Eugene DePrince

We present sum-of-squares spectral amplification (SOSSA), a framework for improving quantum simulation relevant to low-energy problems. We show how SOSSA can be applied to problems like energy and phase estimation and provide fast quantum algorithms for these problems that significantly improve over prior art. We analyze the performance of SOSSA on the Sachdev-Ye-Kitaev model, a representative strongly correlated system, and demonstrate asymptotic speedups over generic simulation methods by a factor of the square root of the system size. We then apply SOSSA to electronic structure problems in quantum chemistry, yielding a factor of 4 to 195 speedup over the state of the art in ground-state energy estimation for models of Iron-Sulfur complexes and a CO2-fixation catalyst.

First-quantized plane-wave representations provide a very promising approach for quantum algorithms for solid state materials. Pseudopotentials provide a method of further reducing the complexity by avoiding the need to simulate highly localized core orbitals. The complicated functional form of pseudopotentials constitutes a major challenge for the design of quantum algorithms. In this work we provide new techniques to efficiently implement pseudopotentials in quantum algorithms, with orders of magnitude improvement in complexity. Our methods include a high-accuracy QROM interpolation of the exponential function, combined with QROM for the pseudopotential parameters and coherent arithmetic. Moreover, we generalize prior methods to enable the simulation of materials defined by non-cubic unit cells. Finally, we combine these techniques to estimate the resources for block encoding required for simulating commercially relevant instances of heterogeneous catalysis.