rhodent: A python package for analyzing real-time TDDFT response

Artikel i vetenskaplig tidskrift, 2026

Real-time time-dependent density functional theory (rt-TDDFT) is a well-established method for studying the dynamic response of matter in the femtosecond or optical range. In this method, the Kohn-Sham wave functions are propagated forward in time, and in principle, one can extract any observable at any given time. Alternatively, by taking a Fourier transform, spectroscopic quantities can be extracted. There are many publicly available codes implementing rt-TDDFT, which differ in their numeric solution of the KS equations, their available Exchange-correlation functionals, and in their analysis capabilities. For users of rt-TDDFT, this is an inconvenient situation because they may need to use a numerical method that is available in one code, but an analysis method available in another. Here, we introduce RHODENT, a modular Python package for processing the output of rt-TDDFT calculations. Our package can be used to calculate hot-carrier distributions, energies, induced densities, and dipole moments, and various decompositions thereof. In its current version, RHODENT handles calculation results from the GPAW code, but can readily be extended to support other rt-TDDFT codes. Additionally, under the assumption of linear response, RHODENT can be used to calculate the response to a narrow-band laser, from the response to a broad-band perturbation, greatly speeding up the analysis of frequency-dependent excitations. We demonstrate the capabilities of RHODENT via a set of examples, for systems consisting of Al and Ag clusters and organic molecules. Program summary Program Title: rhodent CPC Library link to program files: https://doi.org/10.17632/ksp3gdsgw6.1 Developer's repository link: https://gitlab.com/materials-modeling/rhodent Licensing provisions: MPL-2.0 Programming language: Python Nature of problem:rt-TDDFT is a powerful method for probing the response of electronic systems. This method is implemented in several codes, with differing implementation details and possibilities for computing observables. However, if the full evolution of the density is recorded by the rt-TDDFT software, then it is possible to extract observables as a post-processing step. A modular implementation of the post-processing routines allows the same analysis to be applied to calculations performed using different rt-TDDFT programs. Furthermore, relatively weak perturbations are often of interest, so that the system response is in the linear regime. Then one single rt-TDDFT calculation with a broad-spectrum perturbation (e.g., a delta-kick) is enough to reconstruct the response for other perturbations (e.g., Gaussian laser pulses) in post-processing. Carrying out these post-processing steps is orders of magnitude faster than the rt-TDDFT calculation, and allows for computationally efficient analysis of the system at hand. Solution method:We construct the Kohn-Sham density matrix using matrix operations, transform between the time and frequency domains by means of the discrete Fourier transform, and compute relevant observables by weighted summations. These operations are parallelized using the MPI library, allowing efficient execution on consumer-grade CPUs as well as on high-performance computer clusters.