Search arXiv⌕ Search

arXiv · 2501.10907

Direct unconstrained optimization of excited states in density functional theory

Abstract

Orbital-optimized density functional theory (DFT) has emerged as an alternative to time-dependent (TD) DFT capable of describing difficult excited states with significant electron density redistribution, such as charge-transfer, Rydberg, and double-electron excitations. Here, a simple method is developed to solve the main problem of the excited-state optimization -- the variational collapse of the excited states onto the ground state. In this method, called variable-metric time-independent DFT (VM TIDFT), the electronic states are allowed to be nonorthogonal during the optimization but their orthogonality is gradually enforced with a continuous penalty function. With nonorthogonal electronic states, VM TIDFT can use molecular orbital coefficients as independent variables, which results in a closed-form analytical expression for the gradient and allows to employ any of the multiple unconstrained optimization algorithms that guarantees convergence of the excited-state optimization. Numerical tests on multiple molecular systems show that the variable-metric optimization of excited states performed with a preconditioned conjugate gradient algorithm is robust and produces accurate energies for well-behaved excitations and, unlike TDDFT, for more challenging charge-transfer and double-electron excitations.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hanh D. M. Pham, Rustam Z. Khaliullin. 2025-01-19. Direct unconstrained optimization of excited states in density functional theory. https://arxiv.org/abs/2501.10907

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Causality in Liquid Water as a Hallmark of Emergent Glassy Dynamics

In molecular liquids such as water, time-delayed influences between microscopic or mesoscopic variables are typically probed using time-correlation functions, which are symmetric under detailed balance and therefore blind to dynamical asymmetries. Here, we characterize water's dynamics using a causal inference metric that captures asymmetric couplings between collective variables. Analyzing equilibrium molecular dynamics simulations at ambient conditions and in the high-density liquid (HDL) regime of supercooled water, we uncover pronounced asymmetries in the couplings between orientational and translational degrees of freedom across multiple time and length scales. At room temperature, rotational modes exert a modest directional influence on translational dynamics. In contrast, in the supercooled HDL regime, translational motions emerge as the primary drivers of the dynamics, suggesting facilitation-like relaxation mechanisms characteristic of glassy systems. These results reveal a qualitative reorganization of dynamical couplings across thermodynamic conditions, implying that molecular liquids at thermal equilibrium can exhibit an emergent directionality in their fluctuation couplings. As a consequence, our analysis reveals that external perturbations acting on specific degrees of freedom can induce a stronger arrow of time in the causal relations between translational and orientational modes.

physics.chem-ph↗

pANO-F12: An atomic natural orbital-inspired route to more compact basis sets for F12 explicitly correlated methods

Explicitly correlated methods such as MP2-F12 and CCSD(F12*) exhibit much faster basis set convergence (asymptotically $\propto L^{-7}$, with L the highest angular momentum) than orbital-only approaches. Yet it has been pointed out that cc-pVnZ-F12 basis sets themselves are substantially larger than the corresponding cc-pVnZ, and specifically that cc-pVDZ-F12 is the size of cc-pVTZ. One way to generate compact basis sets in an orbital-only context are Atomic Natural Orbital (ANO) basis sets [J. Almlöf and P. R. Taylor, JCP 86, 4070 (1987)]. However, obtaining the required first-order reduced density matrix while properly accounting for the F12 geminal is problematic. In this work, we show that an energy minimization-based contraction process under linear independence constraints yields `pseudo-ANO' (pANO) basis sets that are functionally equivalent in quality. Subsequently, we apply this recipe to obtain pANO-F12 basis sets from the same elements, then validate them for several thermochemical benchmarks and for the hypersensitive out-of-plane vibrations of benzene. We show that, unlike cc-pVnZ-F12, pANO-F12 exhibits the familiar shell structure seen in cc-pVnZ and ANO basis sets, and that pANO-F12 offers a route to more compact F12 basis sets more amenable to medium-sized systems, especially in conjunction with localized pair natural orbital approaches. Overall, the pANO approach is most beneficial for the smaller double-and triple-zeta basis sets, offering either superior performance to cc-pVnZ-F12 at same cost, or similar performance at lower cost.

physics.chem-ph↗

A Task-Based Framework for Evaluating Raman Spectral Quality Measures

Raman spectral preprocessing and enhancement are often evaluated by comparing output spectra with a reference. Interpreting these comparisons requires evidence that spectral quality measures reflect downstream task performance. We present a controlled-perturbation framework for testing this relationship. Five perturbation types (baseline distortion, independent noise, correlated noise, a global wavenumber shift, and nonlinear axis warping) generate paired changes in a spectral measure (metric harm) and in downstream performance (task harm). An alignment gap (AG) quantifies how much the relationship between metric harm and task harm changes with perturbation type. Ordering concordance (OC) measures how often a metric correctly ranks two conditions by their task harm. The framework evaluates thirteen outputs (MSE, RMSE, MAE, NMSE, spectral angle, Pearson correlation, Wasserstein distance, a structure-to-noise ratio, peak precision, recall, F1, artifact ratio, and missing ratio). Three public datasets provide bacterial classification, sugar-mixture quantification, and mineral identification tasks. PCA with logistic regression, partial least squares regression, and cosine library matching supply the task outcomes. Classifiers and calibrations are fitted either to unperturbed training spectra or to each perturbed training condition, then evaluated on the same perturbed test spectra. Mineral queries are compared with an unchanged or correspondingly perturbed library. The resulting comparisons identify task-specific strengths and limitations, including cases where better ordering does not accompany a smaller AG. Removing axis perturbations and comparing spectra on a common physical grid test how these findings depend on the evaluation design. The framework provides a reproducible procedure for assessing existing measures and testing new candidates against downstream task performance.

physics.chem-ph↗