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Updated: Jun 10, 2025

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与稀疏和更高阶的Ising机器进行全对全的重新配置

Srijan Nikhar1, Sidharth Kannan1, Navid Anjum Aadit1

  • 1Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA.

Nature communications
|October 17, 2024
PubMed
概括

本研究评估基于概率位 (p-bit) 的Ising机器 (IM) 来解决复杂的优化问题. FPGA实现显示了竞争优势,并有可能在未来对优化硬件进行重大改进.

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