Publication date: 15th April 2025
The rapid development of artificial intelligence in the big data era has increased the demand for solving complex combinatorial optimization problems (COPs) such as traveling salesperson problem and vehicle routing problem (VRP), which are difficult to efficiently handle with conventional von-Neumann computing systems. Quantum computing, which uses quantum bits (qubits) that utilize the superposition of spin as ‘0’ and ‘1’, shows the potential to solve these COPs efficiently. However, constructing cryogenic operating environments to not only eliminate unwanted noise but also accurately detect the intrinsic spin behavior remains a noticeable drawback. To address these challenges, a new probabilistic computing (P-computing) has recently been proposed as an alternative to emulate the quantum supremacy even at room temperature.
Here, we showed probabilistic bits (P-bits) with a novel Ti/SiOx/Ti stack, which is a fundamental building block for P-computing. The SiOx layer typically exhibits reliable TS behavior, resulting in robust voltage oscillations. When a Ti scavenging layer was introduced at the interface, oxygen vacancies were provided to the SiOx, causing oscillation to occur probabilistically. Through physical analysis and numerical calculations, the underlying mechanism of P-bit operation in Ti/SiOx/Ti stack was investigated by considering the charging and discharging process. This results in a sigmoidal probability curve for ‘1’ over a wide range of input voltage. Therefore, leveraging the developed SiOx-based P-bit can speed up the algorithm for finding the optimal path in the vehicle routing problem, which is verified through MATLAB simulation.
This work was supported by the Technology Innovation Program (or Industrial Strategic Technology Development Program) (RS-2023-00231956) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea) (1415187475).
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