Novel Low-Loss Fiber-Chip Edge Coupler for Coupling Standard Single Mode Fibers to Silicon Photonic Wire Waveguides

Fiber-to-chip optical interconnects is a big challenge in silicon photonics application scenarios such as data centers and optical transmission systems. An edge coupler, compared to optical grating, is appealing to in the application of silicon photonics due to the high coupling efficiency between standard optical fibers (SMF-28) and the sub-micron silicon wire waveguides. In this work, we proposed a novel fiber–chip edge coupler approach with a large mode size for silicon photonic wire waveguides. The edge coupler consists of a multiple structure which was fulfilled by multiple silicon nitride layers embedded in SiO2 upper cladding, curved waveguides and two adiabatic spot size converter (SSC) sections. The multiple structure can allow light directly coupling from large mode size fiber-to-chip coupler, and then the curved waveguides and SSCs transmit the evanescent field to a 220 nm-thick silicon wire waveguide based on the silicon-on-insulator (SOI) platform. The edge coupler, designed for a standard SMF-28 fiber with 8.2 μm mode field diameter (MFD) at a wavelength of 1550 nm, exhibits a mode overlap efficiency exceeding 95% at the chip facet and the overall coupling exceeding 90%. The proposed edge coupler is fully compatible with standard microfabrication processes.

pmTM-align: scalable pairwise and multiple structure alignment with Apache Spark and OpenMP

Background Structure comparison can provide useful information to identify functional and evolutionary relationship between proteins. With the dramatic increase of protein structure data in the Protein Data Bank, computation time quickly becomes the bottleneck for large scale structure comparisons. To more efficiently deal with informative multiple structure alignment tasks, we propose pmTM-align, a parallel protein structure alignment approach based on mTM-align/TM-align. pmTM-align contains two stages to handle pairwise structure alignments with Spark and the phylogenetic tree-based multiple structure alignment task on a single computer with OpenMP. Results Experiments with the SABmark dataset showed that parallelization along with data structure optimization provided considerable speedup for mTM-align. The Spark-based structure alignments achieved near ideal scalability with large datasets, and the OpenMP-based construction of the phylogenetic tree accelerated the incremental alignment of multiple structures and metrics computation by a factor of about 2–5. Conclusions pmTM-align enables scalable pairwise and multiple structure alignment computing and offers more timely responses for medium to large-sized input data than existing alignment tools such as mTM-align.

Modal analysis of a multiple structure

The aim of the work was to carry out a modal analysis of a multiple structure. Own forms of oscillation of the structure for five tones were obtained through the vector iteration process and were presented in table and graphic form. Using the different methods (Time history, SRSS and CQC), a calculation of the displacements was performed. Theoretically, all three methods are described and the results of the calculation for each of them are obtained. A comparison of the results, for the three methods in a given time interval, is graphically shown. Also, the results are compared which are all the same in all three methods. The modal seismic analysis of Spectral Theory was also performed. It can be concluded that by comparing the method of Time history and Spectral theory their results correspond to the maximum modal displacement.