利用铌酸锂上的非线性声波器件进行频域计算

mingzhao chai
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摘要

乘积是信号处理、数值模拟和机器学习中的关键计算操作。近年来,光学模拟方法已显示出比数字方法更高的计算性能和更好的能效。然而,模拟计算芯片通常需要较大的面积和复杂的结构才能进行并行计算,因为单个器件元件一次只能执行一个计算操作。在这里,我们利用铌酸锂上的非线性声波器件演示了频域计算,其归一化外部二次谐波发生转换效率约为 5.7 × 10-4 W-1。铌酸锂的二阶和频非线性过程可实现频域编码输入的乘法运算。与模拟方案相比,我们的设备具有明显的设计简洁性,纳米制造只需一次升空。利用一个面积仅为 0.03 平方毫米的声波器件,我们可以同时进行超过 13 万次乘法累加运算。我们的声波装置可应用于实际和复杂的矢量卷积和图像处理。这一演示为频域集成非线性声学计算系统的实验实现奠定了基础,有可能影响声学神经网络和量子计算的未来发展。
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Frequency-domain computing using nonlinear acoustic-wave device on lithium niobate
Multiply-accumulation are crucial computing operations in signal processing, numerical simulations, and machine learning. In recent years, optical analog approaches have demonstrated higher computing performance and better power efficiency than their digital counterparts. However, analog computing chips usually need large areas and complex structures for parallel computing, as a single device element only executes one computing operation at a single time. Here, we demonstrate frequency-domain computing using the nonlinear acoustic-wave devices on lithium niobate, featuring a normalized external second-harmonic generation conversion efficiency of ~ 5.7 × 10-4 W-1. The second-order sum-frequency nonlinear process of lithium niobate enables multiplication of inputs encoded in the frequency domain. Compared to the analog schemes, our device features a notably simpler design, and nanofabrication requires only one lift-off. Using a single acoustic-wave device within an area of 0.03 mm2, we can simultaneously conduct over 130,000 multiply-accumulation operations. Our acoustic-wave device shows applications in real and complex vector convolutions and image processing. This demonstration sets the stage for experimental realizations into frequency-domain integrated nonlinear acoustic computing systems, potentially shaping future developments in acoustic neural networks and quantum computing.
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