Scalable High-Precision Trimming of Photonic Resonances by Polymer Exposure to Energetic Beams.

Integrated photonic circuits (PICs) have seen an explosion in interest, through to commercialization in the past decade. Most PICs rely on sharp resonances to modulate, steer, and multiplex signals. However, the spectral characteristics of high-quality resonances are highly sensitive to small variations in fabrication and material constants, which limits their applicability. Active tuning mechanisms are commonly employed to account for such deviations, consuming energy and occupying valuable chip real estate. Readily employable, accurate, and highly scalable mechanisms to tailor the modal properties of photonic integrated circuits are urgently required. Here, we present an elegant and powerful solution to achieve this in a scalable manner during the semiconductor fabrication process using existing lithography tools: by exploiting the volume shrinkage exhibited by certain polymers to permanently modulate the waveguide's effective index. This technique enables broadband and lossless tuning with immediate applicability in wide-ranging applications in optical computing, telecommunications, and free-space optics.

Antimony as a Programmable Element in Integrated Nanophotonics.

The use of nonlinear elements with memory as photonic computing components has seen a huge surge in interest in recent years with the rise of artificial intelligence and machine learning. A key component is the nonlinear element itself. A class of materials known as phase change materials has been extensively used to demonstrate the viability of such computing. However, such materials continue to have relatively slow switching speeds, and issues with cyclability related to phase segregation of phase change alloys. Here, using antimony (Sb) thin films with thicknesses less than 5 nm we demonstrate reversible, ultrafast switching on an integrated photonic platform with retention time of tens of seconds. We use subpicosecond pulses, the shortest used to switch such elements, to program seven distinct memory levels. This portends their use in ultrafast nanophotonic applications ranging from nanophotonic beam steerers to nanoscale integrated elements for photonic computing.

Collapse of the West Antarctic Ice Sheet after local destabilization of the Amundsen Basin.

The future evolution of the Antarctic Ice Sheet represents the largest uncertainty in sea-level projections of this and upcoming centuries. Recently, satellite observations and high-resolution simulations have suggested the initiation of an ice-sheet instability in the Amundsen Sea sector of West Antarctica, caused by the last decades' enhanced basal ice-shelf melting. Whether this localized destabilization will yield a full discharge of marine ice from West Antarctica, associated with a global sea-level rise of more than 3 m, or whether the ice loss is limited by ice dynamics and topographic features, is unclear. Here we show that in the Parallel Ice Sheet Model, a local destabilization causes a complete disintegration of the marine ice in West Antarctica. In our simulations, at 5-km horizontal resolution, the region disequilibrates after 60 y of currently observed melt rates. Thereafter, the marine ice-sheet instability fully unfolds and is not halted by topographic features. In fact, the ice loss in Amundsen Sea sector shifts the catchment's ice divide toward the Filchner-Ronne and Ross ice shelves, which initiates grounding-line retreat there. Our simulations suggest that if a destabilization of Amundsen Sea sector has indeed been initiated, Antarctica will irrevocably contribute at least 3 m to global sea-level rise during the coming centuries to millennia.

An integrated photonics engine for unsupervised correlation detection.

With more and more aspects of modern life and scientific tools becoming digitized, the amount of data being generated is growing exponentially. Fast and efficient statistical processing, such as identifying correlations in big datasets, is therefore becoming increasingly important, and this, on account of the various compute bottlenecks in modern digital machines, has necessitated new computational paradigms. Here, we demonstrate one such novel paradigm, via the development of an integrated phase-change photonics engine. The computational memory engine exploits the accumulative property of Ge2Sb2Te5 phase-change cells and wavelength division multiplexing property of optics in delivering fully parallelized and colocated temporal correlation detection computations. We investigate this property and present an experimental demonstration of identifying real-time correlations in data streams on the social media platform Twitter and high-traffic computing nodes in data centers. Our results demonstrate the use case of high-speed integrated photonics in accelerating statistical analysis methods.

Electronically Reconfigurable Photonic Switches Incorporating Plasmonic Structures and Phase Change Materials.

The ever-increasing demands for data processing and storage will require seamless monolithic co-integration of electronics and photonics. Phase-change materials are uniquely suited to fulfill this function due to their dual electro-optical sensitivity, nonvolatile retention properties, and fast switching dynamics. The extreme size disparity however between CMOS electronics and dielectric photonics inhibits the realization of efficient and compact electrically driven photonic switches, logic and routing elements. Here, the authors achieve an important milestone in harmonizing the two domains by demonstrating an electrically reconfigurable, ultra-compact and nonvolatile memory that is optically accessible. The platform relies on localized heat, generated within a plasmonic structure; this uniquely allows for both optical and electrical readout signals to be interlocked with the material state of the PCM while still ensuring that the writing operation is electrically decoupled. Importantly, by miniaturization and effective thermal engineering, the authors achieve unprecedented energy efficiency, opening up a path towards low-energy optoelectronic hardware for neuromorphic and in-memory computing.

Stabilizing the West Antarctic Ice Sheet by surface mass deposition.

There is evidence that a self-sustaining ice discharge from the West Antarctic Ice Sheet (WAIS) has started, potentially leading to its disintegration. The associated sea level rise of more than 3m would pose a serious challenge to highly populated areas including metropolises such as Calcutta, Shanghai, New York City, and Tokyo. Here, we show that the WAIS may be stabilized through mass deposition in coastal regions around Pine Island and Thwaites glaciers. In our numerical simulations, a minimum of 7400 Gt of additional snowfall stabilizes the flow if applied over a short period of 10 years onto the region (-2 mm year-1 sea level equivalent). Mass deposition at a lower rate increases the intervention time and the required total amount of snow. We find that the precise conditions of such an operation are crucial, and potential benefits need to be weighed against environmental hazards, future risks, and enormous technical challenges.