Rapid quantum approaches for combinatorial optimisation inspired by optimal state-transfer
arXiv:2301.06846 · doi:10.22331/q-2024-02-13-1253
Abstract
We propose a new design heuristic to tackle combinatorial optimisation problems, inspired by Hamiltonians for optimal state-transfer. The result is a rapid approximate optimisation algorithm. We provide numerical evidence of the success of this new design heuristic. We find this approach results in a better approximation ratio than the Quantum Approximate Optimisation Algorithm at lowest depth for the majority of problem instances considered, while utilising comparable resources. This opens the door to investigating new approaches for tackling combinatorial optimisation problems, distinct from adiabatic-influenced approaches.
37 pages, 25 figures, 2 tables
References in corpus (14)
- QuTiP 2: A Python framework for the dynamics of open quantum systems
- Quantum Computation as Geometry
- Demonstration of multi-qubit entanglement and algorithms on a programmable neutral atom quantum computer
- Singular extremals for the time-optimal control of dissipative spin 1/2 particles
- Quantum Adiabatic Brachistochrone
- Quantum brachistochrone curves as geodesics: obtaining accurate control protocols for time-optimal quantum gates
- Solution to the quantum Zermelo navigation problem
- Time-optimal navigation through quantum wind
- Zermelo Navigation in the Quantum Brachistochrone
- Optimal Control for Closed and Open System Quantum Optimization
- Greedy parameter optimization for diabatic quantum annealing
- Binary Control Pulse Optimization for Quantum Systems
- How to Compute Using Quantum Walks
- Locally Suppressed Transverse-Field Protocol for Diabatic Quantum Annealing