US 12,210,933 B2
Quantum statistic machine
Masoud Mohseni, Calabasas, CA (US); and Hartmut Neven, Malibu, CA (US)
Assigned to Google LLC, Mountain View, CA (US)
Filed by Google LLC, Mountain View, CA (US)
Filed on Jan. 4, 2024, as Appl. No. 18/404,365.
Application 18/404,365 is a continuation of application No. 17/678,897, filed on Feb. 23, 2022, granted, now 11,900,215.
Application 17/678,897 is a continuation of application No. 16/067,560, granted, now 11,288,585, issued on Mar. 29, 2022, previously published as PCT/US2016/068308, filed on Dec. 22, 2016.
Claims priority of provisional application 62/273,282, filed on Dec. 30, 2015.
Prior Publication US 2024/0412086 A1, Dec. 12, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 10/00 (2022.01); G06N 20/00 (2019.01)
CPC G06N 10/00 (2019.01) [G06N 20/00 (2019.01)] 19 Claims
OG exemplary drawing
 
1. A method performed by a quantum processor, the method comprising:
receiving data specifying a machine learning inference problem;
preparing a quantum system in an initial quantum state, wherein the initial quantum state is a tensor product of i) an initial state of the quantum processor comprising a plurality of logical quantum nodes and control quantum nodes and ii) a state of an environment modelled by a thermal bath;
evolving the initial quantum state under a dissipative quantum map until a steady state is reached, the steady state encoding a solution to the machine learning inference problem, wherein the dissipative quantum map comprises a map induced by a Hamiltonian of the logical quantum nodes, control quantum nodes, and interactions between the logical quantum nodes, control quantum nodes, and the bath; and
performing a quantum measurement on the steady state to obtain a measurement outcome that represents an energy value of the steady state and that comprises the solution to the machine learning inference problem;
wherein the interactions between the logical quantum nodes and the control quantum nodes comprise interactions that have been configured, through one or more hidden node training phases and control node training phases, to encode the solution to the machine learning inference problem in quantum statistics of the steady state, wherein during each hidden node training phase the control quantum nodes are set to a non-interacting state and learning and unlearning subphases of hidden quantum nodes included in the logical quantum nodes are iteratively changed.