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The stability of the West Antarctic Ice Sheet (WAIS), crucial for predicting future sea-level rise, is threatened by ocean-forced melting in the Pacific sector of the Southern Ocean. While some geological records and ice-sheet models suggest WAIS retreat during past warm periods, reliable data constraining the extent of retreat are lacking. Detrital Nd, Sr, and Pb isotope data of sediments recently drilled at International Ocean Discovery Program (IODP) Site U1532 on the Amundsen Sea continental rise manifest repeated alternations in sediment provenance during glacial–interglacial cycles of the Pliocene (5.33 to 2.58 Mya), a time warmer than present. The variations reflect large fluctuations in WAIS extent on the Antarctic continent. A unique high Pb/low ε_Ndsignature of sediments found at the onset of glacial intervals (3.88, 3.6, and 3.33 Ma) is attributed to the supply of detritus sourced from plutonic rocks located in the West Antarctic interior. Its isotopic signature at Site U1532 indicates major inland retreat of the WAIS during the preceding interglacials. During peak interglacials, the ice margin had retreated inland, and icebergs rafted and deposited inland-sourced detritus over 500 km across the Amundsen Sea shelf. Subsequent readvance of grounded ice then “bulldozed” these inland-derived fine-grained sediments from the shelf down to the continental slope and rise, resulting in a high Pb/low ε_Ndpeak in the rise sediments. Our continuous Pliocene records provide conclusive evidence for at least five major inland retreat events of the WAIS, highlighting the significant vulnerability of the WAIS to ongoing warming. 

We present high-resolution, high-speed fluorescence lifetime imaging microscopy (FLIM) of live cells based on a compressed sensing scheme. By leveraging the compressibility of biological scenes in a specific domain, we simultaneously record the time-lapse fluorescence decay upon pulsed laser excitation within a large field of view. The resultant system, referred to as compressed FLIM, can acquire a widefield fluorescence lifetime image within a single camera exposure, eliminating the motion artifact and minimizing the photobleaching and phototoxicity. The imaging speed, limited only by the readout speed of the camera, is up to 100 Hz. We demonstrated the utility of compressed FLIM in imaging various transient dynamics at the microscopic scale. 

Compressed ultrafast photography (CUP) is a computational optical imaging technique that can capture transient dynamics at an unprecedented speed. Currently, the image reconstruction of CUP relies on iterative algorithms, which are time-consuming and often yield nonoptimal image quality. To solve this problem, we develop a deep-learning-based method for CUP reconstruction that substantially improves the image quality and reconstruction speed. A key innovation toward efficient deep learning reconstruction of a large three-dimensional (3D) event datacube ( $x,y,t$) ( $x,y$, spatial coordinate; $t$, time) is that we decompose the original datacube into massively parallel two-dimensional (2D) imaging subproblems, which are much simpler to solve by a deep neural network. We validated our approach on simulated and experimental data. 

Abstract Multidimensional photography can capture optical fields beyond the capability of conventional image sensors that measure only two-dimensional (2D) spatial distribution of light. By mapping a high-dimensional datacube of incident light onto a 2D image sensor, multidimensional photography resolves the scene along with other information dimensions, such as wavelength and time. However, the application of current multidimensional imagers is fundamentally restricted by their static optical architectures and measurement schemes—the mapping relation between the light datacube voxels and image sensor pixels is fixed. To overcome this limitation, we propose tunable multidimensional photography through active optical mapping. A high-resolution spatial light modulator, referred to as an active optical mapper, permutes and maps the light datacube voxels onto sensor pixels in an arbitrary and programmed manner. The resultant system can readily adapt the acquisition scheme to the scene, thereby maximising the measurement flexibility. Through active optical mapping, we demonstrate our approach in two niche implementations: hyperspectral imaging and ultrafast imaging.