Matthew Fishman of the Center for Computational Quantum Physics at The Flatiron Institute introduces us to ITensor.jl, a memory-independent interface for tensor manipulations in Julia.
Tensor network methods are an extremely useful class of simulation algorithms in physics. They work by constructing a graph of tensors and making local optimizations to capture the essential physics of a many-body system. ITensor (Intelligent Tensor) is a leading C++ package for work with tensor network methods.
In this talk, we present the initial version of ITensors.jl, a ground-up rewrite of ITensor in Julia. Using lessons from the ITensor C++ project, we offer much of the same powerful functionality in a more concise and elegant format, with the goal to substantially lower the "barrier to entry" for using tensor network techniques.
We will present some usage examples that are common in physics applications to exemplify the ITensors.jl user interface and design philosophy. Using Julia, we can create a tensor network package expressive enough to capture a variety of physics that's also more easily accessible to working physicists and computer scientists.