Mastercard International Incorporated (20240320295). Variable Freezing Method for an Objective Optimisation Problem simplified abstract
Contents
Variable Freezing Method for an Objective Optimisation Problem
Organization Name
Mastercard International Incorporated
Inventor(s)
Nicola Mariella of Oranmore (IE)
Stephen Patrick Flinter of Dublin (IE)
Variable Freezing Method for an Objective Optimisation Problem - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320295 titled 'Variable Freezing Method for an Objective Optimisation Problem
Simplified Explanation: The patent application describes a computer-implemented method for optimizing an objective optimization problem by freezing certain variables and determining an equivalent optimization problem that can be solved on a quantum computer using fewer quantum bits.
Key Features and Innovation:
- Optimization method for objective optimization problems
- Freezing variables to reduce quantum bit usage
- Determining equivalent optimization problems for quantum computer solving
Potential Applications: This technology could be applied in various fields such as finance, logistics, and machine learning where optimization problems are common.
Problems Solved: This technology addresses the challenge of optimizing objective optimization problems efficiently on quantum computers by reducing the required quantum bits.
Benefits:
- Improved efficiency in solving optimization problems
- Reduced quantum bit usage
- Potential for faster computation on quantum computers
Commercial Applications: Optimizing supply chain logistics, financial portfolio management, and machine learning algorithms are potential commercial applications of this technology.
Prior Art: Prior research in quantum optimization algorithms and methods for reducing quantum bit usage in solving complex problems may be relevant to this technology.
Frequently Updated Research: Stay updated on advancements in quantum computing algorithms and optimization techniques to enhance the efficiency of this technology.
Questions about Quantum Optimization: 1. How does freezing variables help in reducing quantum bit usage in optimization problems? 2. What are the key differences between solving an objective optimization problem directly and solving an equivalent optimization problem on a quantum computer?
Original Abstract Submitted
a computer implemented method for optimising, an objective optimisation problem. the methods begins by receiving the objective optimisation problem. the objective optimisation problem is represented by an l�l objective matrix comprising a plurality of matrix components a set of frozen variables is received. the method determines a set of freezable matrix components corresponding to the set of frozen variables. then, a contribution vector is determined based on the set of freezable matrix components and the set of frozen variables an equivalent optimisation problem is determined based on the contribution vector and the objective optimisation problem. the equivalent optimisation problem excludes the freezable matrix components such that the equivalent optimisation problem may be solved on a quantum computer using fewer quantum bits than the objective optimisation problem would require.
