US 11,836,575 B2
Error corrected variational algorithms
Ryan Babbush, Venice, CA (US); and Austin Greig Fowler, Reseda, CA (US)
Assigned to Google LLC, Mountain View, CA (US)
Appl. No. 17/278,137
Filed by Google LLC, Mountain View, CA (US)
PCT Filed Sep. 25, 2018, PCT No. PCT/US2018/052662
§ 371(c)(1), (2) Date Mar. 19, 2021,
PCT Pub. No. WO2020/068052, PCT Pub. Date Apr. 2, 2020.
Prior Publication US 2021/0334691 A1, Oct. 28, 2021
Int. Cl. G06F 5/16 (2006.01); G06F 30/20 (2020.01); G06F 30/337 (2020.01); G06F 30/373 (2020.01); G06F 30/398 (2020.01); G06N 10/40 (2022.01); G06N 10/60 (2022.01); G06N 10/00 (2022.01); G06F 15/16 (2006.01)
CPC G06N 10/00 (2019.01) [G06F 15/16 (2013.01); G06F 30/20 (2020.01); G06F 30/337 (2020.01); G06F 30/373 (2020.01); G06F 30/398 (2020.01); G06N 10/40 (2022.01)] 17 Claims
OG exemplary drawing
 
1. A computer implemented method for approximating a target quantum state, the method comprising:
receiving data representing the target quantum state of a quantum system, wherein the target quantum state is defined as a result of applying a specific quantum circuit to an initial quantum state of the quantum system;
determining an approximate quantum circuit that approximates the specific quantum circuit by adaptively adjusting a number of T gates available to the specific quantum circuit; and
applying the determined approximate quantum circuit to the initial quantum state to obtain an approximation of the target quantum state.