20240037439. QUANTUM SYSTEM SELECTION VIA COUPLING MAP COMPARISON simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

QUANTUM SYSTEM SELECTION VIA COUPLING MAP COMPARISON

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

John S. Werner of Fishkill NY (US)

Vladimir Rastunkov of Mundelein IL (US)

[[:Category:Frederik Frank Fl�ther of Schlieren (CH)|Frederik Frank Fl�ther of Schlieren (CH)]][[Category:Frederik Frank Fl�ther of Schlieren (CH)]]

QUANTUM SYSTEM SELECTION VIA COUPLING MAP COMPARISON - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240037439 titled 'QUANTUM SYSTEM SELECTION VIA COUPLING MAP COMPARISON

Simplified Explanation

The patent application describes systems and techniques that enable the selection of a quantum computing system for executing a quantum machine learning (QML) model. The selection is based on comparing the coupling maps of different quantum computing systems with the coupling map on which the QML model was trained. If there is a topological match between the coupling maps, the QML model can be executed on the selected quantum computing system. Otherwise, the QML model is adjusted and executed on the quantum computing system.

• The system allows access to a quantum machine learning (QML) model.
• The system compares the coupling maps of different quantum computing systems.
• The system identifies a quantum computing system for executing the QML model based on the comparison.
• If there is a topological match between the coupling maps, the QML model can be executed on the selected quantum computing system.
• If there is no topological match, the QML model is adjusted and executed on the quantum computing system.

Potential applications of this technology:

• Quantum machine learning: The technology enables the selection of the most suitable quantum computing system for executing QML models, improving the efficiency and accuracy of quantum machine learning algorithms.
• Quantum computing optimization: By comparing coupling maps, the system can identify quantum computing systems that are better suited for specific tasks, leading to improved performance and optimization of quantum computing resources.

Problems solved by this technology:

• Inefficient QML model execution: The technology addresses the problem of executing QML models on unsuitable quantum computing systems by selecting the most appropriate system based on coupling map comparison.
• Resource optimization: By selecting the quantum computing system that matches the QML model's coupling map, the technology optimizes the utilization of quantum computing resources, reducing wastage and improving efficiency.

Benefits of this technology:

• Improved QML model execution: By selecting the quantum computing system with a matching coupling map, the technology ensures that QML models are executed on the most suitable hardware, leading to improved performance and accuracy.
• Resource efficiency: The technology optimizes the utilization of quantum computing resources by selecting the most appropriate system, reducing resource wastage and improving overall efficiency in quantum computing operations.

Original Abstract Submitted

systems/techniques that facilitate quantum system selection via coupling map comparison are provided. in various embodiments, a system can access a quantum machine learning (qml) model. in various aspects, the system can identify, from a set of quantum computing systems, a quantum computing system for the qml model, based on a comparison between a first coupling map of the quantum computing system and a second coupling map on which the qml model was trained. if the second coupling map topologically matches the first coupling map or topologically matches a subgraph of the first coupling map, the system can execute the qml model on the quantum computing system. otherwise, the system can adjust the qml model and can accordingly execute the adjusted qml model on the quantum computing system.