MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641107185 A) filed by Karpagam College Of Engineering; Karpagam Academy Of Higher Education; Dr. P. Shanthi; and Sridhar R on September 02, 2026, for Quantum Noise Intelligence: A Hybrid Learning Approach For Noise Classification In Nisq Systems.
Inventors include Dr. P. Shanthi; and Sridhar R.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: Noisy Intermediate-Scale Quantum (NISQ) systems represent the current generation of quantum computing devices, characterized by limited qubit counts and significant susceptibility to noise. Noise arising from decoherence, gate imperfections, measurement errors, and environmental disturbances adversely affects computational accuracy and system reliability. This project proposes Quantum Noise Intelligence, a hybrid learning-based framework designed to analyze and classify noise patterns in NISQ systems. The proposed approach integrates classical machine learning techniques with statistical and quantum-inspired feature extraction methods to identify noise characteristics from quantum system behavior. By treating noise as an analyzable phenomenon rather than solely as a disturbance, the framework aims to improve noise interpretability, enable systematic classification of noise types, and support enhanced diagnostic analysis. The system leverages noise- sensitive features such as error probabilities, measurement variance, and state fidelity deviations to build predictive classification models. The outcomes of this study are expected to contribute to improved understanding of quantum noise behavior, assist error mitigation strategies, and enhance the reliability and performance evaluation of NISQ systems.
Disclaimer: Curated by HT Syndication.
