arXiv subjects

Zhichang Fu

Publications and source records attributed to Zhichang Fu.

3 recordsLinked to original sources

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

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↗