TD-SCHA is a theory to simulate quantum nuclear motion in materials with strong anharmonicity.
TD-SCHA stands for Time-Dependent Self-Consistent Harmonic Approximation, and it is the dynamical extension of the SCHA theory, that can describe equilibrium properties of materials accounting for both quantum and dynamical nuclear fluctuations.
The tdscha Python library allows performing dynamical linear response calculations on top of the equilibrium results (computed with the python-sscha package).
Enhanced Simulation Capabilities
TD-SCHA is an essential tool for researchers and professionals in material science, particularly for simulating transport or thermal properties of materials, phase diagrams, and phonon-related properties.
Integration with python-sscha
Seamless integration with python-sscha allows for the inclusion of both thermal and quantum phonon fluctuations in ab initio simulations.
Leveraging the SSCHA Method
Quantum and Thermal Fluctuations
The Stochastic Self-Consistent Harmonic Approximation (SSCHA) is a full-quantum method optimizing the nuclear wave-function or density matrix to minimize free energy, crucial for simulating highly anharmonic systems.
Efficiency and Cost-Effectiveness
Despite its full quantum and thermal nature, the computational cost is comparable to classical molecular dynamics, enhanced by the algorithm's ability to exploit crystal symmetries.
User-Friendly and Versatile
Python Library and Stand-alone Software
Available both as a Python library and stand-alone software, with input scripts sharing syntax with Quantum ESPRESSO.
Broad Compatibility
Can couple with any ab initio engine and interacts through the Atomic Simulation Environment (ASE) with an interface for automatic job submission on remote clusters.
Getting Started
Easy to Use
User-friendly with short, readable input files and comprehensive tutorials.
Download and Explore
Download and install python-sscha, and start exploring the tutorials to enhance your material simulation projects.
You need to have installed python-sscha and CellConstructor to work with tdscha.
Please read the installation guide for those packages before proceeding further.
You may find all instructions on the official website.
To install from PyPI, simply type:
pip install tdschaYou can alternatively clone the repository from GitHub and install the package with:
pip install .
Go to the tutorials