arXiv subjects

Weiqing Zhou

Publications and source records attributed to Weiqing Zhou.

13 recordsLinked to original sources

arXiv2026

A stochastic propagation method for large-scale phonon calculations

Large-scale phonon calculations for structurally complex materials are limited by the cubic cost of full diagonalization. We extend the stochastic propagation method (sPM) from electronic systems to lattice dynamics for estimating phonon frequencies, constructing vibrational densities of states, and reconstructing selected phonon polarization vectors by propagating random initial vectors under the dynamical matrix. For finite-range interactions, the leading propagation cost scales linearly with atom number at fixed sampling and propagation parameters. Our error analysis shows that, for nondegenerate modes that are spectrally resolved and have nonzero frequency in the small-error regime, extending propagation yields faster asymptotic reduction of frequency-estimation errors than increasing the number of random initial states alone. Comparisons with direct diagonalization validate the spectral estimates and a selected polarization vector. Convergence tests support the predicted scaling of frequency errors for selected resolved modes.

cond-mat.mtrl-sci↗

arXiv2026

From local learning to global electronic properties in large-scale systems

Machine learning from local atomic environments offers an efficient route to electronic structure, but evaluating global electronic properties in large systems remains computationally demanding. Here we combine real space charge density learning with stochastic propagation using Kohn-Sham Hamiltonians constructed from the predicted densities. The framework avoids target system self-consistent iterations and explicit diagonalization, while hierarchical blocking enables dense grid inference within limited GPU memory. We demonstrate density of states calculations for one million Si atoms and optical and transport calculations for over one hundred thousand atoms, without training separate models for each property. This framework extends the practical scale of electronic structure calculations within Kohn-Sham DFT, opening opportunities to investigate how atomic structure governs electronic, optical and transport properties at length scales relevant to real materials and devices.

cond-mat.mtrl-sci↗

arXiv2026

Hierarchical Fourier Phase Projection for Local Electronic Observables

In this letter, we develop hierarchical Fourier phase projection (HPP) for the calculation of local electronic observables. The method couples the spatial decay of the density matrix with a hierarchy of Fourier probes, improving accuracy through refinement, and making use of all previously evaluated responses. The variation in the calculated observables during the refinement process carries information on the residual error. We use a locality-based model to estimate the error from these changes with no extra probing calculations. In particular, we demonstrate the method for electron densities and nonlocal pseudopotential forces for fixed Kohn-Sham Hamiltonians of semiconductors, metals and thermally perturbed silica. The convergence is significantly accelerated by the spatial decay of the density matrix, especially if the density matrix is short-ranged. The number of probes necessary to achieve a specific local accuracy is only weakly dependent on the system size within the range of consideration. HPP provides a route toward linear-scaling electronic-structure calculations in which the computational effort for local observables can be matched to the required accuracy, offering an error-aware strategy for large-scale first-principles simulations.

cond-mat.mtrl-sci↗

arXiv2025

Integrating Deep-Learning-Based Magnetic Model and Non-Collinear Spin-Constrained Method: Methodology, Implementation and Application

We propose a non-collinear spin-constrained method that generates training data for deep-learning-based magnetic model, which provides a powerful tool for studying complex magnetic phenomena that requires large-scale simulations at the atomic level. First, we propose a basis-independent projection method for calculating atomic magnetic moments by applying a radial truncation to numerical atomic orbitals. A double-loop Lagrange multiplier method is utilized to ensure the satisfaction of constraint conditions while achieving accurate magnetic torque. The method is implemented in ABACUS with both plane wave basis and numerical atomic orbital basis. We benchmark the iron (Fe) systems and analyze differences from calculations with the plane wave basis and numerical atomic orbitals basis in describing magnetic energy barriers. Based on an automated workflow composed of first-principles calculations, magnetic model, active learning, and dynamics simulation, more than 30,000 first-principles data with the information of magnetic torque are generated to train a deep-learning-based magnetic model DeePSPIN for the Fe system. By utilizing the model in large-scale molecular dynamics simulations, we successfully predict Curie temperatures of alpha-Fe close to experimental values.

cond-mat.mtrl-sci↗

arXiv2025

ABACUS: An Electronic Structure Analysis Package for the AI Era

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and molecular dynamics functions and is compatible with both plane-wave basis sets and numerical atomic orbital basis sets. ABACUS serves as a platform that facilitates the integration of various electronic structure methods, such as Kohn-Sham DFT, stochastic DFT, orbital-free DFT, and real-time time-dependent DFT, etc. In addition, with the aid of high-performance computing, ABACUS is designed to perform efficiently and provide massive amounts of first-principles data for generating general-purpose machine learning potentials, such as DPA models. Furthermore, ABACUS serves as an electronic structure platform that interfaces with several AI-assisted algorithms and packages, such as DeePKS-kit, DeePMD, DP-GEN, DeepH, DeePTB, HamGNN, etc.

cond-mat.mtrl-sci↗

arXiv2025

Large-scale stochastic propagation method beyond the sequential approach

The $O(N)$ stochastic propagation method, which relies on the numerical solution of the time-dependent Schrödinger equation using random initial states, is widely used in large-scale first-principles calculations. In this work, we eliminate the conventional sequential computation of intermediate states by introducing a concurrent strategy that minimizes information redundancy. The new method, in its state-, moment-, and energy-based implementations, not only surpasses the time step constraint of sequential propagation but also maintains precision within the framework of the Nyquist-Shannon sampling theorem. Systematic benchmarking on one billion atoms within the tight-binding model demonstrates that our new concurrent method achieves up to an order-of-magnitude speedup, enabling the rapid computation of a wide range of electronic, optical, and transport properties. This performance breakthrough offers valuable insights for enhancing other time-propagation algorithms, including those employed in large-scale stochastic density functional theory.

physics.comp-ph↗

arXiv2024

Electronic states and quantum transport in bilayer graphene Sierpinski-carpet fractals

We construct Sierpinski-carpet (SC) based on AA or AB bilayer graphene by atom vacancies, namely, SC-AA and SC-AB, to investigate the effects of interlayer coupling on the electronic properties of fractals. Compared with monolayer graphene SC, their density of states have similar features, such as Van-Hove singularities and edge states corresponding to the central peaks near zero energy, but remarkable energy broadening of edge states emerges in SC-AA(AB). Calculated conductance spectrum shows that the conductance fluctuations still hold the Hausdorff fractal dimension behavior even with the interlayer coupling. Thus, the high correlation between quantum conductance and fractal geometry dimension is not affected by the interlayer coupling in bilayer graphene SC. We further reveal the quasi-eigenstates in fractal-like pressure-modulated bilayer graphene, namely, SC-pAA and SC-pAB. Numerical results show that the density of states of SC-pAA(pAB) show an asymptotic behavior to those of SC-AA(AB) especially for high energy quasi-eigenstates. Within a certain energy range, stronger pressure can lead to stronger localization, forming an efficient fractal space.

cond-mat.mes-hall↗

arXiv2023

Enhanced hydrogen-gas permeation through rippled graphene

The penetration of atomic hydrogen through defect-free graphene was generally predicted to have a barrier of at least several eV, which is much higher than the 1 eV barrier measured for hydrogen-gas permeation through pristine graphene membranes. Herein, our density functional theory calculations show that ripples, which are ubiquitous in atomically thin crystals and mostly overlooked in the previous simulations, can significantly reduce the barriers for all steps constituting the mechanism of hydrogen-gas permeation through graphene membranes, including dissociation of hydrogen molecules, reconstruction of the dissociated hydrogen atoms and their flipping across graphene. Especially, the flipping barrier of hydrogen atoms from a cluster configuration is found to decrease rapidly down to <1 eV with increasing ripples' curvature. The estimated hydrogen permeation rates by fully considering the distribution of ripples with all realistic curvatures and the major reaction steps that occurred on them are quite close to the experimental measurements. Our work provides insights into the fundamental understanding of hydrogen-gas permeation through graphene membranes and emphasizes the importance of nanoscale non-flatness (ripples) in explaining many surface and transport phenomena (for example, functionalization, corrosion and separation) in graphene and other two-dimensional materials.

cond-mat.mtrl-sci↗

arXiv2023

A Time-Dependent Random State Approach for Large-scale Density Functional Calculations

We develop a self-consistent first-principle method based on the density functional theory. Physical quantities, such as the density of states, Fermi energy and electron density are obtained using a time-dependent random state method without diagonalization. The numerical error for calculating either global or local variables always scales as $1/\sqrt{SN_{e}}$, where $N_{e}$ is the number of electrons and $S$ is the number of random states, leading to a sublinear computational cost with the system size. In the limit of large systems, one random state could be enough to achieve reasonable accuracy. The method's accuracy and scaling properties are derived analytically and verified numerically in different condensed matter systems. Our time-dependent random state approach provides a powerful strategy for large-scale density functional calculations.

cond-mat.mes-hall↗

arXiv2022

Electronic properties and quantum transports in functionalized graphene Sierpinski carpet fractals

Recent progress in controllable functionalization of graphene surfaces enables the experimental realization of complex functionalized graphene nanostructures, such as Sierpinski carpet (SC) fractals. Herein, we model the SC fractals formed by hydrogen and fluorine functionalized patterns on graphene surfaces, namely, H-SC and F-SC, respectively. We then reveal their electronic properties and quantum transport features. From calculated results of the total and local density of state, we find that states in H-SC and F-SC have two characteristics: (i) low-energy states inside about |E/t|<1 (with t as the near-neighbor hopping) are localized inside free graphene regions due to the insulating properties of functionalized graphene regions, and (ii) high-energy states in F-SC have two special energy ranges including -2.3<E/t<-1.9 with localized holes only inside free graphene areas and 3<E/t<3.7 with localized electrons only inside fluorinated graphene areas. The two characteristics are further verified by the real-space distributions of normalized probability density. We analyze the fractal dimension of their quantum conductance spectra and find that conductance fluctuations in these structures follow the Hausdorff dimension. We calculate their optical conductivity and find that several additional conductivity peaks appear in high energy ranges due to the adsorbed H or F atoms.

cond-mat.mes-hall↗

arXiv2021

Confined Electrons in Effective Plane Fractals

As an emerging complex two-dimensional structure, plane fractal has attracted much attention due to its novel dimension-related physical properties. In this paper, we check the feasibility to create an effective Sierpinski carpet (SC), a plane fractal with Hausdorff dimension intermediate between one and two, by applying an external electric field to a square or a honeycomb lattice. The electric field forms a fractal geometry but the atomic structure of the underlying lattice remains the same. By calculating and comparing various electronic properties, we find parts of the electrons can be confined effectively in a fractional dimension with a relatively small field, and representing properties very close to these in a real fractal. In particular, compared to the square lattice, the external field required to effectively confine the electron is smaller in the hexagonal lattice, suggesting that a graphene-like system will be an ideal platform to construct an effective SC experimentally. Our work paves a new way to build fractals from a top-down perspective, and can motivate more studies of fractional dimensions in real systems.

cond-mat.mes-hall↗

arXiv2019

Effect of mechanical strain on the optical properties of nodal-line semimetal ZrSiS

Optical properties of nodal-line semimetal ZrSiS are studied using first-principles calculations. Frequency-independent optical conductivity is a fingerprint of the infrared optical response in ZrSiS. We find that this characteristic feature is robust with respect to uniaxial compressive strain of up to 10 GPa, yet with the flat region being narrowed with increasing strain. Upon uniaxial tensile stress of 2 GPa, the Fermi surface undergoes a Lifshitz transition accompanied by a weakening of the interband screening, which reduces the spectral weight of infrared excitations. We also show that the high-energy region is characterized by low-loss plasma excitations at $\sim$20 eV with essentially anisotropic dispersion. Strongly anisotropic dielectric properties suggest the existence of a hyperbolic regime for plasmons in the deep ultraviolet range. Although the frequencies of high-energy plasmons are virtually unaffected by external uniaxial deformation, their dispersion can be effectively tuned by strain.

physics.comp-ph↗

arXiv2018

Tunable Half-Metallicity and Edge Magnetism of H-saturated InSe Nanoribbons

We report on a theoretical study of electronic and magnetic properties of hydrogen-saturated InSe nanoribbons (H-ZISNs). Based on hybrid-functional first-principles calculations, we find that H-ZISNs exhibit tunable half-metallicity and short-range ferromagnetic order. We first show that p-type doping turns narrow H-ZISNs from semimetal to half-metal with spin-polarization along In-terminated edge. This behavior is further analyzed in terms of a two-band tight-binding model, which provides a tractable description of the H-ZISN electronic structure, and serves as a starting point for the determination of magnetic interactions. The dominant exchange interaction determined within the Heisenberg model is found to be ferromagnetic independently of the ribbon width and charge doping. Short-range stability of magnetic order is assessed in terms of the zero-field spin correlation length, which is found to be about 1 nm at liquid nitrogen temperatures. Finally, by calculating spin-dependent transport properties, we find a doping regime in which strongly spin-selective electrical conductivities can be observed. Our findings suggest that H-ZISNs are appealing candidates for the realization of spintronic effects at the nanoscale.

physics.comp-ph↗