Flatiron Software
The ITensor library supports the productive development of robust and efficient software based on tensor networks. The innovative design of the ITensor library lets users focus on the connectivity of tensor networks instead of lower-level considerations, and is modeled on tensor diagram notation. ITensor has a multi-layered design including basic dense tensors; sparse tensor types; sophisticated handling of quantum number symmetries; and high-level algorithms for matrix product states.
In addition to providing ongoing support for ITensor and its users, there is a major effort at CCQ to continue expanding the scope of ITensor to make handling complex quantum models easier and to continue incorporating the latest algorithmic developments and tensor network formats.
NetKet is an open-source project delivering advanced methods for the study of many-body quantum systems with artificial neural networks and machine learning techniques. It is the first open-source platform supporting collaborative developments in the field and aims to be a robust yet highly responsive reference implementation for both consolidated and new, more experimental, techniques.
One of the main features of this software is the ability to find the ground state of interacting Hamiltonians using neural network–based ansatz states for the many-body wave function. Because of the modular infrastructure of the library, it is possible to highly customize most of its components. For example, changing Hamiltonians, observables and other problem-dependent quantities is meant to be easy and does not require an in-depth knowledge of programming languages.
To stimulate a large-scale conceptual and practical development of the software, NetKet has introduced a series of “Challenges” tasks, to be tackled by researchers worldwide.
The TRIQS (Toolbox for Research in Interacting Quantum Systems) project provides a Python/C++ library of basic components to implement the cutting-edge algorithms in the Quantum Many-Body problem, with a focus on Quantum Embedding and Quantum Monte Carlo methods. The project also includes a series of applications, e.g. state-of-the-art quantum impurity solvers, and an interface to electronic structure codes for DFT+DMFT computations.