Minisymposium Presentation

Tensor Networks are in the center of every disproval of quantum advantage claims in these recent years. Achieving quantum advantage, the predicted theoretical moment when quantum computers will beat classical computers on some problems, is key for the general adoption of quantum computers. But proving it theoretically has proven to be a task of great difficulty. Due to that, researchers have tried to attack the problem from an empirical point of view, by finding a problem which is solvable in a quantum computer, but intratable in a supercomputer. Tensor Networks are a mathematical framework for multilinear operators which originated in the Condensed Matter community but have also proven to be very powerful in Quantum Information/Computation and Machine Learning tasks. In this talk, I will speak about our efforts on developing a modular Tensor Network and Quantum Simulation framework for high-performant and large-scale simulations in some of the top supercomputers in the world.