mirror of
https://github.com/triqs/dft_tools
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60 lines
2.3 KiB
ReStructuredText
60 lines
2.3 KiB
ReStructuredText
.. meta::
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:description: TRIQS: a Toolbox for Research on Interacting Quantum Systems
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:keywords: triqs quantum interacting systems toolbox research
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.. _welcome:
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Welcome
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=======
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.. sidebar:: TRIQS 1.0
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This is the homepage of the new TRIQS 1.0. Many things
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have changed and been improved since the versions 0.x.
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The format of the archives and names of some python classes
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have changed too. So go look at our :ref:`changelog page <changelog>`
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to find out how to upgrade to 1.0.
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TRIQS (**T**\oolbox for **R**\esearch on **I**\nteracting **Q**\uantum **S**\ystems)
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is a scientific project providing a set of C++ and Python libraries to develop new tools
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for the study of interacting quantum systems.
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The goal of this toolkit is to provide condensed matter physicists with
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some high level, efficient and simple to use libraries in C++ and Python,
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and to promote the use of modern programming techniques in our field.
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TRIQS is free software (GPL).
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TRIQS applications
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-----------------------
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Based on the TRIQS toolkit, several :ref:`full-fledged applications <applications>`
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are also maintained by the TRIQS collaboration. They allow for example to
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solve a generic quantum impurity model or to run a complete LDA+DMFT
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calculation.
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Elaborated in a collaboration between IPhT Saclay and Ecole Polytechnique since 2005,
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the TRIQS library and applications have allowed to address questions as diverse as:
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* Momentum-selective aspects on cuprate superconductors (with various cluster DMFT)
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* Degree of correlation in iron-based superconductors (within an LDA+DMFT approach)
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* Fermionic Mott transition and exploration of Sarma phase in cold-atoms
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Python & C++
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-----------------------------
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The libraries exist at two
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complementary levels: on the one hand, C++ libraries allow to quickly develop
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performant low-level codes; on the other hand python libraries implement the
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most common many-body objects, like Green's functions, that can be manipulated
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easily in python scripts.
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This duality is a real advantage in the development of new many-body tools.
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Critical parts where performance is essential can be written in C++ (like a
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quantum impurity solver) while the manipulation of the results, preparation of
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the inputs or interface with other programs can be done at the very
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user-friendly python level.
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