6 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…
Simulating plasma wave propagation on a superconducting quantum chip
Bhuvanesh Sundar, Bram Evert, Vasily Geyko +3
Quantum computers may one day enable the efficient simulation of strongly coupled plasmas that lie beyond the reach of classical computation in regimes where quantum effects are im…
Many-Body Effects in Dark-State Laser Cooling
Muhammad Miskeen Khan, David Wellnitz, Bhuvanesh Sundar +5
We develop a unified many-body theory of two-photon dark-state laser cooling, the workhorse for preparing trapped ions close to their motional quantum ground state. For ions with a…
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…