Deep Inelastic Structure Functions for Bound States in the Ladder Approximation
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Pham, T. N.↗
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Results for “functional approximation”
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Density functional theory of material design: fundamentals and applications—II
Abstract This is the second and the final part of the review on density functional theory (DFT), referred to as DFT-II. In the first review, DFT-I, we have discussed wavefunction-based methods, their complexity, and basics of density functional theory. In DFT-II, we focus on fundamentals of DFT and their implications for the betterment of the theory. We start our presentation with the exact DFT results followed by the concept of exchange-correlation (xc) or Fermi-Coulomb hole and its relationship with xc energy functional. We also provide the exact conditions for the xc-hole, xc-energy and xc-potential along with their physical interpretation. Next, we describe the extension of DFT for non-integer number of electrons, the piecewise linearity of total energy and discontinuity of chemical potential at integer particle numbers, and derivative discontinuity of the xc potential, which has consequences on fundamental gap of solids. After that, we present how one obtains more accurate xc energy functionals by going beyond the LDA. We discuss the gradient expansion approximation (GEA), generalized gradient approximation (GGA), and hybrid functional approaches to designing better xc energy functionals that give accurate total energies. However, these functionals fail to predict properties like the ionization potential and the band gap. Thus, we next describe different methods of modelling these potentials and results of their application for calculation of the band gaps of different solids to highlight accuracy of different xc potentials. Finally, we conclude with a glimpse on orbital-free density functional theory and the machine learning approach.
36 MATERIALS SCIENCE↗
Approximate Bisimulation-Based Reduction of Power System Dynamic Models
In this paper we propose approximate bisimulation relations and functions for reduction of power system dynamic models in differential- algebraic (descriptor) form. The full-size dynamic model is obtained by linearization of the nonlinear transient stability model. We generalize theoretical results on approximate bisimulation relations and bisimulation functions, originally derived for a class of constrained linear systems, to linear systems in descriptor form. An algorithm for transient stability assessment is proposed and used to determine whether the power system is able to maintain the synchronism after a large disturbance. Two benchmark power systems are used to illustrate the proposed algorithm and to evaluate the applicability of approximate bisimulation relations and bisimulation functions for reduction of the power system dynamic models.
Stankovic, AM↗
Motional displacements in proteins: The origin of wave-vector-dependent values
In the case of average mean-square displacement, r 2 , of H atoms in a protein, it is frequently determined using incoherent neutron-scattering experiments. r 2 is obtained from the observed elastic incoherent dynamic structure factor, S i (Q,ω =0), assuming the form S i (Q, ω =0) =exp( -Q 2 r 2 /3). Moreover, this is often referred to as the Gaussian approximation (GA) to S i (Q, ω =0). r 2 obtained in this way depends on the value of the wave vector, Q considered. Equivalently, the observed S i (Q, ω =0) deviates from the GA. We investigate the origin of the Q dependence of r 2 by evaluating the scattering functions in different approximations using molecular dynamics (MD) simulation of the protein lysozyme. We find that keeping only the Gaussian term in a cumulant expansion of S(Q, ω ) is an accurate approximation and is not the origin of the Q dependence of r 2 . We demonstrated by showing that the term beyond the Gaussian is negligible and that the GA is valid for an individual atom in the protein. Rather, the Q dependence (deviation from the GA) arises from the dynamical heterogeneity of the H in the protein. Specifically it arises from representing, in the analysis of data, this diverse dynamics by a single average scattering center that has a single, average r 2 . The observed Q dependence of r 2 can be used to provide information on the dynamical heterogeneity in proteins.
59 BASIC BIOLOGICAL SCIENCES↗
Efficient prediction of time- and angle-resolved photoemission spectroscopy measurements on a nonequilibrium BCS superconductor
We study how time- and angle-resolved photoemission (tr-ARPES) reveals the dynamics of BCS-type, s -wave superconducting systems with time-varying order parameters. Approximate methods are discussed, based on previous approaches to either optical conductivity or quantum dot transport, to enable computationally efficient prediction of photoemission spectra. One use of such predictions is to enable extraction of the underlying order parameter dynamics from experimental data, which is topical given the rapidly growing use of tr-ARPES in studying unconventional superconductivity. The methods considered model the two-time lesser Green's functions with an approximated lesser self-energy that describes relaxation by coupling of the system to two types of baths. The approach primarily used here also takes into consideration the relaxation of the excited states into equilibrium by explicitly including the level-broadening of the retarded and advanced Green's functions. Here, we present equilibrium and nonequilibrium calculations of tr-ARPES spectrum from our model and discuss the signatures of different types of superconducting dynamics.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
First-principles calculations of the electronic and structural properties of GaSb
In this paper, we carried out first-principles calculations in order to investigate the structural and electronic properties of the binary compound gallium antimonide (GaSb). This theoretical study was carried out using the Density Functional Theory within the plane-wave pseudopotential method. The effects of exchange and correlation (XC) were treated using the functional Local Density Approximation (LDA), generalized gradient approximation (GGA): Perdew–Burke–Ernzerhof (PBE), Perdew-Burke-Ernzerhof revised for solids (PBEsol), Perdew-Wang91 (PW91), revised Perdew–Burke–Ernzerhof (rPBE), Armiento–Mattson 2005 (AM05) and meta-generalized gradient approximation (meta-GGA): Tao–Perdew–Staroverov–Scuseria (TPSS) and revised Tao–Perdew–Staroverov–Scuseria (RTPSS) and modified Becke-Johnson (MBJ). We calculated the densities of state (DOS) and band structure with different XC potentials identified and compared them with the theoretical and experimental results reported in the literature. It was discovered that functional: LDA, PBEsol, AM05 and RTPSS provide the best results to calculate the lattice parameters (a) and bulk modulus (B{sub 0}); while for the cohesive energy (E{sub coh}), functional: AM05, RTPSS and PW91 are closer to the values obtained experimentally. The MBJ, Rtpss and AM05 values found for the band gap energy is slightly underestimated with those values reported experimentally.
36 MATERIALS SCIENCE↗
A numerical method for deriving shape functions of nanoparticles for pair distribution function refinements
We report that in the structural refinement of nanoparticles, discrete atomistic modeling can be used for small nanocrystals (< 15 nm), but becomes computationally unfeasible at larger sizes, where instead unit-cell-based small-box modeling is usually employed. However, the effect of the nanocrystal's shape is often ignored or accounted for with a spherical model regardless of the actual shape due to the complexities of solving and implementing accurate shape effects. Recent advancements have provided a way to determine the shape function directly from a pair distribution function calculated from a discrete atomistic model of any given shape, including both regular polyhedra (e.g. cubes, spheres, octahedra) and anisotropic shapes (e.g. rods, discs, ellipsoids) [Olds et al. (2015). J. Appl. Cryst. 48, 1651–1659], although this approach is still limited to small size regimes due to computational demands. In order to accurately account for the effects of nanoparticle size and shape in small-box refinements, a numerical or analytical description is needed. This article presents a methodology to derive numerical approximations of nanoparticle shape functions by fitting to a training set of known shape functions; the numerical approximations can then be employed on larger sizes yielding a more accurate and physically meaningful refined nanoparticle size. Lastly, the method is demonstrated on a series of simulated and real data sets, and a table of pre-calculated shape function expressions for a selection of common shapes is provided.
36 MATERIALS SCIENCE↗
Chaos control of the micro-electro-mechanical resonator by using adaptive dynamic surface technology with extended state observer
This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Putting tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Impact of Surface Chemistry of Ultrasmall Superparamagnetic Iron Oxide Nanoparticles on Protein Corona Formation and Endothelial Cell Uptake, Toxicity, and Barrier Function
Ultrasmall superparamagnetic iron oxide nanoparticles (USPIONs) have been investigated for biomedical applications, including novel contrast agents, magnetic tracers for tumor imaging, targeted drug delivery vehicles, and magneto-mechanical actuators for hyperthermia and thrombolysis. Despite significant progress, recent clinical reports have raised concerns regarding USPION safety related to endothelial cell dysfunction; however, there is limited information on factors contributing to these clinical responses. The influence of USPION surface chemistry on nanoparticle interactions with proteins may impact endothelial cell function leading to adverse responses. Therefore, the goal of this study was to assess the effects of carboxyl-functionalized USPION (CU) or amine-functionalized USPION (AU) (approximately 30 nm diameter) on biological responses in human coronary artery endothelial cells. Increased protein adsorption was observed for AU compared with CU after exposure to serum proteins. Exposure to CU, but not AU, resulted in a concentration-dependent decrease in cell viability and perinuclear accumulation inside cytoplasmic vesicles. Internalization of CU was correlated with endothelial cell functional changes under non-cytotoxic conditions, as evidenced by a marked decreased expression of endothelial-specific adhesion proteins (eg, vascular endothelial-cadherin and platelet endothelial cell adhesion molecule-1) and increased endothelial permeability. Evaluation of downstream signaling indicated endothelial permeability is associated with actin cytoskeleton remodeling, possibly elicited by intracellular events involving reactive oxygen species, calcium ions, and the nanoparticle cellular uptake pathway. This study demonstrated that USPION surface chemistry significantly impacts protein adsorption and endothelial cell uptake, viability, and barrier function. This information will advance the current toxicological profile of USPION and improve development, safety assessment, and clinical outcomes of USPION-enabled medical products.
Toxicology↗
A degradation function consistent with Cocks–Ashby porosity kinetics
Here, the load carrying capacity of ductile materials degrades as a function of porosity, stress state and strain-rate. The effect of these variables on porosity kinetics is captured by the Cocks–Ashby model; however, the Cocks–Ashby model does not account for material degradation directly. This work uses a yield criteria to form a degradation function that is consistent with Cocks–Ashby porosity kinetics and is a function of porosity, stress state and strain-rate dependence. Approximations of this degradation function for pure hydrostatic stress states are also explored.
36 MATERIALS SCIENCE↗
Ground state wave functions for single-band Hubbard models from the Gutzwiller conjugate gradient minimisation theory
The Gutzwiller conjugate gradient minimisation (GCGM) theory is an ab initio quantum many-body theory for computing the ground-state properties of infinite systems. Previous applications of GCGM provides satisfying accuracy of ground-state energy of Hubbard models. In the current work, we address the problem of whether the obtained wave function is a good approximation for the true ground state by comparing the correlation functions with the benchmark data. Additionally, our results confirms the accuracy of the reproduced ground state of the regular Hubbard model, but with some exception for the frustrated Hubbard model.
74 ATOMIC AND MOLECULAR PHYSICS↗
SELF-SIMILAR DYNAMICAL RELAXATION OF DARK MATTER HALOS IN AN EXPANDING UNIVERSE
We investigate the structure of cold dark matter halos using advanced models of spherical collapse and accretion in an expanding universe. These are based on solving time-dependent equations for the moments of the phase-space distribution function in the fluid approximation; our approach includes non-radial random motions and, most importantly, an advanced treatment of both dynamical relaxation effects that take place in the infalling matter: phase-mixing associated with shell crossing and collective collisions related to physical clumpiness. We find self-similar solutions for the spherically averaged profiles of mass density {rho}(r), pseudo phase-space density Q(r), and anisotropy parameter {beta}(r). These profiles agree with the outcomes of state-of-the-art N-body simulations in the radial range currently probed by the latter; at smaller radii, we provide specific predictions. In the perspective provided by our self-similar solutions, we link the halo structure to its two-stage growth history and propose the following picture. During the early fast collapse of the inner region dominated by a few merging clumps, efficient dynamical relaxation plays a key role in producing closely universal mass density and pseudo phase-space density profiles; in particular, these are found to depend only weakly on the detailed shape of the initial perturbation and the related collapse times. The subsequent inside-out growth of the outer regions feeds on the slow accretion of many small clumps and diffuse matter; thus the outskirts are only mildly affected by dynamical relaxation but are more sensitive to asymmetries and cosmological variance.
79 ASTRONOMY AND ASTROPHYSICS↗
FDE-vdW: A van der Waals inclusive subsystem density-functional theory
We present a formally exact van der Waals inclusive electronic structure theory, called FDE-vdW, based on the Frozen Density Embedding formulation of subsystem Density-Functional Theory. In subsystem DFT, the energy functional is composed of subsystem additive and non-additive terms. We show that an appropriate definition of the long-range correlation energy is given by the value of the non-additive correlation functional. This functional is evaluated using the fluctuation–dissipation theorem aided by a formally exact decomposition of the response functions into subsystem contributions. FDE-vdW is derived in detail and several approximate schemes are proposed, which lead to practical implementations of the method. We show that FDE-vdW is Casimir-Polder consistent, i.e., it reduces to the generalized Casimir-Polder formula for asymptotic inter-subsystems separations. Pilot calculations of binding energies of 13 weakly bound complexes singled out from the S22 set show a dramatic improvement upon semilocal subsystem DFT, provided that an appropriate exchange functional is employed. The convergence of FDE-vdW with basis set size is discussed, as well as its dependence on the choice of associated density functional approximant.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Description of quasiparticle and satellite properties via cumulant expansions of the retarded one-particle Green's function
A cumulant-based GW approximation for the retarded one-particle Green's function is proposed, motivated by an exact relation between the improper Dyson self-energy and the cumulant generating function. We explore qualitative aspects of this method within a simple one-electron independent phonon model, where it is seen that the method preserves the energy moment of the spectral weight while also reproducing the exact Green's function in the weak-coupling limit. For the three-dimensional electron gas, this method predicts multiple satellites at the bottom of the band, albeit with inaccurate peak spacing. But, its quasiparticle properties and correlation energies are more accurate than both previous cumulant methods and standard G0W0. These results point to features that may be exploited within the framework of cumulant-based methods and suggest promising directions for future exploration and improvements of cumulant-based GW approaches.
36 MATERIALS SCIENCE↗
Evaluating the Feasibility of Measuring and Analyzing Strain Caused by Changes in Barometric Pressure in the Vadose Zone
Changes in barometric pressure propagate into the subsurface where they can affect water level measurements in wells and cause vertical strain. Previous strain sensors were developed to measure vertical strain, but they were limited to measurements at a single depth, making it difficult to evaluate strains from a migrating pressure wave. Technology known as Coherence-length-gated Microwave Photonics Interferometry (CMPI) uses optical fiber sensors to measure strain at multiple locations. It has the potential to detect strain caused by variations in barometric pressure at multiple depths in the subsurface. The goal of this study is to evaluate the feasibility of using this technology to record the changes in vertical strain in the vadose zone from small fluctuations in air pressure. Propagation of these air pressure fluctuations is affected by hydrogeological properties such as water content and permeability. A second goal of this study is to evaluate how these properties affect the air pressure distribution, strain, and gas-phase diffusivity with a long-term goal of using strain to monitor the vadose zone. The focus of this study is on a suite of laboratory experiments that used a sand-filled column with an open head space. The CMPI fiber was packaged and embedded along the axis of the column to measure the strain at multiple locations while air pressure transducers were installed through the wall of the column. Small periodic fluctuations in air pressure, similar to barometric pressure fluctuations, were created in the head space of the column using an audio driven speaker driven at 4 Hz using a sinusoidal signal created by a function generator. Then, the fluctuations propagated along the column where they were measured by the transducers and recorded as functions of time. Initial tests were conducted using dry sand, but then additional tests were conducted after injecting water into the column, which changed the hydrologic and mechanical properties. Another experiment was conducted after creating a thin barrier to air flow, which was designed to simulate a thin layer of saturated ground during rainfall. A final experiment was conducted by changing the grain size of the material to create a heterogeneity in the upper half of the column. The suite of six experiments was conducted to highlight effects of variations in water content and heterogeneities on air pressure and vertical strain. Numerical simulations were also created to evaluate the laboratory data and to provide a baseline analysis for the results. The numerical simulations used the governing equations to linear poroelasticity and two-phase flow with boundary conditions representing the experiments. The conceptual model for strain caused by barometric pressure recognizes that a fluctuating barometric pressure causes fluctuations in the air pore pressure that decrease in amplitude and lag in time with increase depth. The pressure distribution results in two different loads that cause strain: 1.) a mechanical load as the barometric pressure acts on the ground surface; and 2.) pressure loading in the pore space. The results show that the total vertical strain is a contribution of both of these loads, and this is the strain that was observed in the laboratory. The lab experiments show that both air pressure and strain vary as sinusoids that propagate with depth. The amplitude of the air pressure and strain decrease as a function of depth in all the conditions that were evaluate. For example, in the dry sand, the amplitude of the air pressure decreases from 25 Pa at the head space to 5 Pa at a depth of 70 cm, whereas the amplitude of the strain decreases from 0.15 to 0.06 µε over the same depth interval. In many cases the amplitudes decrease is approximately negative exponential functions of depth. When water was injected into the sand and the saturation increased, the amplitude of the air pressure increased in the partially saturated sand but decreased sharply to zero where the soil was saturated. The strain decreased with depth, but the transition from partially to fully saturated conditions had little effect on the strain profile, even though it had a major effect on the air pressure. This apparently is because strain is caused by variations in both water and air pressure. The fluctuating air pressure caused the water pressure to fluctuate, which caused strain throughout the column. Phase delay of the air pressure and the strain both increase as linear to bi-linear functions of depth. The phase delays indicate that pressure propagates at a velocity of 7 to 8 m/s in dry or partially saturated sand, but it drops by more than an order of magnitude in the vicinity of the capillary fringe. The phase delays indicate the strain propagates faster than the pressure. The data indicate that the strain propagates from 1.2 to more than 4x faster than the pressure. Switching from sand to silt in the column caused the velocity of the pressure to drop by roughly half for both pressures, but curiously, it had little effect on the velocity of the strain.
54 ENVIRONMENTAL SCIENCES↗
Diffusion quantum Monte Carlo calculations of SrFeO 3 and LaFeO 3
The equations of state, formation energy, and migration energy barrier of the oxygen vacancy in SrFeO 3 and LaFeO 3 were calculated in this paper with the diffusion quantum Monte Carlo (DMC) method. Calculations were also performed with various Density Functional Theory (DFT) approximations for comparison. DMC reproduces the measured cohesive energies of these materials with errors below 0.23(5) eV and the structural properties within 1% of the experimental values. The DMC formation energies of the oxygen vacancy in SrFeO 3 and LaFeO 3 under oxygen-rich conditions are 1.3(1) and 6.24(7) eV, respectively. Similar calculations with semi-local DFT approximations for LaFeO 3 yielded vacancy formation energies 1.5 eV lower. Comparison of charge density evaluated with DMC and DFT approximations shows that DFT tends to overdelocalize the electrons in defected SrFeO 3 and LaFeO 3 . Finally, calculations with DMC and local density approximation yield similar vacancy migration energy barriers, indicating that steric/electrostatic effects mainly determine migration barriers in these materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The incomplete plasma dispersion function: Properties and application to waves in bounded plasmas
The incomplete plasma dispersion function is a generalization of the plasma dispersion function in which the defining integral spans a semi-infinite, rather than infinite, domain. It is useful for describing the linear dielectric response and wave dispersion in non-Maxwellian plasmas when the distribution functions can be approximated as Maxwellian over finite, or semi-infinite, intervals in velocity phase-space. A ubiquitous example is the depleted Maxwellian electron distribution found near boundary sheaths or double layers, where the passing interval can be modeled as Maxwellian with a lower temperature than the trapped interval. The depleted Maxwellian is used as an example to demonstrate the utility of using the incomplete plasma dispersion function for calculating modifications to wave dispersion relations.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Quasi-Stochastic Approximation and Off-Policy Reinforcement Learning: Preprint
The Robbins-Monro stochastic approximation algorithm is a foundation of many algorithmic frameworks for reinforcement learning and often an efficient approach to solving (or approximating the solution to) complex optimal control problems. In many cases, however, practitioners are unable to apply these techniques because of an inherent high variance. This paper aims to provide a general foundation for 'quasi-stochastic approximation,' in which all of the processes under consideration are deterministic, much like quasi-Monte Carlo for variance reduction in simulation. The variance reduction can be substantial, subject to tuning of pertinent parameters in the algorithm. This paper introduces a new coupling argument to establish the optimal rate of convergence provided the gain is sufficiently large. These results are established for linear models and tested also in nonideal settings. A major application of these general results is a new class of reinforcement learning algorithms for deterministic state space models. In this setting, the main contribution is a class of algorithms for approximating the value function for a given policy, using a different policy designed to introduce exploration.
24 POWER TRANSMISSION AND DISTRIBUTION↗