Research
arXiv
26.11.24
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems
In this work we develop theoretical techniques for analysing the performance of the quantum approximate optimization algorithm (QAOA) when applied to random boolean constraint sati...
arXiv
20.11.24
Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver
We numerically benchmark 30 optimisers on 372 instances of the variational quantum eigensolver for solving the Fermi-Hubbard system with the Hamiltonian variational ansatz. We rank...
arXiv
07.11.24
Quantum speedups in solving near-symmetric optimization problems by low-depth QAOA
We present new advances in achieving exponential quantum speedups for solving optimization problems by low-depth quantum algorithms. Specifically, we focus on families of combinato...
