arXiv subjects

Sandra Luber

Publications and source records attributed to Sandra Luber.

5 recordsLinked to original sources

arXiv2026

Development of ab initio Hubbard parameter calculation schemes in the k-point sampling real-time TDDFT program in CP2K

We implemented ab initio Hubbard parameter calculation schemes in the k-point sampling real-time TDDFT (RT-TDDFT) program in CP2K. We propose a new linear-response-based calculation scheme for energy-dependent Hubbard parameters. Our scheme extends the minimum-tracking linear-response method proposed in [Moynihan et al., arXiv preprint arXiv:1704.08076(2017); E. B. Linscott et al., Phys. Rev. B 98, 235157 (2018)] to realize the calculation of energy-dependent Hubbard parameters that reflect the exchange-correlation (xc) effects included in the xc-functional. We discuss the properties of the minimum-tracking linear-response method in comparison to another promising scheme, ACBN0 [Agapito et al., Phys. Rev. X, 5, 011006 (2015)]. We show that, while neither clearly outperforms the other in the accuracy of static property calculations, each has a distinct dynamical application depending on its theoretical formulation.

cond-mat.str-el↗

arXiv2026

Stable, Fast, and Accurate Kohn-Sham Inversion in Gaussian Basis for Open Shell Molecular and Condensed Phase Systems via Density Matrix Penalization

Here we present a density matrix based KS inversion method formulated entirely within a Gaussian basis representation to optimize a KS potential matrix that reproduces a target electron density. Inverse Kohn-Sham (KS) density functional theory (DFT) aims to determine the effective local KS potential that reproduces a target electron density, and is important both for electronic structure analysis and for the development of orbital based correction methods. In finite Gaussian basis implementations, however, conventional inverse KS-DFT approaches such as the Zhao-Morrison-Parr (ZMP) method often become poorly constrained and inefficient, because the real space penalty potential is projected onto a limited number of Gaussian basis matrix elements, which can strongly coarse-grain its spatial variation. In the present method, the density matrix mismatch is defined in a Lowdin orthogonalized basis, which yields a penalty energy invariant under unitary rotations in that basis. The corresponding penalty potential contribution to the KS Hamiltonian is derived analytically in the original nonorthogonal Gaussian basis. Across a wide range of penalty strengths, the self consistent field (SCF) optimization remains robust and efficient for various open shell systems, while progressively tightening the penalty drives the electron density into accurate agreement with the target. Benchmarks on molecules and condensed phase systems show that the method achieves substantially smaller attainable density deviations than the conventional ZMP method. The method provides a fast and accurate route to KS inversion in finite Gaussian basis sets and may also be useful for future orbital based correction schemes.

physics.chem-ph↗

arXiv2025

The Anisotropic Interface Continuum Solvation Model and the Finite-Element Anisotropic Poisson Solver

We propose an anisotropic interfacial continuum solvation (AICS) model to simulate the distinct in-plane and out-of-plane dielectric constants of liquids near solid-liquid interfaces and their spatial variations along the surface normal direction. In low-electron-density regions, each dielectric function in the diagonal components of a dielectric tensor varies monotonically with distance from the solid surface along the surface normal; in high-electron-density regions near the surface, each dielectric function adopts the electron-density-based formulation proposed by Andreussi et al. (J. Chem. Phys. 136, 064102 (2012)) The resulting dielectric tensor is continuously differentiable with respect to both electron density and spatial coordinates. We derived analytical expressions for electrostatic contributions to the KS potential and forces, and implemented AICS, including these analytical derivatives, into CP2K. To solve the anisotropic Poisson equations, we developed a parallel finite-element anisotropic Poisson solver (FEAPS) based on the FEniCSx platform and its interface with CP2K. Analytical forces were validated against finite-difference calculations, while electrostatic potentials computed under vacuum and isotropic solvent conditions using AICS and FEAPS were benchmarked against standard vacuum DFT and SCCS results, respectively. In the anisotropic solvent environment characterized by the enhanced in-plane and reduced out-of-plane dielectric functions near the Ag(111) surface, we calculated the resulting work functions and electrostatic potentials, and optimized the adsorption geometry for OH. Compared to the isotropic case, we observed more pronounced work function shifts and spatially modulated electrostatic profiles across different charge states. Our results also showed that OH tilted more towards the plane parallel to the surface under the anisotropic dielectric conditions.

physics.chem-ph↗

arXiv2024

Functional Analytic Derivation and CP2K Implementation of the SCCS Model Based on the Solvent-Aware Interface

In the self-consistent continuum solvation (SCCS) approach ($\textit{J. Chem. Phys.}$ 136, 064102 (2012)), the analytical expressions of the local solute-solvent interface functions determine the interface function and dielectric function values at a given real space position based solely on the electron density at that position, completely disregarding the surrounding electron density distribution. Therefore, the low electron density areas inside the solute will be identified by the algorithm as regions where implicit solvent exists, resulting in the emergence of non-physical implicit solvent regions within the solute and even potentially leading to the divergence catastrophe of Kohn-Sham SCF calculations. We present a new and efficient SCCS implementation based on the solvent-aware interface ($\textit{J. Chem. Theory Comput.}$ 15, 3, 1996-2009 (2019)) which addresses this issue by utilizing a solute-solvent interface function based on convolution of electron density in the CP2K software package, which is based on the mixed Gaussian and plane waves (GPW) approach. Starting with the foundational formulas of SCCS, we have rigorously and meticulously derived the contributions of the newly defined electrostatic energy to the Kohn-Sham potential and the analytical forces. This comprehensive derivation utilizes the updated versions of the solute-solvent interface function and the dielectric function, tailored to align with the specifics of the GPW implementation. Our implementation has been tested to successfully eliminate non-physical implicit solvent regions within the solute and achieve good SCF convergence, as demonstrated by test results for both bulk and surface models, namely liquid $H_2O$, titanium dioxide, and platinum.

physics.chem-ph↗

arXiv2024

Predicting electronic screening for fast Koopmans spectral functional calculations

Koopmans spectral functionals are a powerful extension of Kohn-Sham density-functional theory (DFT) that enable the prediction of spectral properties with state-of-the-art accuracy. The success of these functionals relies on capturing the effects of electronic screening through scalar, orbital-dependent parameters. These parameters have to be computed for every calculation, making Koopmans spectral functionals more expensive than their DFT counterparts. In this work, we present a machine-learning model that -- with minimal training -- can predict these screening parameters directly from orbital densities calculated at the DFT level. We show on two prototypical use cases that using the screening parameters predicted by this model, instead of those calculated from linear response, leads to orbital energies that differ by less than 20 meV on average. Since this approach dramatically reduces run-times with minimal loss of accuracy, it will enable the application of Koopmans spectral functionals to classes of problems that previously would have been prohibitively expensive, such as the prediction of temperature-dependent spectral properties. More broadly, this work demonstrates that measuring violations of piecewise linearity (i.e. curvature in total energies with respect to occupancies) can be done efficiently by combining frozen-orbital approximations and machine learning.

cond-mat.mtrl-sci↗