The Short Path Algorithm Applied to a Toy Model

The Short Path Algorithm Applied to a Toy Model

Blog Article

We numerically investigate the performance of the short path optimization algorithm on a toy problem, with the potential chosen to depend only on the total Hamming weight to allow simulation of larger systems.We consider classes of potentials with multiple minima which cause the adiabatic algorithm to experience difficulties with small gaps.The numerical investigation allows us to consider a broader range teeter totter cabernet 2019 of parameters than was studied in previous duke waves and fades rigorous work on the short path algorithm, and to show that the algorithm can continue to lead to speedups for more general objective functions than those considered before.We find in many cases a polynomial speedup over Grover search.

We present a heuristic analytic treatment of choices of these parameters and of scaling of phase transitions in this model.