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.GRANAD是一款基于紧束缚近似（tight-binding approximation）的程序，用于模拟石墨烯纳米片（graphene nanoflakes）与Su–Schrieffer–Heeger（SSH）链在电磁辐照下带有吸附原子缺陷时的光电子学性质。其核心特性为针对自旋追踪的单粒子约化密度矩阵（spin-traced one-particle reduced density matrix）求解时域主方程（time-domain master equation）的数值解。该程序可呈现电荷分布的时间分辨演化过程，支持感应场动力学分析，并可实现等离激元响应（plasmonic response）的表征。其他可计算的物理量包括能量分布曲线、实空间电子分布以及吸收光谱（absorption spectra）。GRANAD采用Python语言编写，依托JAX库实现高性能数组计算、即时（just-in-time, JIT）编译与可微分性。该工具旨在轻量化、可移植且易于配置部署，提供了一种透明高效的途径，用以研究从纳米尺度至介观尺度的低维碳结构的相关性质。GRANAD为开源项目，完整代码与包含使用示例的详尽文档可通过https://github.com/GRANADlauncher/granad.git获取。