20240028537. Hidden Flow Discovery simplified abstract (Mastercard International Corporation)

Hidden Flow Discovery

Organization Name

Mastercard International Corporation

Inventor(s)

Nicola Mariella of Oranmore (IE)

Stephen Patrick Flinter of Tenenure (IE)

Hidden Flow Discovery - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240028537 titled 'Hidden Flow Discovery

Simplified Explanation

The patent application describes a method for determining internal flow within a processing node. The method involves receiving an input flow vector and an output flow vector, which represent the monetary amount exiting the processing node. The objective is to determine the input flow matrix and output flow matrix by solving an optimization problem subject to constraints. A quadratic unconstrained binary optimization (QUBO) formulation is then determined to implement the optimization problem. The QUBO formulation is solved by a quantum computer, providing a solution representative of the input flow matrix and output flow matrix. Finally, a probability matrix is generated by a classical computer, indicating the probability of an internal flow connecting an input entry to an output entry.

• The method involves receiving input and output flow vectors representing monetary amounts exiting a processing node.
• An optimization problem is determined to find the input and output flow matrices.
• A QUBO formulation is created to implement the optimization problem.
• The QUBO formulation is solved by a quantum computer to obtain a solution.
• A probability matrix is generated by a classical computer to indicate the probability of internal flows connecting input and output entries.

Potential Applications:

• Financial systems: This technology can be applied in financial systems to optimize the flow of monetary transactions within processing nodes.
• Supply chain management: The method can be used to optimize the flow of goods and resources within supply chain networks.
• Transportation networks: It can be applied to optimize the flow of passengers or goods within transportation networks, such as airlines or logistics companies.

Problems Solved:

• Optimization: The method solves the problem of determining the optimal flow of resources or transactions within a processing node.
• Efficiency: By optimizing the flow, it improves the efficiency of resource allocation and reduces bottlenecks within the system.

Benefits:

• Improved resource allocation: The technology helps in allocating resources more effectively by optimizing the flow within processing nodes.
• Cost savings: By optimizing the flow, it reduces inefficiencies and minimizes unnecessary costs.
• Enhanced system performance: The method improves the overall performance of systems by optimizing the internal flow, leading to better throughput and reduced delays.

Original Abstract Submitted

an internal flow determination method comprising the steps of: receiving, at a classical computer, an input flow vector comprising a plurality of input entries. then, receiving an output flow vector comprising a plurality of output entries. said output entries are indicative of a monetary amount exiting the processing node. determining an objective optimization problem subject to one or more constraints, wherein an objective of the objective optimization problem is to determine: an input flow matrix and an output flow matrix. then, determining a quadratic unconstrained binary optimization (qubo) formulation suitable for implementing the objective optimization problem. solving, by a quantum computer, the qubo formulation, thereby providing a solution representative of the input flow matrix and the output flow matrix. finally, generating, by the classical computer, a probability matrix indicative of a probability that an internal flow of the processing node connects an input entry to an output entry.