Gregory Crosswhite, University of Washington

Photo of Gregory Crosswhite

Large systems governed by the laws of quantum mechanics are very difficult beasts to simulate with numerical methods; this is because the precise description of such systems requires a tensor with rank equal to the number of particles in the system, and so the amount of space needed to store the state of the system grows exponentially with its size. Happily, it turns out that these beasts are susceptible to attack by a class of techniques based on tensor networks. The idea is that one can hope that the large rank (scary) tensor describing the system can be well approximated by a network of (more benign) tensors with small rank. In my poster I will present an overview of these techniques, how I am applying them to simulate particular quantum systems of interest, and results I have obtained.

Abstract Author(s): Gregory M. Crosswhite