Fenna–Matthews–Olson (FMO) datasets

The dynamics of the Fenna–Matthews–Olson (FMO) complex. FMO-Ia and FMO-Ib data sets: 7-site FMO model Hamiltonian parametrized by Adolphs and Renger solved with local thermalizing Lindblad master equation approach. FMO-II data set: 7-site FMO model Hamiltonian parametrized by Cho et al. solved with local thermalizing Lindblad master equation approach. FMO-III data set: 8-site FMO model Hamiltonian parametrized by Jia et al. solved with local thermalizing Lindblad master equation approach. FMO-IV data set: 8-site FMO model Hamiltonian parametrized by Olbrich et al. and Busch et al. solved with local thermalizing Lindblad master equation approach. FMO-V data set: FMO trimer based on 8-site model Hamiltonian parametrized by Olbrich et al. and Busch et al. solved with local thermalizing Lindblad master equation approach. FMO-VI data set: 8-site FMO model Hamiltonian parametrized by by Olbrich et al. and Busch et al. solved solved with hierarchical equations of motion approach. Each data set contains reduced density matrix of the electronic 7- or 8-site system. See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6389553 Collection description: Simulations of the dynamics of dissipative quantum systems utilize many methods such as physics-based quantum, semiclassical, and quantum-classical as well as machine learning-based approximations, development and testing of which requires diverse data sets. Here we present a new database QD3SET-1 containing eight data sets of quantum dynamical data for two systems of broad interest, spin-boson (SB) model and the Fenna–Matthews–Olson (FMO) complex, generated with two different methods solving the dynamics, approximate local thermalizing Lindblad master equation (LTLME) and highly accurate hierarchy equations of motion (HEOM). One data set was generated with the SB model which is a two-level quantum system coupled to a harmonic environment using HEOM for 1,000 model parameters. Seven data sets were collected for the FMO complex of different sizes (7- and 8-site monomer and 24-site trimer with LTLME and 8-site monomer with HEOM) for 500–879 model parameters. Our QD3SET-1 database contains both population and coherence dynamics data and part of it has been already used for machine learning-based quantum dynamics studies.芬纳-马修斯-奥尔森（Fenna–Matthews–Olson, FMO）复合物动力学数据集详情如下： FMO-Ia与FMO-Ib数据集：采用Adolphs与Renger参数化的7位点FMO模型哈密顿量，通过局域热化林德布拉德主方程（local thermalizing Lindblad master equation）方法求解。 FMO-II数据集：采用Cho等人参数化的7位点FMO模型哈密顿量，通过局域热化林德布拉德主方程方法求解。 FMO-III数据集：采用Jia等人参数化的8位点FMO模型哈密顿量，通过局域热化林德布拉德主方程方法求解。 FMO-IV数据集：采用Olbrich与Busch等人参数化的8位点FMO模型哈密顿量，通过局域热化林德布拉德主方程方法求解。 FMO-V数据集：基于Olbrich与Busch等人参数化的8位点模型哈密顿量构建的FMO三聚体，通过局域热化林德布拉德主方程方法求解。 FMO-VI数据集：采用Olbrich与Busch等人参数化的8位点FMO模型哈密顿量，通过层级运动方程（hierarchical equations of motion）方法求解。 所有数据集均包含电子7位或8位点系统的约化密度矩阵。相关研究素材可于以下馆藏获取：https://doi.org/10.25452/figshare.plus.c.6389553 馆藏说明：耗散量子系统的动力学模拟可依托多种方法实现，涵盖基于物理的量子方法、半经典方法、量子-经典混合方法，以及基于机器学习的近似方法。此类方法的开发与验证亟需多样化的数据集作为支撑。本研究推出新型数据库QD3SET-1，包含两类广受关注的系统的8组量子动力学数据集：自旋玻色（spin-boson, SB）模型与芬纳-马修斯-奥尔森（FMO）复合物。数据集通过两种不同的动力学求解方案生成：近似局域热化林德布拉德主方程（approximate local thermalizing Lindblad master equation, LTLME）与高精度层级运动方程（hierarchical equations of motion, HEOM）。其中一组数据集基于自旋玻色模型生成，该模型为耦合至谐波环境的二能级量子系统，研究通过HEOM方法对1000组模型参数完成动力学模拟。针对FMO复合物，本数据库共收集7组不同尺寸体系的模拟数据：7位点、8位点单体，以及采用LTLME方法的24位点三聚体，和采用HEOM方法的8位点单体，涵盖500至879组模型参数。本QD3SET-1数据库同时包含布居数与相干动力学数据，其中部分数据集已被应用于基于机器学习的量子动力学研究。