17540485. OPTIMIZED SELECTION OF DATA FOR QUANTUM CIRCUITS simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

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OPTIMIZED SELECTION OF DATA FOR QUANTUM CIRCUITS

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

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

Michele Grossi of Prevessin-Möens (FR)

Vaibhaw Kumar of Frederick MD (US)

Robert E. Loredo of North Miami Beach FL (US)

OPTIMIZED SELECTION OF DATA FOR QUANTUM CIRCUITS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17540485 titled 'OPTIMIZED SELECTION OF DATA FOR QUANTUM CIRCUITS

Simplified Explanation

The patent application describes a data selection system for quantum computers that selects a suitable subset of data to be processed by a quantum algorithm.

  • The system compresses and clusters a data set based on a specific distribution criteria.
  • It selects a subset of clustered data that represents the overall data set.
  • The selected subset is processed by a quantum device.
  • The system generates a metric score based on the performance of the quantum algorithm.
  • The selected subset is refined over multiple iterations based on successive metric scores.
  • The process continues until a termination criterion is met.
  • The final selected subset is used as input for the quantum computer to execute the processing task.

Potential Applications

  • Quantum computing tasks that require processing large data sets.
  • Optimization problems that can benefit from quantum algorithms.
  • Machine learning tasks that involve large-scale data analysis.

Problems Solved

  • Overcoming the limitations of input data size for quantum computers.
  • Selecting a representative subset of data for quantum processing.
  • Improving the efficiency and performance of quantum algorithms.

Benefits

  • Enables meaningful computational results with limited input data for quantum computers.
  • Reduces the computational complexity by selecting a subset of data.
  • Improves the overall efficiency and accuracy of quantum algorithms.


Original Abstract Submitted

To obtain meaningful computational results despite limits on the amount of data that can be input to a quantum computer, a data selection system uses an iterative approach to select a suitable subset of data to be input to a quantum device for processing by a quantum algorithm. The system compresses and clusters a data set according to a task-specific distribution criteria and selects a subset of this clustered data corresponding to representative cases of the data. The selected subset is processed by the quantum device and the system generates a metric score based on the degree to which the results satisfy a performance criterion. The selected subset is refined over multiple iterations based on successive metric scores until a termination criterion is reached, and the final selected subset of data is used as input to the quantum computer for execution of the processing task.

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