MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641090054 A) filed by Sathyabama Institute Of Science And Technology on July 24, 2026, for Adaptive Hybrid Quantum–classical Computing System With Dynamic Workload Partitioning For Large-Scale Optimization.
Inventors include Ms. R. Ramyabharathi; Dr. N. Srinivasan; Ms. K. Triveni; Ms. G. Abirami; Ms. Gayathri Sivakumar; and Mr. S. Praveen.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: The present invention relates to the design and implementation of an adaptive hybrid quantum-classical computing system with workload partitioning for large-scale optimization that effectively splits computational tasks among quantum and classical computation capabilities to achieve better optimization efficiency and higher quality solutions. The adaptive engine evaluates features of a problem, computational complexity, available computational hardware, and performance in real time. Then, based on received information, the optimization task is split into two parts: suitable for quantum and classical computing respectively. Parallel execution of both of these processes is enabled through effective workload partitioning. Using machine learning techniques, the partitioning algorithm is refined to minimize execution time, energy cost, and computation load to produce the highest possible quality of solutions. This approach can be applied in combinatorial optimization, logistics, scheduling, finance, scientific simulations, and industry planning. By combining both quantum and classical computing paradigms with the help of an adaptive system, it is possible to solve large-scale optimization problems that cannot be solved efficiently by standard computational methods. FIG.1
Disclaimer: Curated by HT Syndication.
