TBPLaS
TBPLaS (Tight-Binding Package for Large-scale Simulation) is an open-source package for building and solving tight-binding models, with emphasis on handling large systems. It implements the tight-binding propagation method (TBPM) and achieves linear scaling in CPU time and RAM costs with respect to the model size. The highly efficient C++ core, hybrid OpenMP+MPI parallelization and GPU acceleration makes solving extra-large models with billions of orbitals on computers with moderate hardware possible. The user API is designed following the object-oriented paradigm and provides both Python and C++ implementations, offering both user friendliness and efficiency.
TBPLaS是一个专注于构建和求解超大规模紧束缚模型的软件包。该软件实现了紧束缚时间演化方法,可以实现线性标度计算。核心部分采用C++编写,支持MPI+OpenMP混合并行和GPU加速,可以在中等硬件配置的计算机上模拟超过十亿轨道的紧束缚模型。用户接口采用Python语言编写,采用面向对象设计,并为追求高性能的用户提供了兼容的C++接口,充分保证了易用性和运行效率。
- Models with arbitrary dimension (1D-3D), shape and boundary conditions;
- Defects, impurities and disorders;
- External electric and magnetic fields;
- Hetero-structures, quasicrystals, fractals.
- Exact-diagonalization: Band structure, density of states (DOS), wave functions, Lindhard functions;
- Recursive Green’s function method: Local density of states (LDOS);
- Tight-binding propagation method (TBPM): DOS, LDOS and carrier density; Optical (AC) conductivity and absorption spectrum; Electrical (DC) conductivity and time-dependent diffusion coefficient, carrier velocity, mobility, elastic mean free path, Anderson localization length; Polarization function, response function, dielectric function, energy loss function, plasmon dispersion, plasmon lifetime and damping rate; Quasi-eigenstate and real-space charge density;
- Kernel polynomial method: Electrical (DC) and Hall Conductivity.
- 一维至三维任意维度、形状和边界条件的紧束缚模型;
- 缺陷、空位、掺杂;
- 外加电磁场;
- 异质结、准晶、分形。
- 精确对角化方法:能带、态密度、局域态密度、波函数、极化率、介电函数、吸收光谱、光电导;
- Haydock迭代法:局域态密度;
- TBPM:态密度、局域态密度、载流子浓度、(光)电导率、载流子速率、迁移率、平均自由程、极化函数、介电函数、电子能量损失谱、吸收光谱、等离激元色散关系、寿命、准本征态;
- 核多项式方法:直流电导率和霍尔电导率。
Research articles published utilizing TBPLaS can be found at https://www.tbplas.net/publication.html.
More information about TBPLaS is available at http://www.tbplas.net.
TBPLaS已经被用于40多项研究工作中,详情请见 https://www.tbplas.net/publication.html。
软件下载和使用请见项目主页 http://www.tbplas.net。

ABPLaS
ABPLaS (Ab initio Package for Large-scale Simulation) 是一款可用于进行百万原子量级密度泛函理论计算的大尺度第一性原理计算软件包。ABPLaS支持密度泛函传播法(DFPM)和对角化方法等多种求解算法;基于实空间网格;支持多种边界条件,可用于晶体、团簇、表面等多类体系的基态计算。计算的时间和内存消耗均随着体系线性增加;采用稀疏矩阵存储技术,支持OpenMP/MPI混合并行,可在普通集群算力下进行上百万原子的第一性原理计算。ABPLaS还提供一系列后处理功能模块,可用于模拟基态的电学、光学、输运、等离激元等性质;代码主体为C++,架构灵活,便于扩展。ABPLaS目前正在积极开发之中,预计将在近期发布首个正式版本。
ABPLaS (Ab initio Package for Large-scale Simulation) is a large-scale first-principles computational package designed for density functional theory (DFT) calculations at the million-atom scale. ABPLaS supports multiple solution algorithms such as the Density Functional Propagation Method (DFPM) and diagonalization methods; it is based on real-space grids; supports various boundary conditions, and can be applied to ground-state calculations of crystals, clusters, and surfaces. The computational cost in both time and memory scales linearly with system size. By employing sparse matrix storage techniques and hybrid OpenMP/MPI parallelization, ABPLaS enables million-atom first-principles simulations on standard computing clusters. It also provides a series of post-processing modules for simulating ground-state properties such as electronic, optical, transport, and plasmonic characteristics. The core code is written in C++, featuring a flexible architecture for easy extension. ABPLaS is currently under active development, with its first official release expected soon.
量子计算与量子模拟云平台
Quantum Computing and Quantum Simulation Cloud Platform
量子计算与量子模拟云平台是由武汉大学、武汉量子技术研究院以及中科酷原科技(武汉)有限公司联合开发的国内首个针对中性原子体系的综合性量子计算云平台。
该平台集量子计算、量子操控以及量子模拟于一体,旨在为用户提供高效、便捷、专业的量子计算与模拟服务。
The Quantum Computing and Quantum Simulation Cloud Platform is jointly developed by Wuhan University, Wuhan Institute of Quantum Technology, and Zhongke KuYuan Technology (Wuhan) Co., Ltd. It is the first comprehensive quantum computing cloud platform in China dedicated to neutral atom systems.
The platform integrates quantum computing, quantum control, and quantum simulation, aiming to provide users with efficient, convenient, and professional quantum computing and simulation services.
- 全振幅量子计算模拟器:最大支持提交28量子比特的计算任务。提供高精度全振幅模拟,适合研究小规模但高度纠缠的量子线路。
- 张量网络量子计算模拟器:最大支持提交50量子比特的计算任务。针对弱纠缠系统的高效模拟,适用于较大规模量子系统的研究。
- 中性原子量子计算真机操作接口:支持直接操作中性原子量子计算真机。包含两个功能接口:
- 全局模拟接口:提供对实验运行的理论模拟。
- 真机拉比震荡模拟接口:帮助用户分析和优化实验过程。
- 大规模量子系统模拟接口:支持模拟多种复杂体系,如莫尔转角晶格、分形系统、准晶系统。提供高效计算能力,助力大尺度量子系统的研究。
- 量子计算动力学模拟接口:目前支持对自旋系统的动力学模拟。后续将推出:
- 线路式动力学模拟程序
- 中性原子量子计算动力学模拟程序
- 含噪声版本动力学模拟
- Full-Amplitude Quantum Computing Simulator: Supports up to 28 qubits per submitted task. Provides high-precision full-amplitude simulation, suitable for studying small-scale but highly entangled quantum circuits.
- Tensor Network Quantum Computing Simulator: Supports up to 50 qubits per submitted task. Efficient simulation for weakly entangled systems, suitable for research on larger-scale quantum systems.
- Neutral Atom Quantum Computing Real-Machine Interface: Supports direct operation of neutral atom quantum computing hardware. Includes two interfaces:
- Global Simulation Interface: Provides theoretical simulation of experimental runs.
- Real-Machine Rabi Oscillation Simulation Interface: Helps users analyze and optimize experimental procedures.
- Large-Scale Quantum System Simulation Interface: Supports simulation of complex systems such as moiré twisted lattices, fractal systems, and quasicrystals. Provides efficient computing power for large-scale quantum system research.
- Quantum Computing Dynamics Simulation Interface: Currently supports dynamics simulation of spin systems. Upcoming features include:
- Circuit-based dynamics simulation program
- Neutral atom quantum computing dynamics simulation program
- Noisy version dynamics simulation
更多关于云平台的信息请访问 https://quantumclouds.cn/。
For more information about the cloud platform, please visit https://quantumclouds.cn/.

