Optical Fiber Research Articles

Rare-earth dopant distribution measurement of optical fibers based on filtered back projection

We present a nondestructive measurement based on filtered back projection (FBP) for the distribution of rare-earth dopant in optical fibers. Based on the approach, a measurement system is established, where the single-mode pumped laser illuminates the fiber under test from the side, generating multi-wavelength fluorescence through photoluminescence (PL). The distribution of rare-earth doped particles is proportional to the distribution of fluorescence intensity. The projection images are collected by the CCD camera at 90° relative to the excitation arm. According to the computed tomography (CT), the rotation of the optical fiber enables the experimental measurements of intensity information extracted from multi-angle projections. The rare-earth dopant distribution of the fiber is reconstructed by the improved filtered back projection algorithm, which improves the quality of the reconstructed result by incorporating total variation (TV) algorithm. To evaluate the proposed approach, rare-earth dopant distribution is compared with results measured by EPMA, exhibiting a correlation coefficient above 0.99, and the relationship between the dopant distribution and the refractive index is analyzed. Measurements on doped particle distributions at various wavelengths are conducted, and the fluorescence spectrum are constructed to further analyze the fluorescence characteristics of rare earth doped fiber. Measurement of RE dopant distribution will be useful for quality evaluation and optimization of partial active optical fibers.

Enhanced highly bismuth‐doped multicomponent phosphate glass fibers for broadband amplifiers

AbstractBismuth (Bi)‐doped glass fibers are being developed into next‐generation broadband amplifiers and tunable lasers. Yet, the well‐developed Bi‐doped fiber devices only realize silica‐based optical fibers prepared by the modified chemical vapor deposition method, which faces challenges such as low doping concentration, high cost, intricate device structure, and high preparation difficulty. Here, a novel highly Bi‐doped multicomponent phosphate glass was developed. The high ion solubility of this phosphate glass facilitates achieving a Bi doping concentration of 8 mol%. The introduction of aluminum nitride (a new reducing agent) can create a local reducing environment, further increasing the concentration of low‐valence near‐infrared (NIR) active Bi ions. Furthermore, the resulting enhanced highly Bi‐doped multicomponent phosphate glass with efficient 900–1600 nm NIR emission can be drawn into corresponding optical fibers by a rod‐in‐tube method. Broadband NIR amplified spontaneous emission with a 3 dB bandwidth of 275 nm was achieved in this new fiber. As far as we know, this is the first successful preparation of Bi‐doped multicomponent phosphate glass fiber. Our results indicate that this fiber will be a powerful alternative to Bi‐doped silica‐based fibers for the preparation of related Bi‐doped fiber devices.

Learnable Dual Attention Fusion Network (LDAFNet) For Borehole DAS Data Reconstruction.

As the demand of important non-renewable oil and gas resources increase, distributed optical fiber acoustic sensing systems have been widely used in the acquisition of vertical seismic profile (VSP) data relying on its various advantages. The complicated underground environment produces many types of noise with strong energy. Meanwhile, the effective information is absorbed by the formation reflection and refraction, resulting in obvious energy loss and aliased frequency characteristics. Satisfactory processing results and quality cannot be achieved through traditional denoising methods. In recent years, rapidly developed deep learning methods with attention mechanism have greatly attracted researchers. Noise reduction and signals reconstruction technologies with multiple attention mechanism under the framework of joint-domain features is becoming an important development direction of DAS data processing. Attention mechanism can help the network ignore useless information and pay attention to useful information like humans. This paper presents a novel learnable dual attention fusion network (LDAFNet). It combines local and patch-based non-local attention mechanisms together based on the ResBlock modules and makes the extraction process of the network learnable and selective according to different signals or noise. In addition, the novel network can focus on the local complex information and those from the global level. Meanwhile, the residual learning strategy is used to simplify the training process to gradually establish the best mapping under the guidance of L2 loss function. All the experimental results of the simulation and actual records show that our novel network has better denoising and effective signals restoration ability. It can clearly recover the upward and downward wave fields and attenuate different types of noise with less effective energy loss.

Compact broadband high-resolution real-time four-dimensional imaging spectrometer

A broadband high-resolution real-time four-dimensional imaging spectrometer (HRRFDIS) is presented, which can acquire both broadband fine spectra and high-resolution three-dimensional (3D) spatial images of a 3D object in real time. The HRRFDIS consists of a first microlens array arranged in a plane to achieve orthographic view spatial imaging, a second microlens array arranged on a conical surface to measure the depth and to achieve 360-degree side-view spatial imaging, multiple optical fibers, a collimating microlens array arranged in a straight line, a parallel planar transmission grating pair to obtain high spectral resolution over a broadband spectral range, and an area-array detector. Compared with the scanning four-dimensional imaging spectrometer (FDIS), the HRRFDIS can obtain a broadband high-resolution four-dimensional dataset using only one frame of data, and it is more stable, compact, small-sized, and lightweight. Compared to the staring FDIS using a liquid crystal filter and requiring at least one modulation period of liquid crystal to acquire a complete hyperspectral image, the HRRFDIS can acquire a complete broadband hyperspectral image in real time. Compared to existing snapshot FDIS, the HRRFDIS can achieve much higher spectral resolution, especially over a broadband spectral range. The HRRFDIS is a unique concept that is the first to obtain both high-resolution broadband spectral information and high-resolution 3D spatial information in real time, to the best of our knowledge. The HRRFDIS will be suitable for real-time measurement of 3D objects in the ultraviolet to infrared spectral range.

Mid-infrared supercontinuum generation in As2S3-circular photonic crystal fibers pumped by 4.5 µm and 6 µm femtosecond lasers

A study on As2S3 chalcogenide photonic crystal fiber (PCF) and its potential in supercontinuum generation (SCG) applications is presented. The designed fibers exhibit near-zero flattened chromatic dispersion, facilitating coherent and broad SCG utilizing femtosecond lasers at 4.5 and 6 µm wavelengths. A continuous spectrum spanning from 1.5 to 8 µm is achieved when the initial fiber is stimulated with an input power of 20 kW. With a pulse width of 100 fs and input power of 6 kW, the second fiber provides soliton-induced SCG with 2 to 15 µm spectral bandwidth. Furthermore, the integration of these large core diameter PCFs with high-power laser pulses guarantees the preservation of optical fiber integrity without damage. Consequently, these fibers hold promise for delivering SC spectra characterized by high power density, catering to a diverse range of practical applications including optical communications, spectroscopy, sensing, metrology, and calibration.

Optimization and realignment of OAM mode excitation in ring-core optical fibers using machine learning

Optimization and realignment of OAM mode excitation in ring-core optical fibers using machine learning

Simulation analysis of a photonic crystal fiber refractive index sensor based on a double-layer film structure and surface plasmon resonance technology

A photonic crystal fiber surface plasmon resonance sensor based on a double-layer membrane structure is designed and analyzed. In the simple sensing structure with only one air hole size, TiO2 and Au layers with specific thicknesses are sequentially coated on the optical fiber to form a double-layer structure. The sensing characteristics of the double-layer membrane structure are studied by the finite element method. Compared to the single-layer membrane structure, the double-layer membrane sensor has significant sensing properties such as a better wavelength sensitivity and a smaller full width at half maximum in the loss spectrum. In the refractive index range between 1.37 and 1.43, the maximum wavelength sensitivity and average wavelength sensitivity of the sensor are 19,900 nm/RIU and 7417 nm/RIU, respectively, and the resolution can be up to 5.03×10−6RIU. The proposed photonic crystal fiber optic sensor achieves high performance with a simpler sensing structure than previous photonic crystal fiber optic sensors, and eliminates the step of polishing, which will greatly reduce the difficulty of actual fabrication and the error due to uneven polishing. The results show that the photonic crystal fiber optic sensor with a double-layer membrane structure has excellent performance. Due to its high sensitivity and resolution, it has great potential for applications in environmental monitoring, biosensing and chemical sensing.

Exploring chaotic behavior of optical solitons in complex structured Conformable Perturbed Radhakrishnan-Kundu-Lakshmanan Model

In this research, we aim to construct and examine optical soliton solutions for the complex structured Conformable Perturbed Radhakrishnan-Kundu-Lakshmanan Model (CPRKLM) using the Generalized-Kudryashov-Auxiliry Jacobian Method (GKAJM). The current study is notable for its thorough examination and for shedding insight on the chaotic behavior of families of localized optical soliton. Through the creation of 3D and contour visualizations that effectively capture the chaotic behaviors shown by these solitons, we are able to demonstrate that the optical solitons exhibit two distinct forms of perturbations: axial and periodic. Our research stimulates improvements in data processing tools and optical equipment, with consequences for communication networks and nonlinear fiber optics. Through a deeper understanding of optical solitons and their applications, this work also makes a substantial contribution to the discipline of nonlinear optics.

Roadmap on specialty optical fibers

Abstract Optical fibers, long an enabling technology for telecommunications, are proving to play a central role in a growing number of modern applications, starting from high speed broad band internet to medical surgery and entering across the entire spectrum of scientific, military, industrial and commercial applications. Specialty optical fibers either special waveguide structure or novel material composition becomes heart of all fiber based advanced photonics devices and components. This rapidly evolving field calls on the expertise and skills of a broad set of different disciplines: materials science, ceramic engineering, optics, electrical engineering, physics, polymer chemistry, and several others. This roadmap on specialty optical fibers addresses different technologies and application areas. It is constituted by fourteen contributions authored by world-leading experts, providing insight into the current state-of-the-art and the challenges their respective fields face. Some articles address the area of multimode fibers, including the nonlinear effects occurring in them. Several other articles are dedicated to doped, plastic, and soft-glass fibers. Large mode area fibers, hollow-core fibers, and nanostructured fibers are also described in different sections. The use of some of such fibers for optical amplification and to realize several kinds of optical sources - including lasers, single photon sources and supercontinuum sources - is described in some other sections. Different approaches to satisfy applications at visible, infrared and THz spectra regions are also discussed. Throughout the roadmap there is an attempt to foresee and to suggest future directions in this particularly dynamic area of optical fiber technology.

Affordable Highly Sensitive Fiber Optical Sensor Based on Coupled Fibers with Harmonically Varying Refractive Index

Optical fiber sensors consist of multiple Mach–Zehnder (MZ) interferometers and are common in the protection of different compounds. These sensors are very sensitive to any intrusion or threat. However, the spatial resolution is proportional to the number of MZ interferometers along the sensor. Consequently, a long sensor with a high resolution can be costly. In this paper, we suggest replacing the cascaded MZ interferometers with a couple of adjacent fibers, each of which have a harmonically varying refractive index. In this theoretical study, it is shown that two fibers with varying refractive indices demonstrate a sensitivity equivalent to that of multiple MZ interferometers. Furthermore, when the coupling coefficient between the fibers is weak, an analytical expression can be derived for the transmission between the fibers. This transmission reveals a quantization rule for which the light coupling between the two fibers vanishes.

Enhancing IT Infrastructure with Fiber Optics: Revolutionizing Data Flow and Beyond

Fiber optics technology has emerged as a transformative solution in modern IT infrastructure, significantly enhancing data flow and other critical aspects of digital communication. This article explores the latest advancements in fiber optics and how they can be leveraged to improve IT infrastructure. By delving into the benefits of fiber optics, such as increased bandwidth, reduced latency, and improved security, this paper highlights how these technologies can revolutionize data transmission and overall IT operations.

Fiber optic relative humidity and temperature sensor with the cascaded Vernier effect based on the C-shaped cavity structure

The water-absorbent sensing film, coated on the surface of traditional optical fiber humidity sensors, often suffers from detachment issues. In this paper, we present what we believe to be a new fiber-optic cascaded Fabry-Perot interferometer sensor for detecting relative humidity (RH) and temperature, without the need for sophisticated instrumentation. The sensing structure comprises two sections of single-mode optical fibers and a C-shaped cavity between them. The C-shaped cavity is created by grinding the side of a hollow-core fiber with fiber optic abrasive paper. The Vernier effect arises from the cascaded interaction between the C-shaped cavity filled with ultraviolet optical glue (NOA61) and the subsequent single-mode fiber pigtail. The sensor exhibits a high RH sensitivity of 0.248 nm/%RH (35-95%RH) and an RH resolution of up to 0.08%RH. It also has high-temperature sensitivities of -1.091 nm/°C (25 - 65°C). Furthermore, simultaneous measurement of RH and temperature is achieved by establishing a dual parameter matrix, and the sensor's response time and recovery time for RH and temperature are within 300s. Therefore, this work provides a simple and cost-effective manufacturing process and the proposed RH and temperature sensor features a compact size, strong environmental adaptability, and significant potential for practical applications.

Dynamical analysis and optical soliton wave profiles to GRIN multimode optical fiber under the effect of noise

Dynamical analysis and optical soliton wave profiles to GRIN multimode optical fiber under the effect of noise

A novel interface for cortical columnar neuromodulation with multipoint infrared neural stimulation

Cutting edge advances in electrical visual cortical prosthetics have evoked perception of shapes, motion, and letters in the blind. Here, we present an alternative optical approach using pulsed infrared neural stimulation. To interface with dense arrays of cortical columns with submillimeter spatial precision, both linear array and 100-fiber bundle array optical fiber interfaces were devised. We deliver infrared stimulation through these arrays in anesthetized cat visual cortex and monitor effects by optical imaging in contralateral visual cortex. Infrared neural stimulation modulation of response to ongoing visual oriented gratings produce enhanced responses in orientation-matched domains and suppressed responses in non-matched domains, consistent with a known higher order integration mediated by callosal inputs. Controls include dynamically applied speeds, directions and patterns of multipoint stimulation. This provides groundwork for a distinct type of prosthetic targeted to maps of visual cortical columns.

Bridge the gap between simulated and real-world data in optical fiber mode decomposition for accuracy improvement: A deep learning-based co-learning framework with visual similarity-based matching

In the area of optical fiber mode decomposition (MD), data-driven deep-learning (DL) algorithms have achieved remarkable strides with unlimited theoretically synthetic data, but the differences between theoretical and real-world data in the DL context are rarely investigated. The two differences, namely the information bottleneck and the domain discrepancy, between the simulation and realistic domain remain significant obstacles that limit the practical deployment of DL-based MD approaches in real-world optical systems. The paper aims to mitigate their influence on the accuracy limitation and the accuracy degradation of DL-based MD. First, we present a DL-based co-learning framework for MD for the first time. With the co-learning process, the knowledge of the teacher model learned from rich input information sources (near-field, far-field, and phase-distribution optical images) is transferred to the student model with the only near-field input source, which breaks the information bottleneck by allowing the student model to learn more knowledge in a simulation context. Furthermore, to settle the domain discrepancy between ideal data and practical observation, we propose a visual similarity-based matching to assign real values of modal coefficients to the practical optical images whose ground truth values cannot be easily acquired, which enables the transfer learning from the synthetic data to the real-world data for accuracy enhancement. Simulated and experimental results show that the proposed co-learning framework with visual similarity-based matching has realized high precision and robustness in MD simulated and practical tasks. By bridging the gap between theoretical and practical data, our study offers novel perspectives on DL-based MD practice.

Prototype Cherenkov Detector Characterization for Muon Tomography Applications

Muography is an innovative imaging technique using naturally produced elementary particles – atmospheric muons – used to determine the distribution of density inside massive objects. The modification of the particles flux – by scattering or absorption – reflects the contrasts in density within the medium and therefore offers the possibility for an image of the crossed volumes. In most muography setups the imaging process is based on the tracking of the particles which accounts for the absorption or the scattering of the muons trajectories. Neither the energy nor the identity of the particles (the so-called PID) are exploited since this information traditionally relies on the use of calorimeters and/or high intensity magnetic fields. Both these techniques hinder detector portability which in the case of muography is important and this renders them impractical for its purpose. In this paper we characterize the performance of a simple and small water Cherenkov detector capable of providing some insights on the energy of muons and the PID for the crossing particles that could potentially improve the background rejection for a muography survey when operating in conjunction with a muon telescope. We tested a prototype of such water Cherenkov detector in combination with two small muon hodoscopes. Both systems are using the same opto-electronics chain – optical fibers and pixellized photosensors – and the same data acquisition (DAQ) readout system which ensures an easy integration and implementation within presently running systems. This article presents the test setup, the detector response to cosmic muons and its performance evaluation against a basic simulation of its geometry and detection principle.

Extraction of newly soliton wave structure of generalized stochastic NLSE with standard Brownian motion, quintuple power law of nonlinearity and nonlinear chromatic dispersion

Stochastic optical solitons are a fascinating phenomenon in nonlinear optics where soliton-like behavior emerges in systems affected by stochastic noise. This study investigates the influence of Brownian motion on wave propagation in optical fibers. The propagation is modeled using a stochastic nonlinear Schrödinger equation incorporating quintuple power-law nonlinearity and nonlinear chromatic dispersion. To explore this, the improved modified extended tanh (IMET) scheme, leveraging the extended Riccati equation, is employed. This technique facilitates the extraction of various stochastic solutions, including bright, dark, and singular solitons. Furthermore, solutions in the shapes of exponential, singular periodic, and Weierstrass elliptic forms are investigated. The study looks at how the strength of noise impacts various solutions, and Matlab software is used to create 2D and 3D graphs that show the results. It has been noted that when noise intensity rises, signal level falls and surface flattens.

Ultra-low loss Rayleigh scattering enhancement via light recycling in fiber cladding

Rayleigh backscattering enhancement (RSE) of optical fibers is an effective means to improve the performance of distributed optical fiber sensing. Femtosecond laser direct-writing techniques have been used to modulate the fiber core for RSE. However, in-core modulation loses more transmission light, thus limiting the sensing distance. In this work, a cladding-type RSE (cl-RSE) structure is proposed, where the femtosecond laser is focused in the fiber cladding and an array of scatterers is written parallel to the core. The refractive-index modulation structure redistributes the light in the cladding, and the backward scattered light is recovered, which enhances the Rayleigh backscattered signal with almost no effect on the core light. Experimentally, it was demonstrated that in an effectual cl-RSE structure, the insertion loss was reduced to 0.00001 dB per scatterer, corresponding to the lowest value for a point scatterer to date. The cl-RSE structure accomplished measurements up to 800°C. In particular, the temperature measurement fluctuation of the cl-RSE fiber portion is only 0.00273°C after annealing. These results show that the cl-RSE structure has effective scattering enhancement, ultra-low loss, and excellent high-temperature characteristics, and has great potential for application in Rayleigh scattering-enhanced distributed fiber sensing.

Using orbital angular momentum for temperature and force sensing in an optical fiber

We demonstrate an optical fiber sensor that uses the orbital angular momentum of light in a polarization maintaining fiber to act as a temperature and force sensor. The polarization of the input light is shown to greatly affect the sensitivity of the sensor. In addition, we show how our sensor can be used to resolve the direction and magnitude of a force applied to a fiber.

EXPRESS: Feasibility of a Fiber-Dispersive Raman Spectrometer for Biomarker Detection.

Raman spectroscopy is among the top analytical techniques for ultra-low-dense organic matter, crucial to the search for life and analysis of celestial body surfaces in space exploration missions. Achieving the ultimate sensitivity in in situ Raman spectroscopy necessitates a breakthrough in detecting inelastically scattered light. Single-photon detectors (SPD) operating in photon counting mode, which can differentiate between Raman and luminescence responses, are promising candidates for the challenging scientific requirements. Since large SPD arrays are not yet commercially available, a dispersive element can be adapted to a single-pixel detector. By exploiting chromatic dispersion in optical fibers and picosecond-pulsed excitation, we delay the arrivals of different spectral components onto a single-pixel SPD. This method also separates weak Raman signals from stronger luminescence through correlated time-domain measurements. We study the impact of fiber properties and the excitation wavelength of a pulsed laser on the spectral resolution of the fiber-dispersive Raman spectrometer (FDRS). Additionally, we demonstrate the FDRS's potential for studying biomarkers and discuss its feasibility for analyzing inclusions in ice matrices.