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Hong Jiang

Publications and source records attributed to Hong Jiang.

At least 55 records · Page 3Linked to original sources

Non-collinear density functional theory

An approach to generalize any kind of collinear functionals in density functional theory to non-collinear functionals is proposed. This approach, for the very first time, satisfies the correct collinear limit for any kind of functionals, guaranteeing that the exact collinear functional after generalized is still exact for collinear spins. Besides, it has well-defined and numerically stable functional derivatives, a desired feature for non-collinear and spin-flip time-dependent density functional theory. Furthermore, it provides local torque, hinting at its applications in spin dynamics.

quant-ph↗

DFT+$U$ within the framework of linear combination of numerical atomic orbitals

We present a formulation and implementation of the DFT+\textit{U} method within the framework of linear combination of numerical atomic orbitals (NAO). Our implementation not only enables single-point total energy and electronic-structure calculations but also provides access to atomic forces and stresses, hence allowing for full structure relaxations of periodic systems. Furthermore, our implementation allows one to deal with non-collinear spin texture, with the spin-orbit coupling (SOC) effect treated self-consistently. The key aspect behind our implementation is a suitable definition of the correlated subspace when multiple atomic orbitals with the same angular momentum are used, and this is addressed via the "Mulliken charge projector" constructed in terms of the first (most localized) atomic orbital within the $d/f$ angular momentum channel. The important Hubbard $U$ and Hund $J$ parameters can be estimated from a screened Coulomb potential of the Yukawa type, with the screening parameter either chosen semi-empirically or determined from the Thomas-Fermi screening model. Benchmark calculations are performed for four late transition metal monoxide bulk systems, i.e., MnO, FeO, CoO, and NiO, and for the 5$d$-electron compounds IrO$_2$. For the former type of systems, we check the performance of our DFT+$U$ implementation for calculating band gaps, magnetic moments, electronic band structures, as well as forces and stresses; for the latter, the efficacy of our DFT+$U$+SOC implementation is assessed. Systematic comparisons with available experimental results, and especially with the results from other implementation schemes are carried out, which demonstrate the validity of our NAO-based DFT+$U$ formalism and implementation.

cond-mat.mtrl-sci↗

Phase transition and enhanced hardness of LaB4 under pressure

The crystalline structures of lanthanum tetraboride, LaB4, under pressure are investigated using a genetic algorithm method coupled with first-principles calculations. We find two low-enthalpy phases for LaB4 as the thermodynamic ground state up to 200 GPa: a phase previously observed in experiments (P4/mbm) and a novel orthorhombic phase (Pnma-I). The P4/mbm phase transforms to the Pnma-I phase at around 106 GPa, accompanied by breakage of the B-octahedron. The P4/mbm phase of LaB4 exhibits a high hardness (30.5 GPa) at ambient conditions, which is comparable to that of the hard material B4C. The hardness of the two low-enthalpy phases increases with pressure. The electronic band structures shows that all of the competitive phases (two stable and two metastable phases) are metallic. Phonon calculations shows the P4/mbm and Pnma-I phases are thermodynamically stable in their respective pressure ranges. This elucidation of the phase transition behavior and hardness of LaB4 provides new knowledge on the interesting high-pressure behaviors of the rare-earth metal borides.

cond-mat.mtrl-sci↗

Model-free approach to the interpretation of restricted and anisotropic self-diffusion in magnetic resonance of biological tissues

Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time/frequency-dependent ("restricted") and anisotropic self-diffusion of water. Traditional MRI relies on pulsed magnetic field gradients to encode the signal with information about translational motion in the direction of the gradient, which convolves fundamentally different aspects-such as bulk diffusivity, restriction, anisotropy, and flow-into a single effective observable lacking specificity to distinguish between biologically plausible microstructural scenarios. To overcome this limitation, we introduce a formal analogy between measuring rotational correlation functions and interaction tensor anisotropies in nuclear magnetic resonance (NMR) spectroscopy and investigating translational motion in MRI, which we utilize to convert data acquisition and analysis strategies from NMR of rotational dynamics in macromolecules to MRI of diffusion in biological tissues, yielding model-independent quantitative metrics reporting on relevant microstructural properties with unprecedented specificity. Our model-free approach advances the state-of-the-art in microstructural MRI, thereby enabling new applications to complex multi-component tissues prevalent in both tumors and healthy brain.

cond-mat.soft↗

C-for-Metal: High Performance SIMD Programming on Intel GPUs

The SIMT execution model is commonly used for general GPU development. CUDA and OpenCL developers write scalar code that is implicitly parallelized by compiler and hardware. On Intel GPUs, however, this abstraction has profound performance implications as the underlying ISA is SIMD and important hardware capabilities cannot be fully utilized. To close this performance gap we introduce C-For-Metal (CM), an explicit SIMD programming framework designed to deliver close-to-the-metal performance on Intel GPUs. The CM programming language and its vector/matrix types provide an intuitive interface to exploit the underlying hardware features, allowing fine-grained register management, SIMD size control and cross-lane data sharing. Experimental results show that CM applications from different domains outperform the best-known SIMT-based OpenCL implementations, achieving up to 2.7x speedup on the latest Intel GPU.

cs.DC↗

All-electron periodic $G_0W_0$ implementation with numerical atomic orbital basis functions: algorithm and benchmarks

We present an all-electron, periodic {\GnWn} implementation within the numerical atomic orbital (NAO) basis framework. A localized variant of the resolution-of-the-identity (RI) approximation is employed to significantly reduce the computational cost of evaluating and storing the two-electron Coulomb repulsion integrals. We demonstrate that the error arising from localized RI approximation can be reduced to an insignificant level by enhancing the set of auxiliary basis functions, used to expand the products of two single-particle NAOs. An efficient algorithm is introduced to deal with the Coulomb singularity in the Brillouin zone sampling that is suitable for the NAO framework. We perform systematic convergence tests and identify a set of computational parameters, which can serve as the default choice for most practical purposes. Benchmark calculations are carried out for a set of prototypical semiconductors and insulators, and compared to independent reference values obtained from an independent $G_0W_0$ implementation based on linearized augmented plane waves (LAPW) plus high-energy localized orbitals (HLOs) basis set, as well as experimental results. With a moderate (FHI-aims \textit{tier} 2) NAO basis set, our $G_0W_0$ calculations produce band gaps that typically lie in between the standard LAPW and the LAPW+HLO results. Complementing \textit{tier} 2 with highly localized Slater-type orbitals (STOs), we find that the obtained band gaps show an overall convergence towards the LAPW+HLO results. The algorithms and techniques developed in this work pave the way for efficient implementations of correlated methods within the NAO framework.

cond-mat.mtrl-sci↗

The influence of high-energy local orbitals and electron-phonon interactions on the band gaps and optical spectra of hexagonal boron nitride

We report $ab$ $initio$ band diagram and optical absorption spectra of hexagonal boron nitride ($h$-BN), focusing on unravelling how the completeness of basis set for $GW$ calculations and how electron-phonon interactions (EPIs) impact on them. The completeness of basis set, an issue which was seldom discussed in previous optical spectra calculations of $h$-BN, is found crucial in providing converged quasiparticle band gaps. In the comparison among three different codes, we demonstrate that by including high-energy local orbitals in the all-electron linearized augmented plane waves based $GW$ calculations, the quasiparticle direct and fundamental indirect band gaps are widened by $\sim$0.2 eV, giving values of 6.81 eV and 6.25 eV respectively at the $GW_0$ level. EPIs, on the other hand, reduce them to 6.62 eV and 6.03 eV respectively at 0 K, and 6.60 eV and 5.98 eV respectively at 300 K. With clamped crystal structure, the first peak of the absorption spectrum is at 6.07 eV, originating from the direct exciton contributed by electron transitions around $K$ in the Brillouin zone. After including the EPIs-renormalized quasiparticles in the Bethe-Salpeter equation, the exciton-phonon coupling shifts the first peak to 5.83 eV at 300 K, lower than the experimental value of $\sim$6.00 eV. This accuracy is acceptable to an $ab$ $initio$ description of excited states with no fitting parameter.

cond-mat.mtrl-sci↗

Lipschitz Learning for Signal Recovery

We consider the recovery of signals from their observations, which are samples of a transform of the signals rather than the signals themselves, by using machine learning (ML). We will develop a theoretical framework to characterize the signals that can be robustly recovered from their observations by an ML algorithm, and establish a Lipschitz condition on signals and observations that is both necessary and sufficient for the existence of a robust recovery. We will compare the Lipschitz condition with the well-known restricted isometry property of the sparse recovery of compressive sensing, and show the former is more general and less restrictive. For linear observations, our work also suggests an ML method in which the output space is reduced to the lowest possible dimension.

cs.LG↗

Electronic Band Structure of Cuprous and Silver Halides: a Numerically Accurate All-Electron $GW$ Study

Group IB metal halides (CuX and AgX, X=Cl, Br and I) are widely used in optoelectronic devices and photochemical catalysis due to their appropriate optical and electronic properties. First-principles calculations have confronted difficulties in accurately predicting their electronic band structures. Here we study CuX and AgX with many-body perturbation theory in the $GW$ approximation, implemented in the full-potential linearized augmented plane waves (FP-LAPW) framework. Comparing the quasi-particle band structures calculated with the default LAPW basis and the one extended by high-energy local orbitals (HLOs), denoted as LAPW+HLOs, we find that it is crucial to include HLOs to achieve sufficient numerical accuracy in $GW$ calculations of these materials. Using LAPW+HLOs in semi-local density functional approximation based $GW_0$ calculations leads to good agreement between theory and experiment for both band gaps and the splitting between metal (Cu or Ag) $d$ and X-$p$ states. It is indicated that quasi-particle band structures of CuX and AgX are crucially influenced by the numerical accuracy of $GW$ implementations, similar to what was found in ZnO [Jiang, H.; Blaha, P. Phys. Rev. B 2016, 93, 115203]. This work emphasizes the importance of numerical accuracy in the description of unoccupied states for quasi-particle band structure of materials with the $d^{10}$ electronic configuration.

cond-mat.mtrl-sci↗

Novel approaches to spectral properties of correlated electron materials: From generalized Kohn-Sham theory to screened exchange dynamical mean field theory

The most intriguing properties of emergent materials are typically consequences of highly correlated quantum states of their electronic degrees of freedom. Describing those materials from first principles remains a challenge for modern condensed matter theory. Here, we review, apply and discuss novel approaches to spectral properties of correlated electron materials, assessing current day predictive capabilities of electronic structure calculations. In particular, we focus on the recent Screened Exchange Dynamical Mean-Field Theory scheme and its relation to generalized Kohn-Sham theory. These concepts are illustrated on the transition metal pnictide BaCo$_2$As$_2$ and elemental zinc and cadmium.

cond-mat.str-el↗

Block-wise Lensless Compressive Camera

The existing lensless compressive camera ($\text{L}^2\text{C}^2$)~\cite{Huang13ICIP} suffers from low capture rates, resulting in low resolution images when acquired over a short time. In this work, we propose a new regime to mitigate these drawbacks. We replace the global-based compressive sensing used in the existing $\text{L}^2\text{C}^2$ by the local block (patch) based compressive sensing. We use a single sensor for each block, rather than for the entire image, thus forming a multiple but spatially parallel sensor $\text{L}^2\text{C}^2$. This new camera retains the advantages of existing $\text{L}^2\text{C}^2$ while leading to the following additional benefits: 1) Since each block can be very small, {\em e.g.}$~8\times 8$ pixels, we only need to capture $\sim 10$ measurements to achieve reasonable reconstruction. Therefore the capture time can be reduced significantly. 2) The coding patterns used in each block can be the same, therefore the sensing matrix is only of the block size compared to the entire image size in existing $\text{L}^2\text{C}^2$. This saves the memory requirement of the sensing matrix as well as speeds up the reconstruction. 3) Patch based image reconstruction is fast and since real time stitching algorithms exist, we can perform real time reconstruction. 4) These small blocks can be integrated to any desirable number, leading to ultra high resolution images while retaining fast capture rate and fast reconstruction. We develop multiple geometries of this block-wise $\text{L}^2\text{C}^2$ in this paper. We have built prototypes of the proposed block-wise $\text{L}^2\text{C}^2$ and demonstrated excellent results of real data.

cs.CV↗

Electronic origin of spin-phonon coupling effect in transition-metal perovskites

By applying Wannier-based extended Kugel-Khomskii model, we carry out first-principles calculations and electronic structure analysis to understand the spin-phonon coupling effect in transition-metal perovskites. We demonstrate the successful application of our approach to SrMnO$_3$ and BiFeO$_3$. We show that both the electron orbitals under crystal field splitting and the electronic configuration should be taken into account in order to understand the large variances of spin-phonon coupling effects among various phonon modes as well as in different materials.

cond-mat.mtrl-sci↗

Hubbard interactions in iron-based pnictides and chalcogenides: Slater parametrization, screening channels and frequency dependence

We calculate the strength of the frequency-dependent on-site electronic interactions in the iron pnictides LaFeAsO, BaFe2As2, BaRu2As2, and LiFeAs and the chalcogenide FeSe from first principles within the constrained random phase approximation. We discuss the accuracy of an atomic-like parametrization of the two-index density-density interaction matrices based on the calculation of an optimal set of three independent Slater integrals, assuming that the angular part of the Fe-d localized orbitals can be described within spherical harmonics as for isolated Fe atoms. We show that its quality depends on the ligand-metal bonding character rather than on the dimensionality of the lattice: it is excellent for ionic-like Fe-Se (FeSe) chalcogenides and a more severe approximation for more covalent Fe-As (LaFeAsO, BaFe2As2) pnictides. We furthermore analyze the relative importance of different screening channels, with similar conclusions for the different pnictides but a somewhat different picture for the benchmark oxide SrVO3: the ligand channel does not appear to be dominant in the pnictides, while oxygen screening is the most important process in the oxide. Finally, we analyze the frequency dependence of the interaction. In contrast to simple oxides, in iron pnictides its functional form cannot be simply modeled by a single plasmon, and the actual density of modes enters the construction of an effective Hamiltonian determining the low-energy properties.

cond-mat.str-el↗

Multi-resolution Compressive Sensing Reconstruction

We consider the problem of reconstructing an image from compressive measurements using a multi-resolution grid. In this context, the reconstructed image is divided into multiple regions, each one with a different resolution. This problem arises in situations where the image to reconstruct contains a certain region of interest (RoI) that is more important than the rest. Through a theoretical analysis and simulation experiments we show that the multi-resolution reconstruction provides a higher quality of the RoI compared to the traditional single-resolution approach.

cs.CV↗

Convergence of the Generalized Alternating Projection Algorithm for Compressive Sensing

The convergence of the generalized alternating projection (GAP) algorithm is studied in this paper to solve the compressive sensing problem $\yv = \Amat \xv + \epsilonv$. By assuming that $\Amat\Amat\ts$ is invertible, we prove that GAP converges linearly within a certain range of step-size when the sensing matrix $\Amat$ satisfies restricted isometry property (RIP) condition of $δ_{2K}$, where $K$ is the sparsity of $\xv$. The theoretical analysis is extended to the adaptively iterative thresholding (AIT) algorithms, for which the convergence rate is also derived based on $δ_{2K}$ of the sensing matrix. We further prove that, under the same conditions, the convergence rate of GAP is faster than that of AIT. Extensive simulation results confirm the theoretical assertions.

cs.IT↗

Constrained and Preconditioned Stochastic Gradient Method

We consider stochastic approximations which arise from such applications as data communications and image processing. We demonstrate why constraints are needed in a stochastic approximation and how a constrained approximation can be incorporated into a preconditioning technique to derive the pre-conditioned stochastic gradient method (PSGM). We perform convergence analysis to show that the PSGM converges to the theoretical best approximation under some simple assumptions on the preconditioner and on the independence of samples drawn from a stochastic process. Simulation results are presented to demonstrate the effectiveness of the constrained and precondi-tioned stochastic gradient method.

math.NA↗

Compressive Sensing via Low-Rank Gaussian Mixture Models

We develop a new compressive sensing (CS) inversion algorithm by utilizing the Gaussian mixture model (GMM). While the compressive sensing is performed globally on the entire image as implemented in our lensless camera, a low-rank GMM is imposed on the local image patches. This low-rank GMM is derived via eigenvalue thresholding of the GMM trained on the projection of the measurement data, thus learned {\em in situ}. The GMM and the projection of the measurement data are updated iteratively during the reconstruction. Our GMM algorithm degrades to the piecewise linear estimator (PLE) if each patch is represented by a single Gaussian model. Inspired by this, a low-rank PLE algorithm is also developed for CS inversion, constituting an additional contribution of this paper. Extensive results on both simulation data and real data captured by the lensless camera demonstrate the efficacy of the proposed algorithm. Furthermore, we compare the CS reconstruction results using our algorithm with the JPEG compression. Simulation results demonstrate that when limited bandwidth is available (a small number of measurements), our algorithm can achieve comparable results as JPEG.

stat.ML↗

Lensless Compressive Imaging

We develop a lensless compressive imaging architecture, which consists of an aperture assembly and a single sensor, without using any lens. An anytime algorithm is proposed to reconstruct images from the compressive measurements; the algorithm produces a sequence of solutions that monotonically converge to the true signal (thus, anytime). The algorithm is developed based on the sparsity of local overlapping patches (in the transformation domain) and state-of-the-art results have been obtained. Experiments on real data demonstrate that encouraging results are obtained by measuring about 10% (of the image pixels) compressive measurements. The reconstruction results of the proposed algorithm are compared with the JPEG compression (based on file sizes) and the reconstructed image quality is close to the JPEG compression, in particular at a high compression rate.

cs.CV↗