HamLib is an extensive dataset of qubit Hamiltonians spanning a large range of problem sizes and instances that is designed for testing quantum algorithms, software and hardware.
In this paper, we introduce a novel measurement-driven approach that finds eigenenergies by collecting real-time measurements and post-processing them using the machinery of dynamic mode decomposition (DMD).
We extend our circuit compression algorithms to free fermionic systems on arbitrary lattices, incorporate particle creation operations, and allow for controlled evolution.
We report a series benchmarks conducted in NERSC's Perlmutter system using a GPU adaptation of QCLAB++, a light-weight, fully-templated C++ package for quantum circuit simulations.
We introduce a uniform framework for quantum pixel representations that encompasses many of the popular image representations proposed in the literature. We propose a novel circuit implementation with an efficient compression algorithm.
By analyzing the Hamiltonian algebra, we show that Trotter circuits for simulation of free fermions are efficiently compressible. Our method is applied to an adiabatic state preparation experiment.