During the 2023-2024 period, the OptiQ project made significant progress in quantum computing, image processing, and secure communication. In quantum communication and computing, an experimental framework for entangled photon generation was developed using ppKTP and BBO crystals. An optical setup for photon entanglement, including a narrow-bandwidth laser and coincidence detection system, was implemented. Work focused on refining photon detection and improving experimental conditions. Initial tests on quantum teleportation and image representation in optical circuits were conducted. The project also began a Bell’s inequality validation experiment with human participation, developing an interactive quantum game and automating optical setups to enhance precision.
In augmented reality for quantum optical systems, a holographic AR-based quantum optics simulator was developed, enabling interactive design and visualization of quantum circuits. Fiducial marker recognition and 3D spatial mapping were implemented for precise optical setup alignment. A prototype AR system for quantum optics design was created, allowing researchers to construct and visualize experiments in real time. An optical device recognition system was also developed and integrated into laboratory setups, ensuring accurate AR-based visualization of quantum experiments. Ongoing work includes improving real-time visualization of quantum states and interaction features in AR.
For quantum image processing and optimization on NISQ computers, the General Quantum Image Encoding (GQIE) framework was developed, unifying different quantum image encoding methods for systematic testing across multiple quantum platforms. More than ten encoding methods were implemented and tested on IBM, AWS, and Xanadu quantum hardware. Extensive error analysis and mitigation experiments led to the development of the Phase Distortion Unraveling (PDU) technique, which enhances image reconstruction accuracy by correcting quantum noise effects. A hybrid quantum-classical object detection algorithm was developed and tested on real quantum hardware, showing promising results. A novel classifier representation using tensor fields was introduced, leveraging geometric structures for improved flexibility in quantum machine learning.
In quantum security research, a comprehensive assessment of error sources in NISQ quantum systems was conducted, analyzing decoherence, gate noise, and measurement errors. AI-assisted quantum error mitigation was explored, and generative adversarial networks (GANs) were implemented to enhance quantum image reconstruction, significantly reducing errors. A differential enhancement measurement simulator was developed to improve photon correlation detection, with successful initial tests demonstrating feasibility for low-voltage and low-current quantum security applications. Research on quantum-resistant security protocols was initiated, focusing on detecting quantum-enabled attacks and vulnerabilities in hybrid quantum-classical security systems.
Across all research areas, OptiQ has successfully developed experimental frameworks, validated key quantum algorithms, and created tools to support quantum-enhanced computing, security, and optical design. The project remains on track to achieve its final objectives by 2026, with ongoing research and prototype testing advancing toward practical implementations. Future work will expand experimental validations, refine hybrid quantum-classical approaches, and integrate quantum security solutions with real-world communication systems. The continued development of quantum-enhanced image processing, AR-assisted quantum design, and secure quantum communication techniques will contribute to advancements in artificial intelligence, cybersecurity, and quantum information science.
