Matrix Product Operators for Sequence to Sequence Learning

Understand

The method of choice to study one-dimensional strongly interacting many body quantum systems is based on matrix product states and operators.

• Such method allows to explore the most relevant, and numerically manageable, portion of an exponentially large space.
• It also allows to describe accurately correlations between distant parts of a system, an important ingredient to account for the context in machine learning tasks.
• Here we introduce a machine learning model in which matrix product operators are trained to implement sequence to sequence prediction, i.e.