Machine learning approach for computing optical properties of a photonic crystal fiber

Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers. In this paper, machine learning techniques are used to compute various optical properties including effective index, effective mode area, dispersion and confinement loss for a solid-core PCF. These machine learning algorithms based on artificial neural networks are able to make accurate predictions of above-mentioned optical properties for usual parameter space of wavelength ranging from 0.5-1.8 µm, pitch from 0.8-2.0 µm, diameter by pitch from 0.6-0.9 and number of rings as 4 or 5 in a silica solid-core PCF. We demonstrate the use of simple and fast-training feed-forward artificial neural networks that predicts the output for unknown device parameters faster than conventional numerical simulation techniques. Computation runtimes required with neural networks (for training and testing) and Lumerical MODE solutions are also compared

Deeply-trapped molecules in self-nanostructured gas-phase material

Since the advent of atom laser-cooling, trapping or cooling natural molecules has been a long standing and challenging goal. Here, we demonstrate a method for laser-trapping molecules that is radically novel in its configuration, in its underlined physical dynamics and in its outcomes. It is based on self-optically spatially-nanostructured high pressure molecular hydrogen confined in hollow-core photonic-crystal-fibre. An accelerating molecular-lattice is formed by a periodic potential associated with Raman saturation except for a 1-dimentional array of nanometer wide and strongly-localizing sections. In these sections, molecules with a speed of as large as 1800 m/s are trapped, and stimulated Raman scattering in the Lamb-Dicke regime occurs to generate high power forward and backward-Stokes continuous-wave laser with sideband-resolved sub-Doppler emission spectrum. The spectrum exhibits a central line with a sub-recoil linewidth of as low as 14 kHz, more than 5 orders-of-magnitude narrower than in conventional Raman scattering, and sidebands comprising Mollow triplet, molecular motional-sidebands and four-wave-mixing.Comment: 28 pages 1-12 for main manuscript 13-28 for Methodes and appendices 4 figures for Main manuscript 12 figures for the Methods par

P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic Segmentation

Recently, Transformer-based models have achieved promising results in various vision tasks, due to their ability to model long-range dependencies. However, transformers are computationally expensive, which limits their applications in real-time tasks such as autonomous driving. In addition, an efficient local and global feature selection and fusion are vital for accurate dense prediction, especially driving scene understanding tasks. In this paper, we propose a real-time semantic segmentation architecture named Pyramid Pooling Axial Transformer (P2AT). The proposed P2AT takes a coarse feature from the CNN encoder to produce scale-aware contextual features, which are then combined with the multi-level feature aggregation scheme to produce enhanced contextual features. Specifically, we introduce a pyramid pooling axial transformer to capture intricate spatial and channel dependencies, leading to improved performance on semantic segmentation. Then, we design a Bidirectional Fusion module (BiF) to combine semantic information at different levels. Meanwhile, a Global Context Enhancer is introduced to compensate for the inadequacy of concatenating different semantic levels. Finally, a decoder block is proposed to help maintain a larger receptive field. We evaluate P2AT variants on three challenging scene-understanding datasets. In particular, our P2AT variants achieve state-of-art results on the Camvid dataset 80.5%, 81.0%, 81.1% for P2AT-S, P2ATM, and P2AT-L, respectively. Furthermore, our experiment on Cityscapes and Pascal VOC 2012 have demonstrated the efficiency of the proposed architecture, with results showing that P2AT-M, achieves 78.7% on Cityscapes. The source code will be available a

Raman gas self-organizing into deep nano-trap lattice

Trapping or cooling molecules has rallied a long-standing effort for its impact in exploring new frontiers in physics and in finding new phase of matter for quantum technologies. Here we demonstrate a system for light-trapping molecules and stimulated Raman scattering based on optically self-nanostructured molecular hydrogen in hollow-core photonic crystal fibre. A lattice is formed by a periodic and ultra-deep potential caused by a spatially modulated Raman saturation, where Raman-active molecules are strongly localized in a one-dimensional array of nanometre-wide sections. Only these trapped molecules participate in stimulated Raman scattering, generating high-power forward and backward Stokes continuous-wave laser radiation in the Lamb-Dicke regime with sub-Doppler emission spectrum. The spectrum exhibits a central line with a sub-recoil linewidth as low as ∼14 kHz, more than five orders of magnitude narrower than conventional-Raman pressure-broadened linewidth, and sidebands comprising Mollow triplet, motional sidebands and four-wave mixing

Hypocycloid-shaped hollow-core photonic crystal fiber Part II: Cladding effect on confinement and bend loss

We report on numerical and experimental studies on the influence of cladding ring-number on the confinement and bend loss in hypocycloid-shaped Kagome hollow core photonic crystal fiber. The results show that beyond the second ring, the ring number has a minor effect on confinement loss whereas the bend loss is strongly reduced with the ringnumber increase. Finally, the results show that the increase in the cladding ring-number improves the modal content of the fiber

Hypocycloid-shaped hollow-core photonic crystal fiber Part I: Arc curvature effect on confinement loss

We report on numerical and experimental studies showing the influence of arc curvature on the confinement loss in hypocycloid-core Kagome hollow-core photonic crystal fiber. The results prove that with such a design the optical performances are strongly driven by the contour negative curvature of the core-cladding interface. They show that the increase in arc curvature results in a strong decrease in both the confinement loss and the optical power overlap between the core mode and the silica core-surround, including a modal content approaching true single-mode guidance. Fibers with enhanced negative curvature were then fabricated with a record loss-level of 17 dB/km at 1064 nm

Hollow-core fiber-based speckle displacement sensor

The research enterprise towards achieving high-performance hollow-core photonic crystal fibers has led to impressive advancements in the latest years. Indeed, using this family of fibers becomes nowadays an overarching strategy for building a multitude of optical systems ranging from beam delivery devices to optical sources and sensors. In most applications, an effective single-mode operation is desired and, as such, the fiber microstructure or the light launching setups are typically designed for achieving such a behavior. Alternatively, one can identify the use of large-core multimode hollow-core fibers as a promising avenue for the development of new photonic devices. Thus, in this manuscript, we propose and demonstrate the utilization of a large-core tubular-lattice fiber for accomplishing a speckle-based displacement sensor, which has been built up by inserting and suitably dislocating a single-mode fiber inside the void core of the hollow fiber. The work reported herein encompasses both simulation and experimental studies on the evolution of the multimode intensity distributions within the device as well as the demonstration of a displacement sensor with an estimated resolution of 0.7 {\mu}m. We understand that this investigation identifies a new opportunity for the employment of large-core hollow fibers within the sensing framework hence widening the gamut of applications of this family of fibers

Ultralow transmission loss in inhibited-coupling guiding hollow fibers

Attenuation in photonic bandgap guiding hollow-core photonic crystal fiber (HC-PCF) has not beaten the fundamental silica Rayleigh scattering limit (SRSL) of conventional step-index fibers due to strong core-cladding optical overlap, surface roughness at the silica cladding struts, and the presence of interface modes. Hope has been revived recently by the introduction of hypocycloid core contour (i.e., negative curvature) in inhibited-coupling guiding HCPCF. We report on several fibers with a hypocycloid core contour and a cladding structure made of a single ring from a tubular amorphous lattice, including one with a record transmission loss of 7.7 dB/km at ~750 nm (only a factor ~2 above the SRSL) and a second with an ultrabroad fundamental band with loss in the range of 10-20 dB/km, spanning from 600 to 1200 nm. The reduction in confinement loss makes these fibers serious contenders for light transmission below the SRSL in the UV-VIS-NIR spectral range and could find application in high-energy pulse laser beam delivery or gas-based coherent and nonlinear optics

High-efficiency cold-atom transport into a waveguide trap

We develop and characterize an atom-guiding technique that loads 3×10⁶ cold rubidium atoms into a hollow-core optical fiber, an order-of-magnitude greater than previously reported results. This result is possible because it is guided by a physically realistic simulation that can provide the specifications for a loading efficiency of 3.0% and a peak optical depth of 600. The simulation further shows that the loading efficiency is limited solely by the geometric overlap of the atom cloud and the optical guide beam, and is thus open to further improvement with experimental modification. The experimental arrangement allows observation of the real-time effects of light-assisted cold-atom collisions and background-gas collisions by tracking the dynamics of the cold-atom cloud as it falls into the fiber. The combination of these observations, and physical understanding from the simulation, allows estimation of the limits to loading cold atoms into hollow-core fibers.A.P. Hilton, C. Perrella, F. Benabid, B.M. Sparkes, A.N. Luiten and P.S. Ligh