Based on output-oriented education,the OBE(Outcome-Based Education)concept integrates local red culture into the ideological and political course of environmental disciplines,and is an important part of training appli...Based on output-oriented education,the OBE(Outcome-Based Education)concept integrates local red culture into the ideological and political course of environmental disciplines,and is an important part of training applied talents of environmental disciplines in the new era.This educational model makes an innovation on the traditional educational and teaching concepts and centers on students.This paper analyzes the value of integrating local red culture into the ideological and political course under the OBE concept,and puts forward an effective implementation path.展开更多
With the advancement of deep learning and neural networks,the computational demands for applications in wearable devices have grown exponentially.However,wearable devices also have strict requirements for long battery...With the advancement of deep learning and neural networks,the computational demands for applications in wearable devices have grown exponentially.However,wearable devices also have strict requirements for long battery life,low power consumption,and compact size.In this work,we propose a scalable optoelectronic computing system based on an integrated optical convolution acceleration core.This system enables high-precision computation at the speed of light,achieving 7-bit accuracy while maintaining extremely low power consumption.It also demonstrates peak throughput of 3.2 TOPS(tera operations per second)in parallel processing.We have successfully demonstrated image convolution and the typical application of an interactive first-person perspective gesture recognition application based on depth information.The system achieves a comparable recognition accuracy to traditional electronic computation in all blind tests.展开更多
Optical neural networks have emerged as feasible alternatives to their electronic counterparts,offering significant benefits such as low power consumption,low latency,and high parallelism.However,the realization of ul...Optical neural networks have emerged as feasible alternatives to their electronic counterparts,offering significant benefits such as low power consumption,low latency,and high parallelism.However,the realization of ultra-compact nonlinear deep neural networks and multi-thread processing remain crucial challenges for optical computing.We present a monolithically integrated all-optical nonlinear diffractive deep neural network(AON-D^(2) NN)chip for the first time.The all-optical nonlinear activation function is implemented using germanium microstructures,which provide low loss and are compatible with the standard silicon photonics fabrication process.Assisted by the germanium activation function,the classification accuracy is improved by 9.1%for four-classification tasks.In addition,the chip's reconfigurability enables multi-task learning in situ via an innovative cross-training algorithm,yielding two task-specific inference results with accuracies of 95%and 96%,respectively.Furthermore,leveraging the wavelength-dependent response of the chip,the multi-thread nonlinear optical neural network is implemented for the first time,capable of handling two different tasks in parallel.The proposed AON-D^(2)NN contains three hidden layers with a footprint of only 0.73 mm^(2).It can achieve ultra-low latency(172 ps),paving the path for realizing high-performance optical neural networks.展开更多
Optical computing has shown immense application prospects in the post-Moore era.However,as a crucial component of logic computing,the digital multiplier can only be realized on a small scale in optics,restrained by th...Optical computing has shown immense application prospects in the post-Moore era.However,as a crucial component of logic computing,the digital multiplier can only be realized on a small scale in optics,restrained by the limited functionalities and inevitable loss of optical nonlinearity.In this paper,we propose a time-space multiplexed architecture to realize large-scale photonic-electronic digital multiplication.展开更多
The increasing demand for diverse portable high-precision spectral analysis applications has driven the rapid development of spectrometer miniaturization. However, the resolutions of existing miniaturized spectrometer...The increasing demand for diverse portable high-precision spectral analysis applications has driven the rapid development of spectrometer miniaturization. However, the resolutions of existing miniaturized spectrometers mostly remain at the nanometer level, posing a challenge for further enhancement towards achieving picometerlevel precision. Here, we propose an integrated reconstructive spectrometer that utilizes Mach–Zehnder interferometers and a tunable diffraction network. Through random tuning in the time domain and disordered diffraction in the space domain, the random speckle patterns closely related to wavelength information are obtained to construct the transmission matrix. Experimentally, we achieve a high resolution of 100 pm and precisely reconstruct multiple narrowband and broadband spectra. Moreover, the proposed spectrometer features a simple structure, strong portability, and fast sampling speed, which has great potential in the practical application of high-precision portable spectral analysis.展开更多
Despite more than 40 years of development,it remains difficult for optical logic computing to support more than four operands because the high parallelism of light has not been fully exploited in current methods that ...Despite more than 40 years of development,it remains difficult for optical logic computing to support more than four operands because the high parallelism of light has not been fully exploited in current methods that are restrained by inefficient optical nonlinearity and redundant input modulation.In this paper,we propose a large-scale optical programmable logic array(PLA)based on parallel spectrum modulation.By fully exploiting the wavelength resource,an eight-input PLA is experimentally demonstrated with 256 wavelength channels.And it is extended to nine-input PLA through the combination of wavelength’s and spatial dimensions.Based on PLA,many advanced logic functions like 8-256 decoder,4-bit comparator,adder and multiplier,and state machines are first realized in optics.We implement the two-dimensional optical cellular automaton(CA)for what we believe is the first time and run Conway’s Game of Life to simulate the complex evolutionary processes(pulsar explosion,glider gun,and breeder).Other CA models,such as the replicator-like evolution and the nonisotropic evolution to generate the Sierpinski triangle are also demonstrated.Our work significantly alleviates the challenge of scalability in optical logic devices and provides a universal optical computing platform for two-dimensional CA.展开更多
Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms...Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.Photonic accelerators are designed to accelerate specific categories of computing in the optical domain,especially matrix multiplication,to address the growing demand for computing resources and capacity.Photonic matrix multiplication has much potential to expand the domain of telecommunication,and artificial intelligence benefiting from its superior performance.Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors.In this review,we first introduce the methods of photonic matrix multiplication,mainly including the plane light conversion method,Mach–Zehnder interferometer method and wavelength division multiplexing method.We also summarize the developmental milestones of photonic matrix multiplication and the related applications.Then,we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years.Finally,we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.展开更多
As an important computing operation,photonic matrix-vector multiplication is widely used in photonic neutral networks and signal processing.However,conventional incoherent matrix-vector multiplication focuses on real-...As an important computing operation,photonic matrix-vector multiplication is widely used in photonic neutral networks and signal processing.However,conventional incoherent matrix-vector multiplication focuses on real-valued operations,which cannot work well in complex-valued neural networks and discrete Fourier transform.In this paper,we propose a systematic solution to extend the matrix computation of microring arrays from the real-valued field to the complex-valued field,and from small-scale(i.e.,4×4)to large-scale matrix computation(i.e.,16×16).Combining matrix decomposition and matrix partition,our photonic complex matrix-vector multiplier chip can support arbitrary large-scale and complex-valued matrix computation.We further demonstrate Walsh-Hardmard transform,discrete cosine transform,discrete Fourier transform,and image convolutional processing.Our scheme provides a path towards breaking the limits of complex-valued computing accelerator in conventional incoherent optical architecture.More importantly,our results reveal that an integrated photonic platform is of huge potential for large-scale,complex-valued,artificial intelligence computing and signal processing.展开更多
As a resonator-based optical hardware in analog optical computing, a microring synapse can be straightforwardly configured to simulate the connection weights between neurons, but it faces challenges in precision and s...As a resonator-based optical hardware in analog optical computing, a microring synapse can be straightforwardly configured to simulate the connection weights between neurons, but it faces challenges in precision and stability due to cross talk and environmental perturbations. Here, we propose and demonstrate a self-calibration scheme with dual-wavelength synchronization to monitor and calibrate the synaptic weights without interrupting the computation tasks. We design and fabricate an integrated 4 × 4 microring synapse and deploy our self-calibration scheme to validate its effectiveness. The precision and robustness are evaluated in the experiments with favorable performance, achieving 2-bit precision improvement and excellent robustness to environmental temperature fluctuations(the weights can be corrected within 1 s after temperature changes 0.5°C). Moreover, we demonstrate matrix inversion tasks based on Newton iterations beyond 7-bit precision using this microring synapse. Our scheme provides an accurate and real-time weight calibration independently parallel from computations and opens up new perspectives for precision boost solutions to large-scale analog optical computing.展开更多
As an indispensable part to compensate for the signal crosstalk in fiber communication systems,conventional digital multi-input multi-output(MIMO)signal processor is facing the challenges of high com-putational comple...As an indispensable part to compensate for the signal crosstalk in fiber communication systems,conventional digital multi-input multi-output(MIMO)signal processor is facing the challenges of high com-putational complexity,high power consumption and relatively low processing speed.The optical MIMOenables the best use of light and has been proposed to remedy this limitation.However,the currently existing optical MIMO methods are all restricted to the spatial di-mension,while the temporal dimension is neglected.Here,an on-chip spatial-temporal descrambler with four channels were devised and its MIMO functions were experimentally verified simultaneously in both spatial and temporal dimensions.The spatial crosstalk of single-channel descrambler and four-channel descrambler is respectively less than-21 dB and-18 dB,and the time delay is simultaneously com-pensated successfully.Moreover,a more universal model extended to mode-dependent loss and gain(MDL)compensation was further de-veloped,which is capable of being cascaded for the real optical trans-mission system.The first attempt at photonic spatial-temporal de-scrambler enriched the varieties of optical MIMO,and the proposed scheme provided a new opportunity for all-optical MIMO signal pro-cessing.展开更多
基金Supported by Teaching Content and Curriculum System Reform Project of Guizhou Province in 2022(GZJG20220776)Natural Science Research Project of Guizhou Provincial Department of Education(Qianjiaoji[2022]No.067)+1 种基金Research Center for Revolutionary Spirit and Cultural Resources of the Communist Party of China,Zunyi Normal University,Key Research Base of Humanities and Social Sciences,Ministry of Education(22KRIZYPY12)Teaching Content and Curriculum System Reform and Cultivation Project of Zunyi Normal University in 2022(JGPY2022001).
文摘Based on output-oriented education,the OBE(Outcome-Based Education)concept integrates local red culture into the ideological and political course of environmental disciplines,and is an important part of training applied talents of environmental disciplines in the new era.This educational model makes an innovation on the traditional educational and teaching concepts and centers on students.This paper analyzes the value of integrating local red culture into the ideological and political course under the OBE concept,and puts forward an effective implementation path.
基金supported by the National Natural Science Foundation of China (U21A20511)the Innovation Project of Optics Valley Laboratory (OVL2021BG001).
文摘With the advancement of deep learning and neural networks,the computational demands for applications in wearable devices have grown exponentially.However,wearable devices also have strict requirements for long battery life,low power consumption,and compact size.In this work,we propose a scalable optoelectronic computing system based on an integrated optical convolution acceleration core.This system enables high-precision computation at the speed of light,achieving 7-bit accuracy while maintaining extremely low power consumption.It also demonstrates peak throughput of 3.2 TOPS(tera operations per second)in parallel processing.We have successfully demonstrated image convolution and the typical application of an interactive first-person perspective gesture recognition application based on depth information.The system achieves a comparable recognition accuracy to traditional electronic computation in all blind tests.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFB2806502)the National Natural Science Foundation of China(Grant No.62425504)the Knowledge Innovation Program of Wuhan—Basic Research(Grant No.2023010201010049)。
文摘Optical neural networks have emerged as feasible alternatives to their electronic counterparts,offering significant benefits such as low power consumption,low latency,and high parallelism.However,the realization of ultra-compact nonlinear deep neural networks and multi-thread processing remain crucial challenges for optical computing.We present a monolithically integrated all-optical nonlinear diffractive deep neural network(AON-D^(2) NN)chip for the first time.The all-optical nonlinear activation function is implemented using germanium microstructures,which provide low loss and are compatible with the standard silicon photonics fabrication process.Assisted by the germanium activation function,the classification accuracy is improved by 9.1%for four-classification tasks.In addition,the chip's reconfigurability enables multi-task learning in situ via an innovative cross-training algorithm,yielding two task-specific inference results with accuracies of 95%and 96%,respectively.Furthermore,leveraging the wavelength-dependent response of the chip,the multi-thread nonlinear optical neural network is implemented for the first time,capable of handling two different tasks in parallel.The proposed AON-D^(2)NN contains three hidden layers with a footprint of only 0.73 mm^(2).It can achieve ultra-low latency(172 ps),paving the path for realizing high-performance optical neural networks.
基金National Key Research and Development Program of China(2023YFB2806502)National Natural Science Foundation of China(62075075,62275088,U21A20511)Innovation Project of Optics Valley Laboratory(OVL2021BG001)。
文摘Optical computing has shown immense application prospects in the post-Moore era.However,as a crucial component of logic computing,the digital multiplier can only be realized on a small scale in optics,restrained by the limited functionalities and inevitable loss of optical nonlinearity.In this paper,we propose a time-space multiplexed architecture to realize large-scale photonic-electronic digital multiplication.
基金National Natural Science Foundation of China(U21A20511)Innovation Project of Optics Valley Laboratory (OVL2021BG001)。
文摘The increasing demand for diverse portable high-precision spectral analysis applications has driven the rapid development of spectrometer miniaturization. However, the resolutions of existing miniaturized spectrometers mostly remain at the nanometer level, posing a challenge for further enhancement towards achieving picometerlevel precision. Here, we propose an integrated reconstructive spectrometer that utilizes Mach–Zehnder interferometers and a tunable diffraction network. Through random tuning in the time domain and disordered diffraction in the space domain, the random speckle patterns closely related to wavelength information are obtained to construct the transmission matrix. Experimentally, we achieve a high resolution of 100 pm and precisely reconstruct multiple narrowband and broadband spectra. Moreover, the proposed spectrometer features a simple structure, strong portability, and fast sampling speed, which has great potential in the practical application of high-precision portable spectral analysis.
基金supported in part by the National Key Research and Development Program of China(Grant No.2022YFB2804203)the National Natural Science Foundation of China(Grant Nos.62075075,62275088)the Knowledge Innovation Program of Wuhan-Basic Research(Grant No.2023010201010049).
文摘Despite more than 40 years of development,it remains difficult for optical logic computing to support more than four operands because the high parallelism of light has not been fully exploited in current methods that are restrained by inefficient optical nonlinearity and redundant input modulation.In this paper,we propose a large-scale optical programmable logic array(PLA)based on parallel spectrum modulation.By fully exploiting the wavelength resource,an eight-input PLA is experimentally demonstrated with 256 wavelength channels.And it is extended to nine-input PLA through the combination of wavelength’s and spatial dimensions.Based on PLA,many advanced logic functions like 8-256 decoder,4-bit comparator,adder and multiplier,and state machines are first realized in optics.We implement the two-dimensional optical cellular automaton(CA)for what we believe is the first time and run Conway’s Game of Life to simulate the complex evolutionary processes(pulsar explosion,glider gun,and breeder).Other CA models,such as the replicator-like evolution and the nonisotropic evolution to generate the Sierpinski triangle are also demonstrated.Our work significantly alleviates the challenge of scalability in optical logic devices and provides a universal optical computing platform for two-dimensional CA.
基金Chaoran Huang would like to thank Alexander Tait,Bhavin Shastri and Paul Prucnal for the fruitful discussions.J.J.D.acknowledges the support of the National Key Research and Development Project of China(2018YFB2201901)the National Natural Science Foundation of China(61805090,62075075).
文摘Matrix computation,as a fundamental building block of information processing in science and technology,contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.Photonic accelerators are designed to accelerate specific categories of computing in the optical domain,especially matrix multiplication,to address the growing demand for computing resources and capacity.Photonic matrix multiplication has much potential to expand the domain of telecommunication,and artificial intelligence benefiting from its superior performance.Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors.In this review,we first introduce the methods of photonic matrix multiplication,mainly including the plane light conversion method,Mach–Zehnder interferometer method and wavelength division multiplexing method.We also summarize the developmental milestones of photonic matrix multiplication and the related applications.Then,we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years.Finally,we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.
基金This work was partially supported by the National Key Research and Development Project of China(No.2018YFB2201901)the National Natural Science Foundation of China(Grant Nos.61805090 and 62075075)+1 种基金Shenzhen Science and Technology Innovation Commission(No.SGDX2019081623060558)Research Grants Council of Hong Kong SAR(No.PolyU152241/18E).
文摘As an important computing operation,photonic matrix-vector multiplication is widely used in photonic neutral networks and signal processing.However,conventional incoherent matrix-vector multiplication focuses on real-valued operations,which cannot work well in complex-valued neural networks and discrete Fourier transform.In this paper,we propose a systematic solution to extend the matrix computation of microring arrays from the real-valued field to the complex-valued field,and from small-scale(i.e.,4×4)to large-scale matrix computation(i.e.,16×16).Combining matrix decomposition and matrix partition,our photonic complex matrix-vector multiplier chip can support arbitrary large-scale and complex-valued matrix computation.We further demonstrate Walsh-Hardmard transform,discrete cosine transform,discrete Fourier transform,and image convolutional processing.Our scheme provides a path towards breaking the limits of complex-valued computing accelerator in conventional incoherent optical architecture.More importantly,our results reveal that an integrated photonic platform is of huge potential for large-scale,complex-valued,artificial intelligence computing and signal processing.
基金National Key Research and Development Program of China(2021YFB2801900,2021YFB2801903)National Natural Science Foundation of China(62075075,62275088,U21A20511)Innovation Project of Optics Valley Laboratory(OVL2021BG001)
文摘As a resonator-based optical hardware in analog optical computing, a microring synapse can be straightforwardly configured to simulate the connection weights between neurons, but it faces challenges in precision and stability due to cross talk and environmental perturbations. Here, we propose and demonstrate a self-calibration scheme with dual-wavelength synchronization to monitor and calibrate the synaptic weights without interrupting the computation tasks. We design and fabricate an integrated 4 × 4 microring synapse and deploy our self-calibration scheme to validate its effectiveness. The precision and robustness are evaluated in the experiments with favorable performance, achieving 2-bit precision improvement and excellent robustness to environmental temperature fluctuations(the weights can be corrected within 1 s after temperature changes 0.5°C). Moreover, we demonstrate matrix inversion tasks based on Newton iterations beyond 7-bit precision using this microring synapse. Our scheme provides an accurate and real-time weight calibration independently parallel from computations and opens up new perspectives for precision boost solutions to large-scale analog optical computing.
基金National Key Research and Development Program of China(2021YFB2801903,2021YFB2801900)National Natural Science Foundation of China(62075075,U21A20511,62275088)Innovation Project of Optics Valley Laboratory(Grant No.OVL2021BG001).
文摘As an indispensable part to compensate for the signal crosstalk in fiber communication systems,conventional digital multi-input multi-output(MIMO)signal processor is facing the challenges of high com-putational complexity,high power consumption and relatively low processing speed.The optical MIMOenables the best use of light and has been proposed to remedy this limitation.However,the currently existing optical MIMO methods are all restricted to the spatial di-mension,while the temporal dimension is neglected.Here,an on-chip spatial-temporal descrambler with four channels were devised and its MIMO functions were experimentally verified simultaneously in both spatial and temporal dimensions.The spatial crosstalk of single-channel descrambler and four-channel descrambler is respectively less than-21 dB and-18 dB,and the time delay is simultaneously com-pensated successfully.Moreover,a more universal model extended to mode-dependent loss and gain(MDL)compensation was further de-veloped,which is capable of being cascaded for the real optical trans-mission system.The first attempt at photonic spatial-temporal de-scrambler enriched the varieties of optical MIMO,and the proposed scheme provided a new opportunity for all-optical MIMO signal pro-cessing.
