This part of the documentation is currently being rewritten
Welcome to the TRIQS project!
This guide aims at presenting you the main classes of TRIQS and its applications through ready-to-use examples. These small demo codes should help you understand the logic behind the general design and organization of the library.
We strongly recommend first-time users to go through the extensive set of Jupyter Notebook tutorials provided on GitHub. You can run the notebooks either in an interactive Binder Session on the web or run them locally after setting up TRIQS on your computer.
This pages does not aim to replace the full reference of the code available here.
Why use TRIQS?
TRIQS is a powerful library that allows you to easily write code to study strongly correlated problems. It is designed as a toolkit containing all the essential ingredients to tackle condensed matter physics. Before presenting you the tools available both in C++ and Python, we want you to have a look at a small script where a full Dynamical Mean-Field Theory calculation using the Continuous-Time Hybridization Expansion (CT-HYB) solver is realized in… one page!
A quick tour in Python
We here provide a little tour of some aspects of TRIQS and its applications, at the Python level.
If you want to learn more about Python, iPython and the notebook, you can check our external resources: