GRANAD - Simulating GRAphene nanoflakes with ADatoms

GRANAD is a program based on the tight-binding approximation to simulate optoelectronic properties of graphene nanoflakes and Su–Schrieffer–Heeger (SSH) chains with possible adatom defects under electromagnetic illumination. Its core feature is the numerical solution of a time-domain master equation for the spin-traced one-particle reduced density matrix. It provides time-resolved evolution of charge distributions, access to induced-field dynamics, and characterization of the plasmonic response. Other computable quantities include energy profiles, electron distribution in real space, and absorption spectra. GRANAD is written in Python and relies on the JAX library for high-performance array computing, just-in-time (JIT) compilation, and differentiability. It is intended to be lightweight, portable, and easy to set up, offering a transparent and efficient way to access the properties of low-dimensional carbon structures from the nanoscale to the mesoscopic regime. GRANAD is open source, with the full code and extensive documentation with usage examples available at https://github.com/GRANADlauncher/granad.git.