分类: 光学 >> 量子光学 提交时间: 2023-02-19
摘要: We propose efficient modelling of optical fiber channel via NLSE-constrained physics-informed neural operator without reference solutions. This method can be easily scalable for distance, sequence length, launch power, and signal formats, and is implemented for ultra-fast simulations of 16-QAM signal transmission with ASE noise.
分类: 光学 >> 量子光学 提交时间: 2023-02-19
摘要: Harnessing structured light is fascinating for its multi-disciplinary applications, e.g., in remote driving microrobots, sensing, communications, and ultrahigh resolution imaging. Here we experimentally demonstrated the generation of a vortex N2+ lasing pumped by a wavefront structured near-infrared femtosecond pulse with an orbital angular momentum. The topological charge of the new-born N2+ lasing is measured to be twofold that of the pump beam. As compared to the case with pump beam of plane wavefront, the N2+ lasing generation efficiency is much higher for the vortex pump beam at high pumping energy which has a higher clamping intensity by reducing the on-axis plasma density. Our results herald a stirring marching into the territory of remote structured N2+ lasing.
分类: 光学 >> 量子光学 提交时间: 2023-02-19
摘要: A physics-informed neural network (PINN) that combines deep learning with physics is studied to solve the nonlinear Schr\"odinger equation for learning nonlinear dynamics in fiber optics. We carry out a systematic investigation and comprehensive verification on PINN for multiple physical effects in optical fibers, including dispersion, self-phase modulation, and higher-order nonlinear effects. Moreover, both special case (soliton propagation) and general case (multi-pulse propagation) are investigated and realized with PINN. In the previous studies, the PINN was mainly effective for single scenario. To overcome this problem, the physical parameters (pulse peak power and amplitudes of sub-pulses) are hereby embedded as additional input parameter controllers, which allow PINN to learn the physical constraints of different scenarios and perform good generalizability. Furthermore, PINN exhibits better performance than the data-driven neural network using much less data, and its computational complexity (in terms of number of multiplications) is much lower than that of the split-step Fourier method. The results report here show that the PINN is not only an effective partial differential equation solver, but also a prospective technique to advance the scientific computing and automatic modeling in fiber optics.
分类: 光学 >> 量子光学 提交时间: 2023-02-19
摘要: Single-beam super-resolution microscopy, also known as superlinear microscopy, exploits the nonlinear response of fluorescent probes in confocal microscopy. The technique requires no complex purpose-built system, light field modulation, or beam shaping. Here, we present a strategy to enhance spatial resolution of superlinear microscopy by modulating excitation intensity during image acquisition. This modulation induces dynamic optical nonlinearity in upconversion nanoparticles (UCNPs), resulting in variations of higher spatial-frequency information in the obtained images. The high-order information can be extracted with a proposed weighted finite difference imaging algorithm from raw fluorescence images, to generate an image with a higher resolution than superlinear microscopy images. We apply this approach to resolve two adjacent nanoparticles within a diffraction-limited area, improving the resolution to 130 nm. This work suggests a new scope for developing dynamic nonlinear fluorescent probes in super-resolution nanoscopy.
分类: 生物学 >> 植物学 >> 植物生物化学、植物生物物理学 提交时间: 2016-05-04
摘要: The importance of the nitrate (NO3−) transporter for yield and nitrogen-use efficiency (NUE) in rice was previously demonstrated using map-based cloning. In this study, we enhanced the expression of the OsNRT2.1 gene, which encodes a high-affinity NO3− transporter, using a ubiquitin (Ubi) promoter and the NO3−-inducible promoter of the OsNAR2.1 gene to drive OsNRT2.1 expression in transgenic rice plants. Transgenic lines expressing pUbi:OsNRT2.1 or pOsNAR2.1:OsNRT2.1 constructs exhibited the increased total biomass including yields of approximately 21% and 38% compared with wild-type (WT) plants. The agricultural NUE (ANUE) of the pUbi:OsNRT2.1 lines decreased to 83% of that of the WT plants, while the ANUE of the pOsNAR2.1:OsNRT2.1 lines increased to 128% of that of the WT plants. The dry matter transfer into grain decreased by 68% in the pUbi:OsNRT2.1 lines and increased by 46% in the pOsNAR2.1:OsNRT2.1 lines relative to the WT. The expression of OsNRT2.1 in shoot and grain showed that Ubi enhanced OsNRT2.1 expression by 7.5-fold averagely and OsNAR2.1 promoters increased by about 80% higher than the WT. Interestingly, we found that the OsNAR2.1 was expressed higher in all the organs of pUbi:OsNRT2.1 lines; however, for pOsNAR2.1:OsNRT2.1 lines, OsNAR2.1 expression was only increased in root, leaf sheaths and internodes. We show that increased expression of OsNRT2.1, especially driven by OsNAR2.1 promoter, can improve the yield and NUE in rice.