Enhanced Performance of Artificial-Neural-Network-Based Equalization for Short-Haul Fiber-Optic Communications.

This work proposes an efficient and easy-to-implement single-layer artificial neural network (ANN)-based equalizer with improved compensation performance. The proposed equalizer is used for effectively mitigating the distortions induced in the short-haul fiber-optic communication systems based on intensity modulation and direct detection (IMDD). The compensation performance of the ANN equalizer is significantly improved, exploiting an introduced advanced training scheme. The efficiency and robustness of the proposed ANN equalizer are illustrated through 10- and 28-Gbaud short-reach optical-fiber communication systems. Compared to the efficient but computationally expensive maximum likelihood sequence estimator (MLSE), the proposed ANN equalizer not only significantly reduces its computational equalization cost and storage memory requirements, but it also outperforms its bit error rate performance.

Adaptive digital back propagation exploiting adjoint-based optimization for fiber-optic communications.

This work proposes a novel and powerful adaptive digital back propagation (A-DBP) method with a fast adaption process. Given that the total transmission distance is known, the proposed A-DBP algorithm blindly compensates for the linear and nonlinear distortions of optical fiber transmission systems and networks, without knowing the launch power and channel parameters. An adjoint-based optimization (ABO) technique is proposed to significantly accelerate the parameters estimation of the A-DBP. The ABO algorithm utilizes a sequential quadratic programming (SQP) method coupled with an adjoint sensitivity analysis (ASA) approach to rapidly solve the A-DBP training problem. The design parameters are optimized using the minimum overhead of only one extra system simulation. Regardless of the number of A-DBP design parameters, the derivatives of the training objective function with respect to all parameters are estimated using only one extra adjoint system simulation per optimization iterate. This is contrasted with the traditional finite-difference (FD)-based optimization methods whose sensitivity analysis calculations cost per iterate scales linearly with the number of parameters. The robustness, performance, and efficiency of the proposed A-DBP algorithm are demonstrated through applying it to mitigate the distortions of 4-span and 20-span optical fiber communication systems. Coarse-mesh A-DBPs with less number of virtual spans are also used to significantly reduce the computational complexity of the equalizer, achieving compensation performance higher than that obtained using the coarse-mesh DBP with the exact channel parameters and full number of virtual spans.

Adjoint sensitivity analysis approach for the nonlinear Schrödinger equation.

This Letter proposes a novel adjoint sensitivity analysis approach for the nonlinear Schrödinger equation, which describes the light wave propagation in optical fiber communication systems. Using only one extra adjoint system simulation, all the sensitivities of a general objective function with respect to all fiber design parameters are estimated. We provide a full description of the solution to the derived adjoint problem. The accuracy and efficiency of our proposed algorithm are illustrated through optical fiber examples.

Time domain adjoint sensitivity analysis of electromagnetic problems with nonlinear media.

In this paper, we propose a theory for wideband adjoint sensitivity analysis of problems with nonlinear media. We show that the sensitivities of the desired response with respect to all shape and material parameters are obtained through one extra adjoint simulation. Unlike linear problems, the system matrices of this adjoint simulation are time varying. Their values are determined during the original simulation. The proposed theory exploits the time-domain transmission line modeling (TLM) and provides an efficient AVM approach for sensitivity analysis of general time domain objective functions. The theory has been illustrated through a number of examples.

Adjoint sensitivity analysis of plasmonic structures using the FDTD method.

We present an adjoint variable method for estimating the sensitivities of arbitrary responses with respect to the parameters of dispersive discontinuities in nanoplasmonic devices. Our theory is formulated in terms of the electric field components at the vicinity of perturbed discontinuities. The adjoint sensitivities are computed using at most one extra finite-difference time-domain (FDTD) simulation regardless of the number of parameters. Our approach is illustrated through the sensitivity analysis of an add-drop coupler consisting of a square ring resonator between two parallel waveguides. The computed adjoint sensitivities of the scattering parameters are compared with those obtained using the accurate but computationally expensive central finite difference approach.

Realizing vertical light coupling and splitting in nano-plasmonic multilevel circuits.

We present a novel technique for vertical coupling of light guided by nanoscale plasmonic slot waveguides (PSWs). A triangularly-shaped plasmonic slot waveguide rotator is exploited to attain such coupling with a good efficiency over a wide bandwidth. Using this approach, light propagating in a horizontal direction is efficiently coupled to propagate in the vertical direction and vice versa. We also propose a power divider configuration to evenly split a vertically coupled light wave to two horizontal channels. A detailed parametric study of the triangular rotator is demonstrated with multiple configurations analyzed. This structure is suitable for efficient coupling in multilevel nano circuit environment.

Optimized polarization-independent Chand-Bali nano-antenna for thermal IR energy harvesting.

A novel, polarization-independent, wide-angle reception Chand-Bali nano-antenna is proposed. An adjoint-based optimization algorithm is used to create the same resonance at both linear polarizations of the incident radiation. The nano-antenna optimal parameters reveal that two hot spots with a strong field enhancement are created. These hot-spots could be integrated with metal-insulator-metal (MIM) diodes to form a rectenna for infrared (IR) energy harvesting. The metallic resonators allow for selecting several materials to facilitate the fabrication of the nano-antenna and the MIM diode. The Chand-Bali-based IR rectennas are investigated and simulations demonstrate an improvement of more than one order of magnitude in efficiency compared to ones using traditional nano-antennas.

Deep Learning-Based Metasurface Design for Smart Cooling of Spacecraft.

A reconfigurable metasurface constitutes an important block of future adaptive and smart nanophotonic applications, such as adaptive cooling in spacecraft. In this paper, we introduce a new modeling approach for the fast design of tunable and reconfigurable metasurface structures using a convolutional deep learning network. The metasurface structure is modeled as a multilayer image tensor to model material properties as image maps. We avoid the dimensionality mismatch problem using the operating wavelength as an input to the network. As a case study, we model the response of a reconfigurable absorber that employs the phase transition of vanadium dioxide in the mid-infrared spectrum. The feed-forward model is used as a surrogate model and is subsequently employed within a pattern search optimization process to design a passive adaptive cooling surface leveraging the phase transition of vanadium dioxide. The results indicate that our model delivers an accurate prediction of the metasurface response using a relatively small training dataset. The proposed patterned vanadium dioxide metasurface achieved a 28% saving in coating thickness compared to the literature while maintaining reasonable emissivity contrast at 0.43. Moreover, our design approach was able to overcome the non-uniqueness problem by generating multiple patterns that satisfy the design objectives. The proposed adaptive metasurface can potentially serve as a core block for passive spacecraft cooling applications. We also believe that our design approach can be extended to cover a wider range of applications.

Polarization-controlled excitation of multilevel plasmonic nano-circuits using single silicon nanowire.

We propose a surface plasmon polarization-controlled beam splitter based on plasmonic slot waveguides (PSWs). It couples light of different polarizations from a silicon nanowire into multilevel plasmonic networks. Two orthogonal PSWs are utilized as the guiding waveguides for each polarization. The proposed structure overcomes inherent polarization limitation in plasmonic structures by providing multilevel optical signal processing. This ability of controlling polarization can be exploited to achieve 3-D multilevel plasmonic circuits and polarization controlled chip to chip channel. Our device is of a compact size and a wide band operation. The device utilizes both quasi-TE and quasi-TM polarizations to allow for increased optical processing capability. The crosstalk is minimal between the two polarizations propagating in two different levels. We achieve good transmission efficiency at a wavelength of 1.55 µm for different polarizations. We analyze and simulate the structure using the FDTD method. The proposed device can be utilized in integrated chips for optical signal processing and optical computations.

Anticancer activity of milk fat rich in conjugated linoleic acid against Ehrlich ascites carcinoma cells in female Swiss albino mice.

BACKGROUND AND AIM: The major conjugated linoleic acid (CLA) isomers have anticancer effect, especially breast cancer cells, inhibits cell growth and induces cell death. Also, CLA has several health benefits in vivo, including antiatherogenesis, antiobesity, and modulation of immune function. The present study aimed to assess the safety and anticancer effects of milk fat CLA against in vivo Ehrlich ascites carcinoma (EAC) in female Swiss albino mice. This was based on acute toxicity study, detection of the tumor growth, life span of EAC bearing hosts, and simultaneous alterations in the hematological, biochemical, and histopathological profiles. MATERIALS AND METHODS: One hundred and fifty adult female mice were equally divided into five groups. Groups (1-2) were normal controls, and Groups (3-5) were tumor transplanted mice (TTM) inoculated intraperitoneally with EAC cells (2×106/0.2 mL). Group (3) was (TTM positive control). Group (4) TTM fed orally on balanced diet supplemented with milk fat CLA (40 mg CLA/kg body weight). Group (5) TTM fed orally on balanced diet supplemented with the same level of CLA 28 days before tumor cells inoculation. Blood samples and specimens from liver and kidney were collected from each group. The effect of milk fat CLA on the growth of tumor, life span of TTM, and simultaneous alterations in the hematological, biochemical, and histopathological profiles were examined. RESULTS: For CLA treated TTM, significant decrease in tumor weight, ascetic volume, viable Ehrlich cells accompanied with increase in life span were observed. Hematological and biochemical profiles reverted to more or less normal levels and histopathology showed minimal effects. CONCLUSION: The present study proved the safety and anticancer efficiency of milk fat CLA and provides a scientific basis for its medicinal use as anticancer attributable to the additive or synergistic effects of its isomers.

Modeling and design of nano-plasmonic structures using transmission line modeling.

For the first time, we demonstrate the application of the time domain transmission line method (TLM) to accurate modeling of surface plasmon polariton (SPP) structures. The constructed TLM node allows for modeling of dispersive materials through simple time-difference equations. Using such node, an ultra-wide band excitation can be applied to obtain the response over the band of interest. Bérenger's perfectly matched layer (PML) boundary condition can readily be implemented using the same node. We illustrate our TLM approach through the modeling of different challenging structures including SPPs filters and focusing structures.

Efficient 3D sensitivity analysis of surface plasmon waveguide structures.

We present a novel analytical approach for efficient sensitivity analysis of surface plasmon polaritons (SPPs) waveguide-based structures using the beam propagation method (BPM). Our approach exploits the adjoint variable technique to extract the response sensitivities with respect to all the design parameters regardless of their number. No extra BPM simulations are required. The accuracy of the results are comparable to those obtained using the expensive central finite difference approximations applied at the response level. Our approach is successfully applied to different SPPs structures for different applications.

Accurate sensitivity analysis of photonic devices exploiting the finite-difference time-domain cavity adjoint variable method.

For what is believed to be the first time, the central adjoint variable method (CAVM) is applied to the sensitivity analysis of photonic devices using the finite-difference time-domain (FDTD) technique. The FDTD-CAVM technique obtains accurate sensitivities of any desired response with respect to the different design parameters. Our technique requires only one extra FDTD simulation to extract the sensitivities with respect to all the design parameters regardless of their number. Cost-free sensitivities of the power reflectivity are also derived without any additional simulation. The results show a very good agreement between the CAVM sensitivities and those obtained using the expensive central finite difference approximation.