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December 6, 2025Proceedings of the ACM on Measurement and Analysis of Computing Systems2 citationsOpen Access

ObliQ: Solving Quadratic Unconstrained Binary Optimization Problems on Real Photonic Quantum Machines

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ARAditya Ranjan

Key Points

  • ObliQ significantly enhances combinatorial optimization processes for QUBO problems.
  • The approach utilizes co-design of hardware and software, improving efficiency in processing.
  • Analysis of hybrid quantum circuits combines problem-customized and parameterized strategies.
  • These advancements indicate substantial promise for photonic quantum computing applications in optimization.

Abstract

Quadratic Unconstrained Binary Optimization (QUBO) problems are central to combinatorial optimization but challenging due to their exponential solution space. We aim to solve QUBO problems on photonic quantum computers via novel problem-customized optimizations and exploiting unique aspects of photonic quantum machine architecture. We present a novel solution, ObliQ , that creates a hybrid quantum circuit composed of two parts: a theoretically grounded, non-tunable, problem-customized quantum circuit and a parameterized variational quantum circuit -- underlined by the co-design of photonic quantum hardware and software.

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Cite This Study

Aditya Ranjan (2025) studied this question.

synapsesocial.com/papers/69337cefb3f947a0a125a357https://doi.org/10.1145/3771573
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