Noise‐induced sampling of alternative Hamiltonian paths in quantum adiabatic search

We numerically simulate the effects of noise‐induced sampling of alternative Hamiltonian paths on the ability of quantum adiabatic search (QuAdS) to solve randomly generated instances of the NP‐complete problem N‐bit Exact Cover 3. The noise‐averaged median runtime is determined as the noise‐power and number of bits N are varied, and power‐law and exponential fits are made to the data. Noise is seen to slowdown QuAdS, though a downward shift in the scaling exponent is found for N > 12 over a range of noise‐power values. We discuss whether this shift might be connected to arguments in the literature that suggest that altering the Hamiltonian path might benefit QuAdS performance.