Silicon Photonics Cloud (SiCloud) P. T. S. DeVore1,2,3, Y. Jiang1, M. Lynch1, T. Miyatake1, C. Carmona2, A. C. Chan1, K. Muniam2, J. Adam1,4, and B. Jalali1 1
Dept. of Electrical Engineering, University of California, Los Angeles, CA, USA, 90095; Dept. of Physics and Astronomy, University of California, Los Angeles, CA, USA, 90095; 3 Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA, USA, 94550; 4 Mads Clausen Institute, University of Southern Denmark, DK-6400 Sønderborg, Denmark
[email protected] 2
Abstract: Silicon Photonics Cloud (SiCloud.org) is the first silicon photonics interactive web tool. Here we report new features of this tool including mode propagation parameters and mode distribution galleries for user specified waveguide dimensions and wavelengths. OCIS codes: (130.5990) Integrated optics: semiconductors; (130.2790) Integrated optics: guided waves
1. Introduction The silicon photonics is a rapidly growing field [1, 2]; therefore, educational tools are needed to facilitate device design and to train the next generation of engineers who will fuel the industry. However, due to its interdisciplinary nature, encompassing material science, semiconductor physics, electronics and waveguide optics, acquiring the skill and intuition can be a lengthy process. To address this issue, a web-based interactive tool known as Silicon Photonics Cloud (SiCloud [3]; http://www.sicloud.org/) is being developed. Version 1.0 debuted in June of 2014, and includes Material Parameters and their wavelength dependence for silicon and related materials. It consolidates key data on prominent silicon photonics materials that are needed for device design. Work continues towards making SiCloud a “vertically integrated” learning and design platform, with modules spanning the full range from fundamental physics to abstract systems engineering. Along that effort, we report the next version of the tool featuring interactive waveguide propagation mode parameters. The new feature presents effective modal properties, as well as spatial distributions, and is both an exploratory tool and a reference against which to check simulations and experimental results. This tool includes data from mode simulations of channel silicon-on-insulator waveguides across a wide range of relevant telecommunications wavelengths and submicron geometries and all guided modes for a given userdefined configuration. 2. Waveguide Parameters
Fig. 1 Waveguide Parameters Main Graph. Here, SiCloud plots propagation parameters of silicon photonic waveguide modes, whose properties are chosen by the user from a pre-calculated database.
Selecting the new tool in the user interface takes the user to the Waveguide Parameters page. Figure 1 shows the Main Graph in the Waveguide Parameters tab, which allows one to plot waveguide propagation
properties as a function of geometry or wavelength. The user may view important waveguide properties, including refractive index, group velocity, group velocity dispersion as well as higher-order dispersion, and Kerr nonlinear coefficient. One may vary choice of both independent and dependent variables to provide maximal flexibility in examining the relationship between modes. To calculate group velocity and group velocity dispersion, we used polynomial regression and analytic derivatives.
Fig. 2 Waveguide Mode Gallery. SiCloud presents waveguide mode intensity and electric field distributions in multiple views, wherein the user may independently change the physical quantity viewed as well as the simulation conditions. Shown here is an example of the intensity distribution and electric field components of the TM0 mode.
The Mode Gallery feature (c.f. Figure 2) allows one to explore the spatial distribution of modes, which not only builds the user’s wave-optics intuition, but has direct relevance for device design. For example, silicon photonic biosensors rely on measuring small changes in the modal index due to nearby analytes [4] and so are reliant on the precise geometry. As seen in Figure 2, the user selects the geometry and wavelength, and then may view the intensity or electric field components. Side-by-side views allow the user to study contrasting modes, geometries and wavelengths, to optimize sensor sensitivity. 3. Conclusion We have extended Silicon Photonics Cloud (SiCloud), the first silicon photonics online interactive resource, to include waveguide simulations. This brings SiCloud one step closer to being an all-inclusive learning and reference platform. SiCloud is a work in progress and will continue to grow towards the system level. We encourage feedback from academic and industrial users, for whom this tool was built. Acknowledgements Y. Jiang, J. Adam, B. Jalali would like to acknowledge support from the National Science Foundation CIAN ERC under Grant No. EEC-0812072. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. References [1] (2014, December 29). ADVANCED PACKAGING: Silicon Photonics 2014 report [Online]. Available: https://web.archive.org/web/20141229020142/http://www.marketresearch.com/Yole-Developpementv2585/ADVANCED-PACKAGING-Silicon-Photonics-8330874/ [2] J. Wolfe. (2012) Why IBM and Intel Are Chasing the $100B Opportunity in Nanophotonics. Forbes. Available: https://web.archive.org/web/20141229012533/http://www.forbes.com/sites/joshwolfe/2012/12/13/why-ibmand-intel-are-chasing-the-100b-opportunity-in-nanophotonics/ [3] P. T. DeVore, Y. Jiang, M. Lynch, T. Miyatake, C. Carmona, A. C. Chan, et al., "Silicon photonics cloud (SiCloud)," in SPIE OPTO, 2015, pp. 93670G. [4] P. V. Lambeck, "Integrated opto-chemical sensors," Sensors and Actuators B: Chemical vol. 8, no. 1, pp. 103, Apr. 1992.
