Abstract
Quantum computing is a rapidly developing technology that, in theory, can solve complex computational problems practically intractable for classical computers. Although the technology offers promising breakthroughs, it is only in the early stages of development, and various quantum computer architectures are emerging. One such new development is the photonic quantum computer. Since the work on discrete optimization using different quantum computer architectures is well studied, in this paper, we experiment with solving a toy instance of the Job-Shop Scheduling problem using a hybrid learning algorithm on a photonic quantum computer simulator. The promising results, combined with some highly desirable properties of photonic quantum computers, show that this new architecture is worth considering for further development and investment in the quantum technology landscape.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
