Mumbai, April 9 -- The patent highlights a groundbreaking approach to enhance the scalability and performance of quantum machine learning (QML) on near-term quantum computing platforms, including quantum simulators.

This solution transforms high-dimensional classical input data into an enhanced feature space in quantum format. The feature space transformation ensures efficient mapping and preparation for quantum state loading, paving the way for improved quantum data processing and analysis.

The optimal representation method for classical data on quantum systems minimizes the need for additional qubits for higher-dimensional data, handles large feature sets and high volumes of data, and ensures efficient convergence during quantum machi...