Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks

Spiking neural networks (SNNs) have tremendous potential for energy-efficient neuromorphic chips due to their binary and event-driven architecture. SNNs have been primarily used in classification tasks, but limited exploration on image generation tasks. To fill the gap, we propose a Spiking-Diffusion model, which is based on the vector quantized discrete diffusion model. First, we develop a vector quantized variational autoencoder with SNNs (VQ-SVAE) to learn a discrete latent space for images. With VQ-SVAE, image features are encoded using both the spike firing rate and postsynaptic potential, and an adaptive spike generator is designed to restore embedding features in the form of spike trains. Next, we perform absorbing state diffusion in the discrete latent space and construct a diffusion image decoder with SNNs to denoise the image. Our work is the first to build the diffusion model entirely from SNN layers. Experimental results on MNIST, FMNIST, KMNIST, and Letters demonstrate that Spiking-Diffusion outperforms the existing SNN-based generation model. We achieve FIDs of 37.50, 91.98, 59.23 and 67.41 on the above datasets respectively, with reductions of 58.60\%, 18.75\%, 64.51\%, and 29.75\% in FIDs compared with the state-of-art work.Comment: Under Revie

Asymmetric superradiant scattering and abnormal mode amplification induced by atomic density distortion

The superradiant Rayleigh scattering using a pump laser incident along the short axis of a Bose-Einstein condensate with a density distortion is studied, where the distortion is formed by shocking the condensate utilizing the residual magnetic force after the switching-off of the trapping potential. We find that very small variation of the atomic density distribution would induce remarkable asymmetrically populated scattering modes by the matter-wave superradiance with long time pulse. The optical field in the diluter region of the atomic cloud is more greatly amplified, which is not an ordinary mode amplification with the previous cognition. Our numerical simulations with the density envelop distortion are consistent with the experimental results. This supplies a useful method to reflect the geometric symmetries of the atomic density profile by the superradiance scattering.Comment: 7pages,4 figures, Optical Express 21,(2013)1437

Identifying aerial bomb's aerodynamic drag coefficient curve using optimal dynamic fitting method

Journal of Aircraft356971-975JAIR

Iterative Learning Identification

An iterative learning identification method is proposed for curve identification problems. The basic idea is to convert the curve identification problem into an optimal tracking control problem. The measured trajectories are regarded as the desired trajectories to be optimally tracked and the curve to be identified is taken as a virtual control function. A high-order learning updating law is applied. A convergence condition is obtained in a general problem setting. Two case studies, which are related to the aerodynamic drag coefficient curve extraction from actual flight testing data, are presented to show the practical usefulness of the proposed method. 1 Introduction In many system identification tasks, identification of parameters is actually a special case of nonlinear function or curve identification. On the other hand, curve identification or extraction from system testing data can be easily converted to parameter identification through a parameterization procedure of the curve..

Zircon as a Monitoring Tool for the Magmatic–Hydrothermal Process in the Granitic Bedrock of Shitouping Ion-Adsorption Heavy Rare Earth Element Deposit, South China

The Shitouping pluton in Jiangxi Province, southern China, hosts an ion-adsorption heavy rare earth element (HREE) deposit identified by a recent geological survey. This study reveals the HREE pre-enrichment mechanism during the magmatic–hydrothermal process of granitic bedrock based on the comprehensive study of zircon structure and composition. Zircon from the Shitouping pluton, composed of syenogranite and monzogranite, can be categorized into three types based on structure and compositions. The Type-1 zircons, the predominate type in monzogranite, are early magmatic zircons with prismatic crystals and bright oscillatory zoning in CL images. In contrast, the late magmatic-hydrothermal zircons (Type-2 and Type-3) mainly occur in the syenogranite. The Type-2 zircons occur as dark CL images and euhedral crystals crystallized during the late magmatic stage. The Type-3 zircons with irregular zoning and abundant mineral inclusions in BSE images are possibly formed via intense hydrothermal alteration during the hydrothermal stage. The increase in Y/Ho ratios from Type-1 to Type-3 zircon indicates that the Shitouping syenogranites underwent magmatic to hydrothermal evolution. Compared with Type-1 and Type-2 zircons, Type-3 zircons exhibit the highest concentrations of F and HREEs. The significant increase in HREE concentrations both in zircons and bulk-rock composition of syenogranite can be attributed to the introduction of HREE-rich fluids during magma evolution. Therefore, we propose that the increase in HREE contents in zircon reflect the exsolution of HREE-rich fluids during a late stage in the magma evolution, which is an important factor controlling HREE enrichment in Shitouping syenogranites and furthermore in the generation of ion-adsorption HREE deposits

Modification of Zinc Anodes by <i>In Situ</i> ZnO Coating for High-Performance Aqueous Zinc-Ion Batteries

Aqueous zinc-ion batteries have been regarded as promising candidates for advanced energy storage devices due to their high capacity and safety. However, they usually suffer from dendrite growth and side reactions, which severely destabilize the electrode/electrolyte interface and undermine the electrochemical performance. Herein, we report ZnO nanorod-decorated Zn anodes using a facile in situ hydrothermal method. The reactions and evolution at the anode–electrolyte interface are systematically investigated. Various characterization techniques suggest that ZnO transforms into a Zn-ion conductive Zn4SO4(OH)6·4H2O (ZHS·4H2O) interphase, which enables uniform Zn deposition and suppresses dendrite growth. In addition, this passivated interphase can prevent the electrolyte from direct contact with the Zn anode and inhibit side reactions, effectively improving the coulombic efficiency (CE) and the utilization of anodes. Therefore, the Zn-ZnO anodes in the symmetric cells display a low voltage hysteresis (46 mV) and long-term cycling stability at 5 mA cm–2, a lower Zn deposition barrier, and a high Zn plating/stripping CE of 99.7%. Importantly, the Zn-ZnO//MnO2 full cells show a fairly high specific capacity of 580 mAh g–1 and superior cycling stability with 154% capacity retention after 100 cycles at 50 mA g–1 and 105% capacity retention after 800 cycles at 500 mA g–1