Related papers: Distributed Brillouin frequency shift extraction v…
In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP algorithm in a…
Stimulated Brillouin-Mandelstam scattering offers exceptional capabilities for photonic signal processing, but current platforms demand performance trade-offs between long interaction lengths, high gain, low optical losses, and practical…
We demonstrate a hybrid distributed fiber sensing system for multi-parameter detection. The integration of phase-sensitive optical time domain reflectometry ({\Phi}-OTDR) and Brillouin optical time domain reflectometry (B-OTDR) enables…
We develop a simple and cost-efficient configuration of Brillouin optical correlation-domain reflectometry (BOCDR), the setup of which does not include an additional reference path used in standard BOCDR systems. The Fresnel-reflected light…
Fiber tractography is an important tool of computational neuroscience that enables reconstructing the spatial connectivity and organization of white matter of the brain. Fiber tractography takes advantage of diffusion Magnetic Resonance…
We present an optical technique based on ultrafast photoacoustics to precisely determine the local temperature distribution profile in liquid samples in contact with a laser heated optical transducer. This ultrafast pump-probe experiment…
Brillouin spectroscopy is a powerful optical technique for viscoelastic characterization of samples without contact. However, like all optical systems, Brillouin spectroscopy performances are degraded by optical aberrations, and have…
We consider the problem of online learning in the presence of distribution shifts that occur at an unknown rate and of unknown intensity. We derive a new Bayesian online inference approach to simultaneously infer these distribution shifts…
We study the problem of distributed and rate-adaptive feature compression for linear regression. A set of distributed sensors collect disjoint features of regressor data. A fusion center is assumed to contain a pretrained linear regression…
Time-resolved single-molecule biophysical experiments yield data that contain a wealth of dynamic information, in addition to the equilibrium distributions derived from histograms of the time series. In typical force spectroscopic setups…
While radiation-pressure cooling is well known, the Brillouin scattering of light from sound is considered an acousto-optical amplification-only process. It was suggested that cooling could be possible in multi-resonance Brillouin systems…
Brillouin microscopy measures compressibility, but is being increasingly used to assess stiffness of cells and tissues. Using hydrogels with tunable properties, we demonstrate that Brillouin microscopy is insensitive to stiffness of…
Recently, many studies have shed light on the high adaptivity of deep neural network methods in nonparametric regression models, and their superior performance has been established for various function classes. Motivated by this…
Mode-sorting is a procedure that decomposes a light field into a basis of transverse modes, directing each mode into a separate spatial location, allowing the constituent mode intensities to be measured simultaneously. We demonstrate a…
Automatic detection of faults in optical fibers is an active area of research that plays a significant role in the design of reliable and stable optical networks. A fiber measurement system that combines automated data acquisition and…
Characterizing the micromechanical properties of cells and extracellular matrices is critical in mechanobiology. To meet this need, Brillouin light scattering (BLS) has emerged as a noncontact, high-resolution elastography tool that probes…
Many problems in mechanobiology urgently require characterisation of the micromechanical properties of the fibrous proteins of cells and tissues. Brillouin light scattering has been proposed as a new optical elastography technique to meet…
We introduce deep learning technique to perform complete mode decomposition for few-mode optical fiber for the first time. Our goal is to learn a fast and accurate mapping from near-field beam profiles to the complete mode coefficients,…
Ultra-narrow optical spectral features resulting from highly dispersive light-matter interactions are essential for a broad range of applications such as spectroscopy, slow-light, and high-precision sensing. Features approaching sub-MHz, or…
Brillouin scattering has been widely exploited for advanced photonics functionalities such as microwave photonics, signal processing, sensing, lasing, and more recently in micro- and nano-photonic waveguides. So far, all the works have…