In-situ characterization of optical micro/nano fibers using scattering
loss analysis
- URL: http://arxiv.org/abs/2402.03400v1
- Date: Mon, 5 Feb 2024 08:06:02 GMT
- Title: In-situ characterization of optical micro/nano fibers using scattering
loss analysis
- Authors: Shashank Suman, Elaganuru Bashaiah, Resmi M, and Ramachandrarao Yalla
- Abstract summary: We experimentally demonstrate the in-situ characterization of optical micro/nano fibers (MNFs)
The MNF is positioned on a microfiber (probe fiber, PF) and simulated for the scattering loss at various PF and TF diameters.
- Score: 6.948439210905343
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We experimentally demonstrate the in-situ characterization of optical
micro/nano fibers (MNFs).The MNF (test fiber, TF) is positioned on a microfiber
(probe fiber, PF) and simulated for the scattering loss at various PF and TF
diameters. The TF is fabricated using chemical etching technique. The PF is a
conventional single-mode fiber with an outer diameter of 125 um. We measure the
scattering loss along the TF axis at various positions i.e. diameters by
mounting it on the PF. The diameter profile of the TF is inferred from the
measured scattering loss and correlated with its surface morphology
measurement. This work demonstrates an effective, low-cost, and non-destructive
method for in-situ characterization of fabricated micro/nano fibers (OMNFs). It
can detect and determine the irregularities on the surface of OMNFs. It can
also be used to quantify the local evanescent field. Detecting such local
points can improve studies that are carried out using these fields in various
sensing and related study domains. It is simple to implement and can be
accessed by all domains of researchers.
Related papers
- Nonlinear Manifold Learning Determines Microgel Size from Raman
Spectroscopy [40.325359811289445]
Recent approaches show a correlation between Raman signals and particle sizes but do not determine polymer size from Raman measurements accurately and reliably.
We propose three alternative machine learning to perform this task, all involving diffusion maps, alternating diffusion maps, and conformal autoencoder networks.
The conformal autoencoders substantially outperform state-of-the-art methods and results for the first time in a promising prediction of polymer size from Raman spectra.
arXiv Detail & Related papers (2024-03-13T09:39:15Z) - Learning Radio Environments by Differentiable Ray Tracing [56.40113938833999]
We introduce a novel gradient-based calibration method, complemented by differentiable parametrizations of material properties, scattering and antenna patterns.
We have validated our method using both synthetic data and real-world indoor channel measurements, employing a distributed multiple-input multiple-output (MIMO) channel sounder.
arXiv Detail & Related papers (2023-11-30T13:50:21Z) - Tunable non-additivity in Casimir-Lifshitz force between graphene
gratings [7.633060349568631]
We investigate the Casimir-Lifshitz force (CLF) between two identical graphene strip gratings.
We take into account the high-order electromagnetic diffractions, the multiple scattering and the exact 2D feature of the graphene strips.
We show that the non-additivity, which is one of the most interesting features of the CLF in general, is significantly high and can be modulated in situ.
arXiv Detail & Related papers (2023-06-30T13:28:28Z) - Single photon optical bistability [55.2480439325792]
We investigate the bistability in a small Fabry-Perot interferometer (FPI) with the optical wavelength size cavity, the nonlinear Kerr medium and only a few photons, on average, excited by the external quantum field.
Multiple stationary states of the FPI cavity field with different spectra are possible at realistic conditions, for example, in the FPI with the photonic crystal cavity and the semiconductor-doped glass nonlinear medium.
arXiv Detail & Related papers (2023-04-15T10:44:51Z) - Method for in-solution, high-throughput T1 relaxometry using fluorescent
nanodiamonds [0.0]
We have developed a measurement platform that can report the T1 spin relaxation time from a large ensemble of FNDs in solution.
Our approach is simple to set up, robust and can be used for rapid material characterisation or a variety of in-situ quantum sensing applications.
arXiv Detail & Related papers (2022-11-27T22:52:14Z) - Fiber-tip endoscope for optical and microwave control [0.0]
We present a robust, fiber based endoscope with a silver direct-laser-written (DLW) structure for radio frequency (RF) emission next to the optical fiber facet.
We are able to excite and probe a sample, such as nitrogen vacancy centers in diamond, with RF and optical signals simultaneously.
Such an endoscope could be used as a powerful tool for measuring a variety of fluorescent particles.
arXiv Detail & Related papers (2022-05-27T17:09:10Z) - Moser Flow: Divergence-based Generative Modeling on Manifolds [49.04974733536027]
Moser Flow (MF) is a new class of generative models within the family of continuous normalizing flows (CNF)
MF does not require invoking or backpropagating through an ODE solver during training.
We demonstrate for the first time the use of flow models for sampling from general curved surfaces.
arXiv Detail & Related papers (2021-08-18T09:00:24Z) - Measurement of the Casimir Force between 0.2 and 8 mum: Experimental
Procedures and Comparison with Theory [0.0]
We present results on the determination of the differential Casimir force between an Au-coated sapphire sphere and the top and bottom of Au-coated deep silicon trenches.
The random and systematic errors in the measured force signal are determined at the 95% confidence level.
The role of surface roughness and edge effects is investigated and shown to be negligibly small.
arXiv Detail & Related papers (2021-04-08T16:00:59Z) - Entropy Minimizing Matrix Factorization [102.26446204624885]
Nonnegative Matrix Factorization (NMF) is a widely-used data analysis technique, and has yielded impressive results in many real-world tasks.
In this study, an Entropy Minimizing Matrix Factorization framework (EMMF) is developed to tackle the above problem.
Considering that the outliers are usually much less than the normal samples, a new entropy loss function is established for matrix factorization.
arXiv Detail & Related papers (2021-03-24T21:08:43Z) - A reusable pipeline for large-scale fiber segmentation on unidirectional
fiber beds using fully convolutional neural networks [68.8204255655161]
We present an open computational pipeline to detect fibers in ex-situ X-ray computed tomography fiber beds.
To separate the fibers in these samples, we tested four different architectures of fully convolutional neural networks.
When comparing our neural network approach to a semi-supervised one, we obtained Dice and Matthews coefficients greater than $92.28 pm 9.65%$, reaching up to $98.42 pm 0.03 %$.
arXiv Detail & Related papers (2021-01-13T00:58:29Z) - Microscopic Relaxation Channels in Materials for Superconducting Qubits [76.84500123816078]
We show correlations between $T_$ and grain size, enhanced oxygen diffusion along grain boundaries, and concentration of suboxides near the surface.
Physical mechanisms connect these microscopic properties to residual surface resistance and $T_$ through losses arising from the grain boundaries and from defects in the suboxides.
This comprehensive approach to understanding qubit decoherence charts a pathway for materials-driven improvements of superconducting qubit performance.
arXiv Detail & Related papers (2020-04-06T18:01:15Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.