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    Area of Science:

    • Photonics
    • Optical Computing
    • Graph Theory

    Background:

    • Cognitive photonic networks offer potential for solving computationally hard problems.
    • Developing compact, scalable photonic chips is crucial for advancing optical computing and algorithm optimization.

    Purpose of the Study:

    • To demonstrate a femtosecond laser-written optical oracle for solving the Hamiltonian path problem.
    • To showcase the implementation of graph theory problems on integrated photonic networks.

    Main Methods:

    • Fabrication of an optical oracle using cascaded directional couplers in glass via femtosecond laser writing.
    • Interrogation of the integrated photonic chip with ultrashort laser pulses.
    • Utilizing an optical correlator to distinguish light paths and infer Hamiltonian path existence.

    Main Results:

    • Successfully implemented a solution for the Hamiltonian path problem on an integrated photonic network.
    • Demonstrated the ability to distinguish different light paths within the network.
    • Showcased the potential for downscaling network size and speeding up execution times for graph theory problems.

    Conclusions:

    • Integrated photonic networks are suitable for implementing graph theory problems.
    • Femtosecond laser writing provides a flexible fabrication technique for optical computing devices.
    • This approach offers a pathway to more efficient and compact solutions for complex computational challenges.