在芯片上,用于神经形态计算的声子-磁子储存器
Dmytro D Yaremkevich1, Alexey V Scherbakov2, Luke De Clerk3,4
1Experimentelle Physik 2, Technische Universität Dortmund, D-44227, Dortmund, Germany.
Nature communications
|December 14, 2023
概括
这项研究展示了在芯片上的储存器计算,使用纳米设备中的声子 - 磁子相互作用. 这种方法有效地将视觉形状分开,为未来的神经形态架构铺平了道路.
科学领域:
- 物理 物理学 物理
- 材料科学 材料科学 材料科学
- 计算机科学 计算机科学
背景情况:
- 储计算将信号映射到动态系统的相位空间,用于神经网络识别.
- 实现芯片上的储计算需要能够进行复杂的信号处理的新型物理系统.
研究的目的:
- 通过使用基于声子 - 磁子相互作用的纳米设备来实现储计算.
- 为了证明激光输入编码的视觉形状的分离.
主要方法:
- 制造了一种纳米设备,其中包括半导体声子波导和铁磁层.
- 输入信号被编码为声波波包使用脉冲写字激光,与磁子相互作用.
- 用第二个激光读取输出信号,该激光对声 - 磁模式相互作用敏感.
主要成果:
- 纳米设备储存器成功地分离了由写激光器绘制的视觉形状.
- 在一个与单个像素相当的区域中实现了形状分离.
- 波 - 马格农相互作用对激光定位非常敏感.
结论:
- 波 - 马格农相互作用是芯片储存器计算的可行硬件基础.
- 这项工作推动了未来神经形态架构的发展.
- 展示的纳米设备提供了高效的芯片上信号处理能力.
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