A Theoretical Framework for Universal Latency Reduction in Hybrid Quantum-Classical Systems

This paper introduces a novel quantum-classical latency reduction formula, representing a theoretical breakthrough in optimizing performance across hybrid systems. Central to our work is \textit{Aneesh Nandan’s Quantum-Classical Latency Reduction Formula}, which models hybrid latency as an exponential function of baseline classical latency and simulated quantum enhancement. The baseline latency (\( L_c \)) was computed using classical performance metrics—CPU usage, GPU load, and frame rate—measured over a 60-second interval. These data were combined with a simulated range of quantum enhancement values and a noise model to account for experimental variability. The resulting hybrid latencies display a consistent exponential decay as quantum contribution increases, validating the formula’s predictive behavior in theory. To the best of our knowledge, this is the first systematic study to propose a dedicated quantum-classical latency reduction formula, establishing a theoretical framework applicable to domains such as virtual reality, augmented reality, gaming engines, autonomous systems, cloud infrastructure, and quantum-edge computing. All quantum computations were simulated on classical hardware; therefore, the observed latency reductions are theoretical. Future validation using physical quantum systems is necessary to confirm the real-world applicability and effectiveness of this model.