A new architecture for high speed core-selective switch for multicore fibers

The use of multicore optical fibers is now recognized as one of the most promising methods to implement the space-division multiplexing techniques required to overcome the impending capacity limit of conventional single-mode optical fibers. Nonetheless, new devices for networking operations compatible with these fibers will be required in order to implement the next-generation high-capacity optical networks. In this work, we develop a new architecture to build a high-speed core-selective switch, critical for efficiently distributing signals over the network. The device relies on multicore interference, and can change among outputs in less than 0.7 us, while achieving less than -18 dB of average inter-core crosstalk, making it compatible with a wide range of network switching tasks. The functionality of the device was demonstrated by routing a 1GBs optical signal and by successfully switching signals over a field-installed multicore fiber network. Our results demonstrate for the first time the operation of a multicore optical fiber switch functioning under real-world conditions, with switching speeds that are three orders of magnitude faster than current commercial devices. This new optical switch design is also fully compatible with standard multiplexing techniques and, thus, represents an important achievement towards the integration of high-capacity multicore telecommunication networks.

Parallel optimization of fiber bundle segmentation for massive tractography datasets

We present an optimized algorithm that performs automatic classification of white matter fibers based on a multi-subject bundle atlas. We implemented a parallel algorithm that improves upon its previous version in both execution time and memory usage. Our new version uses the local memory of each processor, which leads to a reduction in execution time. Hence, it allows the analysis of bigger subject and/or atlas datasets. As a result, the segmentation of a subject of 4,145,000 fibers is reduced from about 14 minutes in the previous version to about 6 minutes, yielding an acceleration of 2.34. In addition, the new algorithm reduces the memory consumption of the previous version by a factor of 0.79.