US 12,186,585 B2
Quantum computation for intensity-modulated radiation therapy
Cecil Lynch, Granite Bay, CA (US); Kung-Chuan Hsu, Cerritos, CA (US); Shreyas Ramesh, Mountainside, NJ (US); Carl Matthew Dukatz, Troy, MI (US); Felix Dominik Schiessl, Hattersheim (DE); Tim Leonhardt, Munich (DE); and Max Howard, San Francisco, CA (US)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Mar. 25, 2021, as Appl. No. 17/212,815.
Claims priority of provisional application 63/007,666, filed on Apr. 9, 2020.
Prior Publication US 2021/0316157 A1, Oct. 14, 2021
Int. Cl. A61N 5/10 (2006.01); G05B 19/4155 (2006.01); G06F 16/242 (2019.01); G06F 17/11 (2006.01); G06N 5/01 (2023.01); G06N 10/00 (2022.01); G06N 10/60 (2022.01); G16H 20/40 (2018.01); G16H 40/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01)
CPC A61N 5/1031 (2013.01) [G05B 19/4155 (2013.01); G06F 16/2425 (2019.01); G06F 17/11 (2013.01); G06N 10/00 (2019.01); G06N 10/60 (2022.01); G16H 20/40 (2018.01); G16H 40/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01); A61N 5/1045 (2013.01); G05B 2219/45117 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving data relating to an optimization problem, wherein the optimization problem comprises an objective function to be optimized over multiple problem parameters;
iteratively processing, until termination criteria are met, the received data relating to the optimization problem to obtain data representing a solution to the optimization problem, comprising, for each iteration:
performing a classical search algorithm on an input for the iteration to determine a first solution to the optimization problem;
providing data relating to the first solution to the optimization problem to a quantum computing resource, wherein the data relating to the first solution to the optimization problem comprises a quadratic unconstrained binary optimization (QUBO) formulation of the optimization problem in a local region around the first solution to the optimization problem;
generating the quadratic unconstrained binary optimization (QUBO) formulation of the optimization problem in the local region around the first solution to the optimization problem, comprising:
selecting a discretization for the optimization problem;
applying the discretization to the optimization problem to obtain discretized values of the multiple problem parameters, wherein each discretized value comprises a respective binary sequence; and
determining a binary sequence corresponding to a discretization of the first solution to the optimization task;
obtaining data relating to a second solution to the optimization problem from the quantum computing resource; and
providing the data relating to the second solution to the optimization problem as input to a subsequent iteration;
receiving solution data from the processing; and
initiating an action based on the solution data.