Improving nonstoquastic quantum annealing with spin-reversal transformations

Abstract

Nonstoquastic Hamiltonians are hard to simulate due to the sign problem in quantum Monte Carlo simulation. It is however unclear whether nonstoquasticity can lead to advantage in quantum annealing. Here we show that YY-interaction between the qubits makes the adiabatic path during quantum annealing, and therefore the performance, dependent on spin-reversal transformations. With the right choice of spin-reversal transformation, a nonstoquastic Hamiltonian with YY-interaction can outperform stoquastic Hamiltonians with similar parameters. We introduce an optimization protocol to determine the optimal transformation and discuss the effect of suboptimality.

References in corpus (7)

• QuTiP 2: A Python framework for the dynamics of open quantum systems
• Computational complexity and fundamental limitations to fermionic quantum Monte Carlo simulations
• Realizable Hamiltonians for Universal Adiabatic Quantum Computers
• Adiabatic approximation with exponential accuracy for many-body systems and quantum computation
• Exponential Enhancement of the Efficiency of Quantum Annealing by Non-Stochastic Hamiltonians
• Adiabatic optimization versus diffusion Monte Carlo
• De-Signing Hamiltonians for Quantum Adiabatic Optimization

Cited by in corpus (3)

• Comparing Three Generations of D-Wave Quantum Annealers for Minor Embedded Combinatorial Optimization Problems
• Quantum Annealing with Trigger Hamiltonians: Application to 2-SAT and Nonstoquastic Problems
• Quantum annealing for hard 2-SAT problems : Distribution and scaling of minimum energy gap and success probability