Machine Learning Assisted Inverse Design for Ultrafine, Dynamic and Arbitrary Gain Spectrum Shaping of Raman Amplification

Distributed Raman amplifier (DRA) has been widely studied in recent decades because of its low noise figure and flexible gain. In this paper, we present a novel scheme of DRA with broadband amplified spontaneous emission(ASE) source as pump instead of discrete pump lasers. The broadband pump is optimized by machine learning based inverse design and shaped by programmable waveshaper, so as to realize the ultrafine, dynamic and arbitrary gain spectrum shaping of Raman amplification. For the target of flat gain spectrum, the maximum gain flatness of 0.1086 dB is realized based on the simulation results. For the target of arbitrary gain spectrum, we demonstrate four gain profiles with maximum root mean square error (RMSE) of 0.074 dB. To further measure the performance of arbitrary gain spectrum optimization, the probability density functions (PDF) of RMSE and Errormax are presented. Meanwhile, the numeral relationship between the bands of broadband pump and signal is also explored. Furthermore, this work has great application potential to compensate the gain distortion or dynamic change caused by other devices in communication systems.

Application of Virtual Display Technology of LCD Backlight Spectrum Optimization Algorithm Based on Linear Programming

In order to make the color of image display more realistic, optimize the use of energy, and improve the light efficiency of the module through reasonable spectral distribution, this paper proposes a backlight spectral optimization algorithm based on linear programming. With the goal of maximizing the backlight luminous efficiency, the theoretical maximum of the luminous efficiency of the backlight spectrum can be achieved by constructing a linear programming model. The research process is to obtain the optimal distribution of transmittance spectrum by linear programming method on the premise of ensuring the color gamut standard of display system. The results show that the light efficiency can be increased to 335.5 lm/W, while the original light efficiency of the system is less than 150 lm/W. With the goal of maximizing the light efficiency, light sources with narrow bandwidths such as lasers and quantum dot materials can be used to simulate and reconstruct these characteristic wavelengths. There will be easier to approach the ideal optimization spectrum and achieve the theoretical maximum luminous efficiency of 610.8 lm/W.

Ovalbumin antigen-specific activation of T cell receptor closely resembles soluble antibody stimulation as revealed by BOOST phosphotyrosine proteomics

Activation of T cell receptors (TCR) leads to a network of early signaling predominantly orchestrated by tyrosine phosphorylation in T cells. TCR are commonly activated using soluble anti-TCR antibodies, but this approach is not antigen-specific. Alternatively, activating the TCR using specific antigens of a range of binding affinities in the form of peptide-major histocompatibility complex (pMHC) is presumed to be more physiological. However, due to the lack of wide-scale phosphotyrosine (pTyr) proteomic studies directly comparing anti-TCR antibodies and pMHC, a comprehensive definition of these activated states remains enigmatic. Elucidation of the tyrosine phosphoproteome using quantitative pTyr proteomics enables a better understanding of the unique features of these activating agents and the role of ligand binding affinity on signaling. Here, we apply the recently established Broad-spectrum Optimization Of Selective Triggering (BOOST) to examine perturbations in tyrosine phosphorylation of TCR triggered by anti-TCR antibodies and pMHC. Our data reveals that high-affinity ovalbumin (OVA) pMHC activation of the TCR triggers a largely similar, albeit potentially stronger, pTyr-mediated signaling regulatory axis compared to anti-TCR antibody. Signaling output resulting from OVA pMHC variants correlates well with their weaker affinities, enabling affinity-tunable control of signaling strength. Collectively, we provide a framework for applying BOOST to compare pTyr-mediated signaling pathways of T cells activated in an antigen-independent and antigen-specific manner.

Detection Spectrum Optimization of Stealth Aircraft Targets From a Space-based Infrared Platform

Advances in infrared detection techniques require novel spectrum dynamic-modification strategies capable of sensing unprecedentedly low target radiant intensities. A conventional fixed-spectrum detection system cannot satisfy the effective detection of stealth aircraft targets due to complex Earth background clutter and atmospheric attenuation. Therefore, a detection method that can highlight aircraft targets is urgently needed to enhance stealth aircraft detectability. In this research, a spectrum set consisting of different bandwidths associated with a central wavelength is established. Furthermore, a signal-to-noise ratio of the stealth aircraft is computed using the established spectrum set. Finally, the optimal spectrum is selected according to the maximal signal-to-noise ratio from the spectrum set. Our numerical experiments and simulations further demonstrate that the proposed methodology can substantially strengthen the detection performance of stealth aircraft compared with traditional fixed-spectrum detection systems. This work on detection spectrum optimization paves the way to stealth aircraft detection and opens new vistas in the field of target detection technology.