The emergence of quantum computing has transformed our approach to complex computational problems by leveraging the principles of quantum mechanics. A key feature of quantum computers is their unique ability to process and analyze input data. However, today’s quantum computers still face challenges with high error rates, noise, and short qubit coherence times, which limit their reliability and scalability. In this paper, we propose integrating input data as a high-level network of clocks through a newly developed simulator. This simulator dynamically acquires input data, detects objects, and analyzes their motion, constructing a high-level network of periodically rotating clocks. These clocks are grouped and organized into a cone-shaped structure, making them suitable for processing by a quantum computer as a frequency spectrum to explore more probable solutions to the input problem. This approach holds the potential for exponential speedup in processing complex datasets and simulations.