In this work, we explore connections between various “analog” quantum optimization algorithms such as QAOA and annealing, and the limits in which they become approximations of the optimal control strategy.
Approximate optimization of the MaxCut problem with a local spin algorithm
We study the dynamics and practical performance of a quantum-inspired “local tensor” algorithm for approximate optimization of MaxCut problem instances.
Optimal protocols in quantum annealing and quantum approximate optimization algorithm problems
We carry out simulations of optimal control protocols for energy minimization on various transverse field Ising models, demonstrating that optimal protocols typically exhibit a bang-anneal-bang pattern.
Quantum approximate optimization of the long-range Ising model with a trapped-ion quantum simulator
We implement a variational quantum algorithm (QAOA) to approximate the ground-state energy of a long-range Ising model, both quantum and classical, and investigating the algorithm performance on a trapped-ion quantum simulator with up to 40 qubits.
Entanglement bounds on the performance of quantum computing architectures
In this paper, we show that a quantity known as the isoperimetric number establishes a lower bound on the time required to create highly entangled states.
Unitary entanglement construction in hierarchical networks
We present numerical and analytical results on the speed at which large entangled states can be created on nearest-neighbor grids and hierarchy graphs. We also present a scheme for performing circuit placement on hierarchical quantum architectures.
Bang-bang control as a design principle for classical and quantum optimization algorithms
We study the performance of several variational quantum optimization algorithms on two toy constraint satisfaction problem instances, and argue that the type of control strategy can be crucial to success.
Classical simulation of Yang-Baxter gates
We show how to classically simulate circuit representations of the Yang-Baxter equation when the generating gate belongs to certain families of solutions.