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Polarimetric imaging has a wide range of applications for uncovering features invisible to human eyes and conventional imaging sensors. Chip-integrated, fast, cost-effective, and accurate full-Stokes polarimetric imaging sensors are highly desirable in many applications, which, however, remain elusive due to fundamental material limitations. Here we present a chip-integratedMetasurface-based Full-StokesPolarimetricImaging sensor (MetaPolarIm) realized by integrating an ultrathin (~600 nm) metasurface polarization filter array (MPFA) onto a visible imaging sensor with CMOS compatible fabrication processes. The MPFA is featured with broadband dielectric-metal hybrid chiral metasurfaces and double-layer nanograting polarizers. This chip-integrated polarimetric imaging sensor enables single-shot full-Stokes imaging (speed limited by the CMOS imager) with the most compact form factor, records high measurement accuracy, dual-color operation (green and red) and a field of view up to 40 degrees. MetaPolarIm holds great promise to enable transformative applications in autonomous vision, industry inspection, space exploration, medical imaging and diagnosis.

 

Graphene is an attractive material for all-optical modulation because of its ultrafast optical response and broad spectral coverage. However, all-optical graphene modulators reported so far require high pump fluence due to the ultrashort photo-carrier lifetime and limited absorption in graphene. We present modulator designs based on graphene-metal hybrid plasmonic metasurfaces with highly enhanced light-graphene interaction in the nanoscale hot spots at pump and probe (signal) wavelengths. Based on this design concept, we have demonstrated high-speed all-optical modulators at near and mid-infrared wavelengths (1.56 μm and above 6 μm) with significantly reduced pump fluence (1–2 orders of magnitude) and enhanced optical modulation. Ultrafast near-infrared pump-probe measurement results suggest that the modulators’ response times are ultimately determined by graphene’s ultrafast photocarrier relaxation times on the picosecond scale. The proposed designs hold the promise to address the challenges in the realization of ultrafast all-optical modulators for mid-and far-infrared wavelengths.

 

Large-scale distributed systems must be built to anticipate and mitigate a variety of hardware and software failures. In order to build confidence that fault-tolerant systems are correctly implemented, Netflix (and similar enterprises) regularly run failure drills in which faults are deliberately injected in their production system. The combinatorial space of failure scenarios is too large to explore exhaustively. Existing failure testing approaches either randomly explore the space of potential failures randomly or exploit the "hunches" of domain experts to guide the search. Random strategies waste resources testing "uninteresting" faults, while programmer-guided approaches are only as good as human intuition and only scale with human effort. In this paper, we describe how we adapted and implemented a research prototype called lineage-driven fault injection (LDFI) to automate failure testing at Netflix. Along the way, we describe the challenges that arose adapting the LDFI model to the complex and dynamic realities of the Netflix architecture. We show how we implemented the adapted algorithm as a service atop the existing tracing and fault injection infrastructure, and present early results.