Cassella Team Builds 10,000-Variable Analog Floquet Solver, Cutting Energy Use by 9 Orders
Updated
Updated · Northeastern University · Jul 17
Cassella Team Builds 10,000-Variable Analog Floquet Solver, Cutting Energy Use by 9 Orders
1 articles · Updated · Northeastern University · Jul 17
Summary
Cristian Cassella’s team said its Analog Floquet Solver found accurate solutions for optimization equations with up to 10,000 variables, tackling cases the researchers said had not been solved before.
The method targets QUBO problems by overcoming a key weakness of Ising machines, which often get trapped in local minima instead of reaching the global minimum—the best overall answer.
Floquet theory adds periodic energy to the system, effectively helping it jump out of shallow solution valleys and continue toward a lower-energy optimum.
Cassella said the approach delivered record speed and a nine-orders-of-magnitude improvement in energy consumption, potentially widening use in logistics, drug discovery, protein folding, finance and wireless communications.