Quantum Kernel Data Generation and Classification System

ChangeBridge: Patent Apps - AI & Computing (G06N)

Published October 1st, 2024

Detected April 3rd, 2026

Summary

USPTO published patent application US20260094035A1 for a quantum kernel-based data generation and classification system. Inventors include Shungo Miyabe, Noriaki Shimada, Sudeep Ghosh, Jae-Eun Park, and Abhijit Mitra. The system employs quantum kernels to generate new datasets from input data and classify information, with potential applications in quantum computing and machine learning.

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What changed

USPTO published patent application US20260094035A1 (filed October 1, 2024, Application No. 18903716) for a system and method using quantum kernels to generate and classify datasets. The technology comprises an access component to receive input datasets, a data generation component employing quantum kernels to produce multiple new datasets, and a classification component. The patent covers CPC classifications G06N 10/20 (quantum computing models) and G06N 10/60 (quantum kernel methods).

This is a published patent application notice with no compliance requirements or deadlines. Companies developing quantum computing applications, machine learning systems, or data classification technology may wish to review the patent claims to assess potential licensing needs or freedom-to-operate concerns. No immediate action is required as patent applications do not impose regulatory obligations.

Source document (simplified)

← USPTO Patent Applications

DATA GENERATION AND CLASSIFICATION BASED ON QUANTUM KERNELS

Application US20260094035A1 Kind: A1 Apr 02, 2026

Inventors

Shungo Miyabe, Noriaki Shimada, Sudeep Ghosh, Jae-Eun Park, Abhijit Mitra

Abstract

One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to data classification based on quantum kernels. For example, a system can comprise a memory that can store computer executable components. The system can further comprise a processor that can execute the computer executable components stored in the memory, where the computer executable components can comprise an access component that can access an input dataset. The computer executable components can further comprise a data generation component that can generate, based on the input dataset, a plurality of new datasets by employing a plurality of quantum kernels.