US-20260127708-A1 - OPTICAL CONVOLUTION COMPUTING APPARATUS AND OPERATING METHOD OF OPTICAL CONVOLUTION COMPUTING APPARATUS

US20260127708A1US 20260127708 A1US20260127708 A1US 20260127708A1US-20260127708-A1

Abstract

An optical convolution computing apparatus includes a first spatial light modulator that receives illumination light and first input data in a spatial domain and outputs modulated light, a transform device that receives kernel data in the spatial domain and generates kernel phase data and kernel amplitude data in a Fourier domain by performing a fast Fourier transform, a first optical transform device that generates first transformed light by performing an optical Fourier transform, a second spatial light modulator that outputs first element-wise produced light by performing a first element-wise product operation, a third spatial light modulator that outputs second element-wise produced light by performing a second element-wise product operation, a second optical transform device that generates second transformed light by performing an optical inverse Fourier transform, and an image sensor that generates output data based on the second transformed light.

Inventors

Jin Hwa GENE
Jong Moo SOHN

Assignees

ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Dates

Publication Date: 20260507
Application Date: 20251105
Priority Date: 20241107

Claims (20)

1 . An optical convolution computing apparatus that performs a convolutional operation, the apparatus comprising: a first spatial light modulator configured to receive illumination light and first input data in a spatial domain and to output modulated light by modulating the illumination light based on the first input data; a transform device configured to receive kernel data in the spatial domain and to generate kernel phase data and kernel amplitude data in a Fourier domain by performing a fast Fourier transform on the kernel data; a first optical transform device configured to generate first transformed light by performing an optical Fourier transform on the modulated light; a second spatial light modulator configured to output first element-wise produced light by performing a first element-wise product operation on the first transformed light and the kernel amplitude data; a third spatial light modulator configured to output second element-wise produced light by performing a second element-wise product operation on the first element-wise produced light and the kernel phase data; a second optical transform device configured to generate second transformed light by performing an optical inverse Fourier transform on the second element-wise produced light; and an image sensor configured to generate output data based on the second transformed light.
2 . The apparatus of claim 1 , wherein the first element-wise produced light includes Fourier plane information of the second spatial light modulator.
3 . The apparatus of claim 2 , wherein each of a value of the kernel amplitude data and a value of the kernel phase data is positive.
4 . The apparatus of claim 3 , wherein the value of the kernel amplitude data is included within a first normalization range, and wherein the value of the kernel phase data is included within a second normalization range.
5 . The apparatus of claim 4 , wherein the image sensor further receives local oscillator light, and wherein the image sensor generates the output data by using a homodyne detection method based on the second transformed light and the local oscillator light.
6 . The apparatus of claim 5 , wherein a phase difference between the second transformed light and the local oscillator light is 0 or π.
7 . The apparatus of claim 6 , wherein each of the illumination light and the local oscillator light is coherent light.
8 . The apparatus of claim 7 , wherein a value of the first input data is a real number, and wherein the optical convolution computing apparatus performs the convolutional operation on each of a first positive part and a first negative part of the first input data.
9 . The apparatus of claim 8 , wherein a result of the convolutional operation on the first input data is a sum of a result of the convolutional operation on the first positive part and a result of the convolutional operation on the first negative part.
10 . The apparatus of claim 9 , wherein the result of the convolutional operation on the first input data is defined as second input data, and wherein the optical convolution computing apparatus performs the convolutional operation on each of a second positive part and a second negative part of the second input data.
11 . The apparatus of claim 7 , further comprising: a fourth spatial light modulator configured to correct a phase of the local oscillator light.
12 . The apparatus of claim 11 , further comprising: a digital micromirror device configured to reflect the illumination light to the first spatial light modulator; and a wedge prism configured to control a path of the modulated light.
13 . A method for operating an optical convolution computing apparatus that performs a convolutional operation, the method comprising: outputting, by a first spatial light modulator, modulated light by modulating illumination light based on first input data; generating, by a transform device, kernel phase data and kernel amplitude data in a Fourier domain by performing a fast Fourier transform on kernel data in a spatial domain; generating, by a first optical transform device, first transformed light by performing an optical Fourier transform on the modulated light; outputting, by a second spatial light modulator, first element-wise produced light by performing a first element-wise product operation on the first transformed light and the kernel amplitude data; outputting, by a third spatial light modulator, second element-wise produced light by performing a second element-wise product operation on the first element-wise produced light and the kernel phase data; generating, by a second optical transform device, second transformed light by performing an optical inverse Fourier transform on the second element-wise produced light; and generating, by an image sensor, output data based on the second transformed light.
14 . The method of claim 13 , wherein the first element-wise produced light includes Fourier plane information of the second spatial light modulator.
15 . The method of claim 14 , wherein each of a value of the kernel amplitude data and a value of the kernel phase data is positive.
16 . The method of claim 15 , wherein the value of the kernel amplitude data is included within a first normalization range, and wherein the value of the kernel phase data is included within a second normalization range.
17 . The method of claim 16 , wherein the generating, by the image sensor, of the output data based on the second transformed light includes: receiving, by the image sensor, local oscillator light; and generating, by the image sensor, the output data by using a homodyne detection method based on the second transformed light and the local oscillator light.
18 . The method of claim 17 , wherein a phase difference between the second transformed light and the local oscillator light is 0 or π.
19 . The method of claim 18 , further comprising: correcting, a fourth spatial light modulator, a phase of the local oscillator light.
20 . The method of claim 19 , wherein the optical convolution computing apparatus includes: a digital micromirror device configured to reflect the illumination light to the first spatial light modulator, and a wedge prism configured to control a path of the modulated light.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority under 35 U.S.C. § 119 to Korean Patent Application No. 10-2024-0156989 filed on Nov. 7, 2024 and No. 10-2025-0143408 filed on Oct. 1, 2025, in the Korean Intellectual Property Office, the disclosures of which are incorporated by reference herein in their entireties. BACKGROUND Embodiments of the present disclosure described herein relate to an optical convolution computing apparatus and an operating method of the optical convolution computing apparatus, and more particularly, relate to an optical convolution computing apparatus that performs a convolutional operation by using image data in a spatial domain and kernel data in a spatial domain having real values, and an operating method of the optical convolution computing apparatus. An optical convolution operator is one of the optical computing apparatuses for implementing an optical convolutional artificial neural network. A conventional optical convolution operator has the form of an optical 4f-system based on Fourier optics, and is a device that performs convolutional operations by using a spatial domain image and a Fourier domain kernel. The spatial domain image and the Fourier domain kernel are obtained by converting electronic signals to optical signals by using a device called a spatial light modulator. The electronic signals input to the spatial light modulator may only have positive values. Such a system is difficult to apply to a convolutional electronic computer-based convolutional artificial neural network structure, which mainly performs the convolution of a spatial domain kernel and a spatial domain insertion image over a range of real numbers. SUMMARY Embodiments of the present disclosure provide an optical convolution computing apparatus that performs a convolutional operation by using image data in a spatial domain, and kernel data in a spatial domain having real values. According to an embodiment, an optical convolution computing apparatus that performs a convolutional operation includes a first spatial light modulator that receives illumination light and first input data in a spatial domain and outputs modulated light by modulating the illumination light based on the first input data, a transform device that receives kernel data in the spatial domain and generates kernel phase data and kernel amplitude data in a Fourier domain by performing a fast Fourier transform on the kernel data, a first optical transform device that generates first transformed light by performing an optical Fourier transform on the modulated light, a second spatial light modulator that outputs first element-wise produced light by performing a first element-wise product operation on the first transformed light and the kernel amplitude data, a third spatial light modulator that outputs second element-wise produced light by performing a second element-wise product operation on the first element-wise produced light and the kernel phase data, a second optical transform device that generates second transformed light by performing an optical inverse Fourier transform on the second element-wise produced light, and an image sensor that generates output data based on the second transformed light. In an embodiment, the first element-wise produced light includes Fourier plane information of the second spatial light modulator. In an embodiment, each of a value of the kernel amplitude data and a value of the kernel phase data is positive. In an embodiment, the value of the kernel amplitude data is included within a first normalization range, and the value of the kernel phase data is included within a second normalization range. In an embodiment, the image sensor further receives local oscillator light. The image sensor generates the output data by using a homodyne detection method based on the second transformed light and the local oscillator light. In an embodiment, a phase difference between the second transformed light and the local oscillator light is 0 or π. In an embodiment, each of the illumination light and the local oscillator light is coherent light. In an embodiment, a value of the first input data is a real number. The optical convolution computing apparatus performs the convolutional operation on each of a first positive part and a first negative part of the first input data. In an embodiment, a result of the convolutional operation on the first input data is a sum of a result of the convolutional operation on the first positive part and a result of the convolutional operation on the first negative part. In an embodiment, the result of the convolutional operation on the first input data is defined as second input data. The optical convolution computing apparatus performs the convolutional operation on each of a second positive part and a second negative part of the second input data. In an embodiment, the apparatus further includes a fourth spatial light modulator that corrects a phase of the lo