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Combinatorial optimization (CO) has a broad range of applications in various fields, including operations research, computer science, and artificial intelligence. However, many of these problems are classified as nondeterministic polynomial‐time (NP)‐complete or NP‐hard problems, which are known for their computational complexity and cannot be solved in polynomial time on traditional digital computers. To address this challenge, continuous‐time Ising machine solvers have been developed, utilizing different physical principles to map CO problems to ground state finding. However, most Ising machine prototypes operate at speeds comparable to digital hardware and rely on binarizing node states, resulting in increased system complexity and further limiting operating speed. To tackle these issues, a novel device‐algorithm co‐design method is proposed for fast sub‐optimal solution finding with low hardware complexity. On the device side, a piezoelectric lithium niobate (LiNbO3) microelectromechanical system (MEMS) oscillator network‐based Ising machine without second‐harmonic injection locking (SHIL) is devised to solve Max‐cut and graph coloring problems. The LiNbO3 oscillator operates at speeds greater than 9 GHz, making it one of the fastest oscillatory Ising machines. System‐wise, an innovative grouping method is used that achieves a performance guarantee of 0.878 for Max‐cut and 0.658 for graph coloring problems, which is comparable to Ising machines that utilize binarization. [ABSTRACT FROM AUTHOR]

As a clean and renewable energy, wave energy has abundant reserves, and its reasonable development and utilization can effectively alleviate the problems of energy shortage and environmental pollution. This paper proposes a mechanical rectification wave energy converter. The reciprocating linear motion of the buoy is directly converted into the rotary motion through the ball screw. The magnetic coupling force transmission system is adopted to ensure the sealing of the device. Using mechanical rectification mechanism to ensure the service life of the generator. In addition, a dynamic model of the mechanical rectification wave energy converter is established. Through simulation analysis, the curve of power with load resistance is obtained. And there is an optimal load resistance value corresponding to the maximum power in different wave conditions. In order to improve the power generation efficiency, the maximum power point tracking control algorithm is designed based on the admittance differentiation method. By controlling the duty cycle of the switch tube in the Buck‐Boost chopper circuit, the variable load is realized, and then the maximum power point tracking control is realized. Finally, simulation analysis verifies the feasibility of the algorithm under different wave conditions. [ABSTRACT FROM AUTHOR]