Scaling optical computing in synthetic frequency dimension using integrated cavity acousto-optics

Optical computing with integrated photonics brings a pivotal paradigm shift to data-intensive computing technologies. However, the scaling of on-chip photonic architectures using spatially distributed schemes faces the challenge imposed by the fundamental limit of integration density. Synthetic dimensions of light offer the opportunity to extend the length of operand vectors within a single photonic component. Here, we show that large-scale, complex-valued matrix-vector multiplications on synthetic frequency lattices can be performed using an ultra-efficient, silicon-based nanophotonic cavity acousto-optic modulator. By harnessing the resonantly enhanced strong electro-optomechanical coupling, we achieve, in a single such modulator, the full-range phase-coherent frequency conversions across the entire synthetic lattice, which constitute a fully connected linear computing layer. Our demonstrations open up the route towards the experimental realizations of frequency-domain integrated optical computing systems simultaneously featuring very large-scale data processing and small device footprints.Comment: 4 figures, 14 pages for main text, 14 pages of supplementary material

Silicon-lattice-matched boron-doped gallium phosphide: A scalable acousto-optic platform

The compact size, scalability, and strongly confined fields in integrated photonic devices enable new functionalities in photonic networking and information processing, both classical and quantum. Gallium phosphide (GaP) is a promising material for active integrated photonics due to its high refractive index, wide band gap, strong nonlinear properties, and large acousto-optic figure of merit. In this work we demonstrate that silicon-lattice-matched boron-doped GaP (BGaP), grown at the 12-inch wafer scale, provides similar functionalities as GaP. BGaP optical resonators exhibit intrinsic quality factors exceeding 25,000 and 200,000 at visible and telecom wavelengths respectively. We further demonstrate the electromechanical generation of low-loss acoustic waves and an integrated acousto-optic (AO) modulator. High-resolution spatial and compositional mapping, combined with ab initio calculations indicate two candidates for the excess optical loss in the visible band: the silicon-GaP interface and boron dimers. These results demonstrate the promise of the BGaP material platform for the development of scalable AO technologies at telecom and provide potential pathways toward higher performance at shorter wavelengths

Integrated Acousto-optics: Steering light with sound waves on a chip

Thesis (Ph.D.)--University of Washington, 2022When an acoustic wave propagate inside an optical transparent material, it periodicallymodulates the permittivity medium due to the elasto-optical effect. This can generate a moving phase grating that can diffract the incident light into one or more orders. Such phenomenon is known as acouto-optic (AO) diffraction which leads to a various of applications such as temporal modulators, spatial modulators, spectral modulators and more. Historically, the AO diffraction (so called, Brillouin scattering (BS)) was first predicted by Brillouin in 1922 [1]. Ten years later, the phenomenon was experimentally observed by Debye and Sears [2], and Lucas and Biquard [3] successively. Other than than Brillouin’s predictions, instead of only one order of diffracted beam, there are many more orders observed. which was later theoretical analyzed by Raman and Nath [4]. Therefore, in terms of the Brillouin scattering, there are two diffraction regimes, the Raman-Nath regime, characterized by the multiple of diffraction orders, and the Bragg regime, characterized by a single diffraction order [5, 6]. The exploitation of acouto-optics has led to demonstrations of a variety of applications and novel physical phenomena in a lot of optical systems and devices [1,6–12]. The elastic wave can be spontaneously produced by thermal agitation of the environment (i.e., spontaneous Brillouin scattering), or stimulated (narrowly defined to be optically excited) by a stronglight source (i.e., stimulated Brillouin scattering (SBS)). The elastic wave can also be excited by external stimuli, such as optical pulses, thermal shocks, and electrical and magnetic fields. The acoustic wave involved in the acousto-optical scattering process can be launched in different ways. For example, the elastic wave can be spontaneously produced by thermal agitation of the environment (i.e., spontaneous Brillouin scattering), or thermal excitation and the optomechanical stimulation by radiation pressure and electrostriction. While the former method is the original Brillouin’s description, the later one is more explored by recent researchers, especially for the stimulated Brillouin scattering (SBS), [13–15] [15–21] as well as in cavity optomechanical systems [22–25], which feature many intriguing photon-phonon interactions [26]. Meanwhile, the acoustic waves can be also electromechanically excited by the interdigital transducers (IDT) on the piezoelectric material. The IDTs convert radio frequency (RF) and microwave (MW) electromagnetic waves to propagating elastic waves, or in some cases, localized mechanical modes. The advanced electromechanical transducer can achieve near-unity transfer efficiency with compact footprint [27–29]. Such strong acoustic waves have the high scattering efficiency [30], which is essential for the practical applications, especially for the nowadays quantum transduction [31]. The high transfer efficiency from RF power to acoustic power, generated from the electromechanical excitation, leading to a high acoustic wave intensity, is unparalleled with other methods forementioned. In the contrast, in the SBS process, each pump photo can generate at most one phonon. Due to the large frequency difference, (in more than 3 orders), the excitation efficiency is no larger than 10-3. Recently, there are several works using gigahertz electromechanically generated acoustic wave to modulate the guide optical waves inside the waveguides and the cavities [32–38]. Novel physical phenomena has been explored in these works, such as induced transparency [35] and nonreciprocal mode conversion [36], and other advanced optical functionalities [30, 32–35, 37, 38]. Thanks to the development of nanofabrication technology, the state-of-art integrated guided wave acousto-optical device succeedthe conventional acousto-optical devices with significant advances in terms of the power consumption and physical footprint [10, 39–42]. The frequency of the nowadays device can also exceed 10 GHz easily, compared to the previous acousto-optic devices. More interestingly, the newly emerging integrated phononic circuit is anticipated to complement the functionalities of the photonic and electronic circuits, leading to integrated nano-opto-electro-mechanical systems (NOEMS). Such exciting prospect of integration of the three ”x-ons” (photons, phonons and electrons), that implement sophisticated sensing and information processing functionalities through Brillouin scattering in the classical and quantum regimes is attracting increasing research efforts. In this dissertation, a brief overview of BS processes is introduced first in Chapter 1, including the electromechanical excitation of acoustic waves based on piezoelectric IDTs, configurations of such devices, and some prospective applications of the BS devices in reviewed. What follows the introduction and the theory review is the revised compilation of the author’s selected research work, including the acousto-optic beamsteering (AOBS) and the scaling integrated photonic computing in the synthetic frequency dimension. AOBS device has been successfully simulated and fabricated for the first time in 2021. When light interacts with guided acoustic wave inside the acousto-optic waveguide, the scattered beam can be deflected into the designated directions by controlling the acoustic wave frequency. The introduced frequency upshift of the deflected light beam obeys the BS process, mapping the deflection angle to the controlled acoustic wave frequency. Since the angular position of the object is “labeled” by the frequency of the reflected light, the receiver can determine the object’s position without a priori knowledge of the outgoing beam angle. Based on this property, a prototype frequency angular resolving (FAR) light-detection-andranging (LiDAR) system based on chip-scale AOBS devices has been demonstrated. This work is presented in Chapter 2.The scaling integrated photonic computing in the synthetic frequency dimension has been successfully demonstrated in 2020. [43] The optomechanical coupling is improved by one order in our heterogeneous AlN-on-SOI platform. With such a strong AO modulation, the large scale vector multiplier in frequency domain is achieved. This work is presented in Chapter 3

Optimized Ship-Radiated Noise Feature Extraction Approaches Based on CEEMDAN and Slope Entropy

Slope entropy (Slopen) has been demonstrated to be an excellent approach to extracting ship-radiated noise signals (S-NSs) features by analyzing the complexity of the signals; however, its recognition ability is limited because it extracts the features of undecomposed S-NSs. To solve this problem, in this study, we combined complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to explore the differences of Slopen between the intrinsic mode components (IMFs) of the S-NSs and proposed a single-IMF optimized feature extraction approach. Aiming to further enhance its performance, the optimized combination of dual-IMFs was selected, and a dual-IMF optimized feature extraction approach was also proposed. We conducted three experiments to demonstrate the effectiveness of CEEMDAN, Slopen, and the proposed approaches. The experimental and comparative results revealed both of the proposed single- and dual-IMF optimized feature extraction approaches based on Slopen and CEEMDAN to be more effective than the original ship signal-based and IMF-based feature extraction approaches

A nanofabricated optoelectronic probe for manipulating and recording neural dynamics

OBJECTIVE:The convergence of optogenetic and large-scale neural recording technologies opens enormous opportunities for studying brain function. However, compared to the widespread use of optogenetics or recordings as standalone methods, the joint use of these techniques in behaving animals is much less well developed. A simple but poorly scalable solution has been to implant conventional optical fibers together with extracellular microelectrodes. A more promising approach has been to combine microfabricated light emission sources with multielectrode arrays. However, a challenge remains in how to compactly and scalably integrate optical output and electronic readout structures on the same device. Here we took a step toward addressing this issue by using nanofabrication techniques to develop a novel implantable optoelectronic probe. APPROACH:This device contains multiple photonic grating couplers connected with waveguides for out-of-plane light emission, monolithically integrated with a microlectrode array on the same silicon substrate. To demonstrate the device's operation in vivo, we record cortical activity from awake head-restrained mice. MAIN RESULTS:We first characterize photo-stimulation effects on electrophysiological signals. We then assess the probe's ability to both optogenetically stimulate and electrically record neural firing. SIGNIFICANCE:This device relies on nanofabrication techniques to integrate optical stimulation and electrical readout functions on the same structure. Due to the device miniaturization capabilities inherent to nanofabrication, this optoelectronic probe technology can be further scaled to increase the throughput of manipulating and recording neural dynamics

Fractional Order Fuzzy Dispersion Entropy and Its Application in Bearing Fault Diagnosis

Fuzzy dispersion entropy (FuzzDE) is a very recently proposed non-linear dynamical indicator, which combines the advantages of both dispersion entropy (DE) and fuzzy entropy (FuzzEn) to detect dynamic changes in a time series. However, FuzzDE only reflects the information of the original signal and is not very sensitive to dynamic changes. To address these drawbacks, we introduce fractional order calculation on the basis of FuzzDE, propose FuzzDEα, and use it as a feature for the signal analysis and fault diagnosis of bearings. In addition, we also introduce other fractional order entropies, including fractional order DE (DEα), fractional order permutation entropy (PEα) and fractional order fluctuation-based DE (FDEα), and propose a mixed features extraction diagnosis method. Both simulated as well as real-world experimental results demonstrate that the FuzzDEα at different fractional orders is more sensitive to changes in the dynamics of the time series, and the proposed mixed features bearing fault diagnosis method achieves 100% recognition rate at just triple features, among which, the mixed feature combinations with the highest recognition rates all have FuzzDEα, and FuzzDEα also appears most frequently

Fractional Order Fuzzy Dispersion Entropy and Its Application in Bearing Fault Diagnosis

Fuzzy dispersion entropy (FuzzDE) is a very recently proposed non-linear dynamical indicator, which combines the advantages of both dispersion entropy (DE) and fuzzy entropy (FuzzEn) to detect dynamic changes in a time series. However, FuzzDE only reflects the information of the original signal and is not very sensitive to dynamic changes. To address these drawbacks, we introduce fractional order calculation on the basis of FuzzDE, propose FuzzDEα, and use it as a feature for the signal analysis and fault diagnosis of bearings. In addition, we also introduce other fractional order entropies, including fractional order DE (DEα), fractional order permutation entropy (PEα) and fractional order fluctuation-based DE (FDEα), and propose a mixed features extraction diagnosis method. Both simulated as well as real-world experimental results demonstrate that the FuzzDEα at different fractional orders is more sensitive to changes in the dynamics of the time series, and the proposed mixed features bearing fault diagnosis method achieves 100% recognition rate at just triple features, among which, the mixed feature combinations with the highest recognition rates all have FuzzDEα, and FuzzDEα also appears most frequently

A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

Slope entropy (SlopEn) has been widely applied in fault diagnosis and has exhibited excellent performance, while SlopEn suffers from the problem of threshold selection. Aiming to further enhance the identifying capability of SlopEn in fault diagnosis, on the basis of SlopEn, the concept of hierarchy is introduced, and a new complexity feature, namely hierarchical slope entropy (HSlopEn), is proposed. Meanwhile, to address the problems of the threshold selection of HSlopEn and a support vector machine (SVM), the white shark optimizer (WSO) is applied to optimize both HSlopEn and an SVM, and WSO-HSlopEn and WSO-SVM are proposed, respectively. Then, a dual-optimization fault diagnosis method for rolling bearings based on WSO-HSlopEn and WSO-SVM is put forward. We conducted measured experiments on single- and multi-feature scenarios, and the experimental results demonstrated that whether single-feature or multi-feature, the WSO-HSlopEn and WSO-SVM fault diagnosis method has the highest recognition rate compared to other hierarchical entropies; moreover, under multi-features, the recognition rates are all higher than 97.5%, and the more features we select, the better the recognition effect. When five nodes are selected, the highest recognition rate reaches 100%