US Patent Application 18311178. CALIBRATION OF QUANTUM PROCESSOR OPERATOR PARAMETERS simplified abstract

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CALIBRATION OF QUANTUM PROCESSOR OPERATOR PARAMETERS

Organization Name

Google LLC


Inventor(s)

Paul Klimov of Santa Barbara CA (US)


CALIBRATION OF QUANTUM PROCESSOR OPERATOR PARAMETERS - A simplified explanation of the abstract

  • This abstract for appeared for US patent application number 18311178 Titled 'CALIBRATION OF QUANTUM PROCESSOR OPERATOR PARAMETERS'

Simplified Explanation

This abstract describes methods, systems, and apparatus for determining operating parameters for a quantum processor with multiple interacting qubits. The method involves creating a graph with nodes representing qubits and edges representing interactions between qubits. Each node and edge is associated with an operating parameter. An algorithm is selected to traverse the graph based on a traversal rule. Disjoint subsets of nodes or edges are identified based on their relationship via the traversal rule. Calibrated values for the nodes or edges in each subset are determined using a stepwise constrained optimization process, where constraints are determined using previously calibrated operating parameters.


Original Abstract Submitted

Methods, systems and apparatus for determining operating parameters for a quantum processor including multiple interacting qubits. In one aspect, a method includes generating a graph of nodes and edges, wherein each node represents a respective qubit and is associated with an operating parameter of the respective qubit, and wherein each edge represents a respective interaction between two qubits and is associated with an operating parameter of the respective interaction; selecting an algorithm that traverses the graph based on a traversal rule; identifying one or multiple disjoint subsets of nodes or one or multiple disjoint subsets of edges, wherein nodes in a subset of nodes and edges in a subset of edges are related via the traversal rule; and determining calibrated values for the nodes or edges in each subset using a stepwise constrained optimization process where constraints are determined using previously calibrated operating parameters.