Iterative approaches to Quantum Simulation (QS) are restricted to simulation times less than the coherence time of the Quantum Computer (QC), which limits their utility in the near term.
Researchers at Los Alamos have developed is a hybrid combining aspects of classical and quantum computing. Although well-established theorems exclude the potential of general fast forwarding with absolute fidelity for arbitrary quantum simulations, the researchers get around the problem by tolerating small calculation errors for intermediate times in order to provide useful, if slightly imperfect, predictions.
The team has proposed a hybrid quantum-classical algorithm, called Variational Fast Forwarding (VFF), for decreasing the quantum circuit depth of QSs. VFF seeks an approximate diagonalization of a short-time simulation to enable longer-time simulations using a constant number of gates.
Their error analysis provided two results: (1) the simulation error of VFF scales at worst linearly in the fast-forwarded simulation time, and (2) their cost function’s operational meaning as an upper bound on average-case simulation error provides a natural termination condition for VFF.
The researchers implemented VFF for the Hubbard, Ising, and Heisenberg models on a simulator. In addition, they also implemented VFF on Rigetti’s Quantum Computers to demonstrate simulation beyond the coherence time.
Finally, they showed how to estimate energy eigenvalues using VFF.
The paper has been published in npj Quantum Information.
