Tensor Networks
Tensor networks are an elegant approach for compactly representing very high dimensional wavefunctions and other objects encountered when modeling quantum many-body systems.
The success of a tensor network description arises from the locality of interactions between quantum particles, and provides an interesting connection between many-body quantum entanglement and computational efficiency
Tensor networks are not only a powerful numerical tool, but also provide an interesting way to understand and even classify quantum many-body systems. The development of tensor network algorithms is a dynamic area of research, and CCQ researchers are both discovering more efficient algorithms and applying them to solve more complex and realistic models of quantum systems. Current areas of activity include tensor networks for higher-dimensional systems, tensor network impurity solvers for embedding methods, and methods for continuum functions including solving differential equations. CCQ is home to the ITensor library for the rapid development of tensor network algorithms.
Project Leader: Miles Stoudenmire
Project Scientists: Matt Fishman, Joseph Tindall, Olivier Parcollet, Lukas Devos, Sophia Wolczko, Jack Dunham, Marc Ritter