Simulating the t-J Model on a Quantum Computer

Quantum computers are expected to give an exponential speed-up over classical computers for the simulation of strongly correlated quantum systems. Efficient implementation of these simulations is of great interest for many fields in the physical sciences. We consider algorithms for simulating the t-J model, a prominent model for high temperature superconductivity, on a quantum computer. Our approach focuses the computation on the low-energy projected phase space instead of taking the large interaction limit of the Hubbard model. We investigate trade-offs in noise, complexity, time and gate count in extracting the system's Green's function and self-energy, from which a wide variety of interesting physical quantities can be computed.