performance of the resultant hybrid method is assessed using a variety of systems. The results show improved accuracy than earlier numerical schemes. We also find that, even with a generic set of radial grid parameters, accurate energy differences can be obtained using a numerical Coulomb solver in standard density functional studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Transport error estimation using residual Monte Carlo

The residual Monte Carlo (RMC) method is also known in the literature as sequential Monte Carlo and reduced-source Monte Carlo. Given a Monte Carlo method for solving a linear equation and an approximate solution to that system, the residual method enables use of essentially the same Monte Carlo algorithm to directly compute the additive error or “defect” associated with the approximate solution. As the size of the defect decreases relative to the size of the solution, the residual Monte Carlo method becomes increasingly efficient relative to the standard Monte Carlo (SMC) method. Here we present a new RMC algorithm for evaluating the space-angle error in S n radiation transport solutions, and provide computational examples demonstrating that it can be far more efficient than SMC for this purpose. Herein we also describe a particular pitfall that must be avoided if RMC is to be efficient, and explain why the performance of RMC can significantly differ between different transport problems and different quantities of interest for the same problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Density Functional Theory Study on Electronic Structures and Magnetism for Nitrogen-Doped ZnS

Using the full-potential linearized augmented plane wave method, together with the generalized gradient approximation and modified Becke-Johnson as correlation potential, the electronic structures and magnetism for nitrogen-doped ZnS are investigated. Based on the generalized gradient approximation, calculations show nitrogen-substituting sulfur (N{sub S}) would induce the ZnS to be paramagnetic metal. As the band gap increasing to the experimental results (obtained by the modified Becke-Johnson potential), the N{sub S} defects would induce the ZnS to be a ferromagnetic metal. The total magnetic moment for ZnS supercell with single N{sub S} defect is 0.85 μ{sub B}. Positive chemical pair interactions imply that N{sub S} defects would form homogeneous distribution in ZnS host. Sulfur vacancies would give rise to the ZnS with N{sub S} defects system losing the magnetism. Moderate formation energy (0.71 eV) indicates ZnS with N{sub S} defects could be fabricated experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

An iterative dynamic chemical stiffness removal method for reacting flow simulations

Abstract An iterative dynamic chemical stiffness removal method (IDCSR) based on quasi-steady-state approximation (QSSA) is proposed. The IDCSR method is built on a previously developed non-iterative method which has proved to work well for small timestep sizes. A novel iterative procedure is designed in IDCSR to enable explicit time integration of stiff chemistry at relatively large timestep sizes relevant to practical reacting flow simulations. The effectiveness of the iterative procedure is first demonstrated with a toy problem and homogeneous auto-ignition with fixed integration step sizes, showing that larger timestep sizes can be allowed for explicit time integration using IDCSR compared with the previous non-iterative method. IDCSR is then compared with existing explicit chemistry solvers for simulations of homogeneous auto-ignition and shows similar or lower computational cost but significantly higher accuracy across a wide range of timestep sizes. IDCSR is further combined with an automatic adaptive time-stepping scheme for simulations of 0-D homogeneous auto-ignition and a 2-D laminar lifted n -dodecane jet flame. For the 0-D auto-ignition simulations, IDCSR is shown to reduce both the error (by 43%–90%) and computational cost (by 6–15 times) compared with existing explicit solvers, while achieving speed-up factors of up to 400 compared with VODE for a wide range of timestep sizes and reaction mechanisms. For the 2-D jet flame simulations, speed-up factors of 15 and 31 for chemistry integration, and 5 and 9 for overall simulation, are achieved by IDCSR compared with CVODE with and without analytic Jacobian, respectively.

Xu, Chao (ORCID:0000000153074159)↗
DOE OSTI2015

Multi-layer Lanczos iteration approach to calculations of vibrational energies and dipole transition intensities for polyatomic molecules

We report a rigorous full dimensional quantum dynamics algorithm, the multi-layer Lanczos method, for computing vibrational energies and dipole transition intensities of polyatomic molecules without any dynamics approximation. The multi-layer Lanczos method is developed by using a few advanced techniques including the guided spectral transform Lanczos method, multi-layer Lanczos iteration approach, recursive residue generation method, and dipole-wavefunction contraction. The quantum molecular Hamiltonian at the total angular momentum J = 0 is represented in a set of orthogonal polyspherical coordinates so that the large amplitude motions of vibrations are naturally described. In particular, the algorithm is general and problem-independent. An application is illustrated by calculating the infrared vibrational dipole transition spectrum of CH{sub 4} based on the ab initio T8 potential energy surface of Schwenke and Partridge [Spectrochimica Acta, Part A 57, 887 (2001)] and the low-order truncated ab initio dipole moment surfaces of Yurchenko et al. [J. Mol. Spectrosc. 291, 69 (2013)]. A comparison with experiments is made. The algorithm is also applicable for Raman polarizability active spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Electronic structure and optical properties of quantum crystals from first principles calculations in the Born–Oppenheimer approximation

In this work, we develop a formalism to accurately account for the renormalization of the electronic structure due to quantum and thermal nuclear motions within the Born–Oppenheimer approximation. We focus on the fundamental energy gap obtained from electronic addition and removal energies from quantum Monte Carlo calculations in either the canonical or grand-canonical ensembles. The formalism applies as well to effective single electron theories such as those based on density functional theory. We show that the electronic (Bloch) crystal momentum can be restored by marginalizing the total electron–ion wave function with respect to the nuclear equilibrium distribution, and we describe an explicit procedure to establish the band structure of electronic excitations for quantum crystals within the Born–Oppenheimer approximation. Based on the Kubo–Greenwood equation, we discuss the effects of nuclear motion on optical conductivity. Our methodology applies to the low temperature regime where nuclear motion is quantized and, in general, differs from the semi-classical approximation. We apply our method to study the electronic structure of C2/c-24 crystalline hydrogen at 200 K and 250 GPa and discuss the optical absorption profile of hydrogen crystals at 200 K and carbon diamond at 297 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Determination of nuclear PDFs using Markov chain Monte Carlo methods

Global QCD analyses of nuclear parton distribution functions (nPDFs) have traditionally relied on the Hessian method for uncertainty estimation. However, the inherent Gaussian approximation and reliance on local curvature often prove insufficient for nPDF fits, which are frequently characterized by limited data constraints and non-Gaussian likelihoods. In this paper, we present the first nPDF determination based on Markov Chain Monte Carlo (MCMC) techniques, implemented within the nCTEQ framework using an adaptive Metropolis-Hastings algorithm. The MCMC approach enables a direct mapping of the posterior distribution and reveals a highly nontrivial parameter-space structure, including multiple modes and pronounced non-Gaussian behavior, particularly for the valence PDFs. We perform the first single-nucleus global analysis of lead PDFs using exclusively lead data and compare it to a multi-nuclei fit employing a standard analytic A dependence. The inclusion of lighter nuclei reduces quark uncertainties and modifies the shape of the lead PDFs, while leaving the gluon distribution largely unaffected. A complementary Hessian analysis exposes systematic limitations of the Gaussian approximation. Our results demonstrate that MCMC methods provide a more reliable framework for uncertainty quantification in nPDF determinations.

Derakhshanian, N. [Institute of Nuclear Physics Po↗
DOE OSTI2025

Low-energy enhancement of the magnetic dipole radiation in odd-mass lanthanides

We compute the magnetic dipole (M1) $\gamma$-ray strength functions ($\gamma$SF) for the odd-mass lanthanides $^{\textrm{143-151}}$Nd and $^{\textrm{147-153}}$Sm using the shell-model Monte Carlo method in combination with the static-path approximation and the maximum-entropy method. In particular, we quantify the statistical uncertainties in the calculated M1 $\gamma$SFs and show that they are under control for the excitation energies relevant to the experiments despite a Monte Carlo sign problem that originates in the projection onto an odd number of neutrons. We identify a low-energy enhancement (LEE) in the M1 $\gamma$SFs of these odd-mass lanthanides, which was recently observed experimentally in some of them. We also find a scissors mode resonance (SR) in the strongly deformed isotopes. We observe that the decrease in the LEE strength with neutron number along an isotopic chain is compensated for by an increase in the SR strength in the deformed nuclei. Furthermore, we compare our results with recent experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Practical aspects and uncertainty analysis of biological effective dose (BED) regarding its three-dimensional calculation in multiphase radiotherapy treatment plans

Purpose: There is a growing interest in the radiation oncology community to use the biological effective dose (BED) rather than the physical dose (PD) in treatment plan evaluation and optimization due to its stronger correlation with radiobiological effects. Radiotherapy patients may receive treatments involving a single only phase or multiple phases (e.g., primary and boost). Since most treatment planning systems cannot calculate the analytical BED distribution in multiphase treatments, an approximate multiphase BED expression, which is based on the total physical dose distribution, has been used. The purpose of this paper is to reveal the mathematical properties of the approximate BED formulation, relative to the true BED. Methods: The mathematical properties of the approximate multiphase BED equation are analyzed and evaluated. In order to better understand the accuracy of the approximate multiphase BED equation, the true multiphase BED equation was derived and the mathematical differences between the true and approximate multiphase BED equations were determined. The magnitude of its inaccuracies under common clinical circumstances was also studied. All calculations were performed on a voxel-by-voxel basis using the three-dimensional dose matrices. Results: Results showed that the approximate multiphase BED equation is accurate only when the dose-per-fractions (DPFs) in both the first and second phases are equal, which occur when the dose distribution does not significantly change between the phases. In the case of heterogeneous dose distributions, which significantly vary between the phases, there are fewer occurrences of equal DPFs and hence the inaccuracy of the approximate multiphase BED is greater. These characteristics are usually seen in the dose distributions being delivered to organs at risk rather than to targets. Conclusions: The finding of this study indicates that the true multiphase BED equation should be implemented in the treatment planning systems due to the inconsistent accuracy of the approximate multiphase BED equation in most of the clinical situations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Cholesky-based experimental design for Gaussian process and kernel-based emulation and calibration.

Gaussian processes and other kernel-based methods are used extensively to construct approximations of multivariate data sets. The accuracy of these approximations is dependent on the data used. This paper presents a computationally efficient algorithm to greedily select training samples that minimize the weighted L p error of kernel-based approximations for a given number of data. The method successively generates nested samples, with the goal of minimizing the error in high probability regions of densities specified by users. The algorithm presented is extremely simple and can be implemented using existing pivoted Cholesky factorization methods. Training samples are generated in batches which allows training data to be evaluated (labeled) in parallel. For smooth kernels, the algorithm performs comparably with the greedy integrated variance design but has significantly lower complexity. Numerical experiments demonstrate the efficacy of the approach for bounded, unbounded, multi-modal and non-tensor product densities. We also show how to use the proposed algorithm to efficiently generate surrogates for inferring unknown model parameters from data using Bayesian inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Probing Ground-State Phase Transitions through Quench Dynamics

The study of quantum phase transitions requires the preparation of a many-body system near its ground state, a challenging task for many experimental systems. The measurement of quench dynamics, on the other hand, is now a routine practice in most cold atom platforms. Here we show that quintessential ingredients of quantum phase transitions can be probed directly with quench dynamics in integrable and nearly integrable systems. As a paradigmatic example, we study global quench dynamics in a transverse-field Ising model with either short-range or long-range interactions. When the model is integrable, we discover a new dynamical critical point with a nonanalytic signature in the short-range correlators. The location of the dynamical critical point matches that of the quantum critical point and can be identified using a finite-time scaling method. We extend this scaling picture to systems near integrability and demonstrate the continued existence of a dynamical critical point detectable at prethermal timescales. We quantify the difference in the locations of the dynamical and quantum critical points away from (but near) integrability. Thus, we demonstrate that this method can be used to approximately locate the quantum critical point near integrability. Furthermore, the scaling method is also relevant to experiments with finite time and system size, and our predictions are testable in near-term experiments with trapped ions and Rydberg atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Teleoperation for Nuclear Applications Considering Communication Delay and Uncertainty - 18205

Teleoperation in remote environment is of great interest in robotics. Advancement in communication technology has enabled safe execution of complex and life threatening tasks in network environment in teleoperation. Using bilateral teleoperation, the operator receives force feedback from the slave which provides an interactive feel of forces and smoother coordination. However, time delay across the communication link in sending the command signal from the master to the slave may cause instability to the system. In this research, we use the continuous pole placement method to address the time delay problem in teleoperation. Compared to approximation based and prediction based methods, this method shows improved robustness. Simulations and experiments show a stable and well synchronized control. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

On the Statistical Calibration of Physical Models

ABSTRACT We introduce a novel statistical calibration framework for physical models, relying on probabilistic embedding of model discrepancy error within the model. For clarity of illustration, we take the measurement errors out of consideration, calibrating a chemical model of interest with respect to a more detailed model, considered as “truth” for the present purpose. We employ Bayesian statistical methods for such model‐to‐model calibration and demonstrate their capabilities on simple synthetic models, leading to a well‐defined parameter estimation problem that employs approximate Bayesian computation. The method is then demonstrated on two case studies for calibration of kinetic rate parameters for methane air chemistry, where ignition time information from a detailed elementary‐step kinetic model is used to estimate rate coefficients of a simple chemical mechanism. We show that the calibrated model predictions fit the data and that uncertainty in these predictions is consistent in a mean‐square sense with the discrepancy from the detailed model data.

Sargsyan, K.↗
DOE OSTI2015

Study of multiband disordered systems using the typical medium dynamical cluster approximation

We generalize the typical medium dynamical cluster approximation to multiband disordered systems. Using our extended formalism, we perform a systematic study of the nonlocal correlation effects induced by disorder on the density of states and the mobility edge of the three-dimensional two-band Anderson model. We include interband and intraband hopping and an intraband disorder potential. Our results are consistent with those obtained by the transfer matrix and the kernel polynomial methods. We also apply the method to K x Fe 2-y Se 2 with Fe vacancies. Despite the strong vacancy disorder and anisotropy, we find the material is not an Anderson insulator. Moreover our results demonstrate the application of the typical medium dynamical cluster approximation method to study Anderson localization in real materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Identifying Important Ions and Positions in Mass Spectrometry Imaging Data Using CUR Matrix Decompositions

Mass spectrometry imaging enables label-free, high-resolution spatial mapping of the chemical composition of complex, biological samples. Typical experiments require selecting ions and/or positions from the images: ions for fragmentation studies to identify keystone compounds and positions for follow up validation measurements using microdissection or other orthogonal techniques. Unfortunately, with modern imaging machines, these must be selected from an overwhelming amount of raw data. Existing techniques to reduce the volume of data, the most popular of which are principle component analysis and non-negative matrix factorization, have the disadvantage that they return difficult-to-interpret linear combinations of actual data elements. In this work, we show that CX and CUR matrix decompositions can be used directly to address this selection need. CX and CUR matrix decompositions use empirical statistical leverage scores of the input data to provide provably good low-rank approximations of the measured data that are expressed in terms of actual ions and actual positions, as opposed to difficult-to-interpret eigenions and eigenpositions. We show that this leads to effective prioritization of information for both ions and positions. In particular, important ions can be found either by using the leverage scores as a ranking function and using a deterministic greedy selection algorithm or by using the leverage scores as an importance sampling distribution and using a random sampling algorithm; however, selection of important positions from the original matrix performed significantly better when they were chosen with the random sampling algorithm. Also, we show that 20 ions or 40 locations can be used to reconstruct the original matrix to a tolerance of 17% error for a widely studied image of brain lipids; and we provide a scalable implementation of this method that is applicable for analysis of the raw data where there are often more than a million rows and/or columns, which is larger than SVD-based low-rank approximation methods can handle. Lastly, these results introduce the concept of CX/CUR matrix factorizations to mass spectrometry imaging, describing their utility and illustrating principled algorithmic approaches to deal with the overwhelming amount of data generated by modern mass spectrometry imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantum-enhanced phase imaging without coincidence counting

Quantitative phase imaging provides a way to image transparent objects, such as biological cells, and measure their thickness. We report on a phase-imaging method that achieves twice the phase shift and approximately 1.7 times the spatial resolution of an equivalent spatially and temporally coherent classical quantitative phase-imaging system by using quantum interference between successive spontaneous parametric downconversion events in a nonlinear crystal. Furthermore, our method is approximately 1000 times faster than imaging the parametric downconversion photons in coincidence, which requires measurement times on the order of tens of hours. Our method may be useful for imaging sensitive transparent objects that require low illumination intensities at near-infrared and longer illumination wavelengths, such as photosensitive biological samples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The arbitrary‐order virtual element method for linear elastodynamics models: convergence, stability and dispersion‐dissipation analysis

Abstract We design the conforming virtual element method for the numerical approximation of the two‐dimensional elastodynamics problem. We prove stability and convergence of the semidiscrete approximation and derive optimal error estimates under h ‐ and p ‐refinement in both the energy and the L 2 norms. The performance of the proposed virtual element method is assessed on a set of different computational meshes, including nonconvex cells up to order four in the h ‐refinement setting. Exponential convergence is also experimentally observed under p ‐refinement. Finally, we present a dispersion‐dissipation analysis for both the semidiscrete and fully discrete schemes, showing that polygonal meshes behave as classical simplicial/quadrilateral grids in terms of dispersion‐dissipation properties.

Antonietti, Paola F.↗
DOE OSTI2015

Determination of recombination radius in Si for binary collision approximation codes

Displacement damage caused by ions or neutrons in microelectronic devices can have significant effect on the performance of these devices. Therefore, it is important to predict not only the displacement damage profile, but also its magnitude precisely. Analytical methods and binary collision approximation codes working with amorphous targets use the concept of displacement energy, the energy that a lattice atom has to receive to create a permanent replacement. It was found that this “displacement energy” is direction dependent; it can range from 12 to 32 eV in silicon. Obviously, this model fails in BCA codes that work with crystalline targets, such as Marlowe. Marlowe does not use displacement energy; instead, it uses lattice binding energy only and then pairs the interstitial atoms with vacancies. Then based on the configuration of the Frenkel pairs it classifies them as close, near, or distant pairs, and considers the distant pairs the permanent replacements. Unfortunately, this separation is an ad hoc assumption, and the results do not agree with molecular dynamics calculations. After irradiation, there is a prompt recombination of interstitials and vacancies if they are nearby, within a recombination radius. In order to implement this recombination radius in Marlowe, we used the comparison of MD and Marlowe calculation in a range of ion energies in single crystal silicon target. As a result, the calculations showed that a single recombination radius of ~7.4 Å in Marlowe for a range of ion energies gives an excellent agreement with MD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗