5 papers
Qubit-efficient quantum combinatorial optimization solver
Bhuvanesh Sundar, Maxime Dupont
Quantum optimization solvers typically rely on one-variable-to-one-qubit mapping. However, the low qubit count on current quantum computers is a major obstacle in competing against…
Self-consistent mean-field quantum approximate optimization
Maxime Dupont, Bhuvanesh Sundar, Meenambika Gowrishankar
We introduce a self-consistent mean-field quantum optimization algorithm that approximates the ground state of classical Ising Hamiltonians. The algorithm decomposes the problem in…
Optimization via Quantum Preconditioning
Maxime Dupont, Tina Oberoi, Bhuvanesh Sundar
State-of-the-art classical optimization solvers set a high bar for quantum computers to deliver utility in this domain. Here, we introduce a quantum preconditioning approach based…
Benchmarking Quantum Optimization for the Maximum-Cut Problem on a Superconducting Quantum Computer
Maxime Dupont, Bhuvanesh Sundar, Bram Evert +4
Achieving high-quality solutions faster than classical solvers on computationally hard problems is a challenge for quantum optimization to deliver utility. Using a superconducting…
A Multilevel Approach For Solving Large-Scale QUBO Problems With Noisy Hybrid Quantum Approximate Optimization
Filip B. Maciejewski, Bao Gia Bach, Maxime Dupont +5
Quantum approximate optimization is one of the promising candidates for useful quantum computation, particularly in the context of finding approximate solutions to Quadratic Uncons…