# rhodent: A Python package for analyzing real-time TDDFT response

## TL;DR

rhodent is a Python package that simplifies the analysis of real-time TDDFT simulation outputs, enabling efficient computation of spectroscopic and dynamic properties across different codes.

## Contribution

It introduces a modular Python tool for analyzing rt-TDDFT results, compatible with multiple codes and capable of various spectral and dynamic analyses.

## Key findings

- Supports calculation of hot-carrier distributions and energies
- Handles analysis for Al, Ag clusters, and organic molecules
- Can compute responses to laser perturbations efficiently

## Abstract

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 (KS) 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.