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Many-body interactions are essential for understanding non-linear optics and ultrafast spectroscopy of materials. Recent first principles approaches based on nonequilibrium Green’s function formalisms, such as the time-dependent adiabatic GW (TD-aGW) approach, can predict nonequilibrium dynamics of excited states including electron-hole interactions. However, the high-dimensionality of the electron-hole kernel poses significant computational challenges. Here, we develop a data-driven low-rank approximation for the electron-hole kernel, leveraging localized excitonic effects in the Hilbert space of crystalline systems to achieve significant data compression through singular value decomposition (SVD). We show that the subspace of non-zero singular values remains small even as the k-grid grows, ensuring computational tractability with extremely dense k-grids. This low-rank property enables at least 95% data compression and an order-of-magnitude speedup of TD-aGW calculations. Our approach avoids intensive training processes and eliminates time-accumulated errors, seen in previous approaches, providing a general framework for high-throughput, nonequilibrium simulation of light-driven dynamics in materials. 

A critical use case of SLAM for mobile robots is to support localization during task-directed navigation. Current SLAM benchmarks overlook the importance of repeatability (precision) despite its impact on real-world deployments. TaskSLAM-Bench, a task-driven approach to SLAM benchmarking, addresses this gap. It employs precision as a key metric, accounts for SLAM’s mapping capabilities, and has easy-to-meet requirements. Simulated and real-world evaluation of SLAM methods provide insights into the navigation performance of modern visual and LiDAR SLAM solutions. The outcomes show that passive stereo SLAM precision may match that of 2D LiDAR SLAM in indoor environments. TaskSLAM-Bench complements existing benchmarks and offers richer assessment of SLAM performance in navigation-focused scenarios. Publicly available code permits in-situ SLAM testing in custom environments with properly equipped robots. 

Abstract Horizontal transfer of genetic material in eukaryotes has rarely been documented over short evolutionary timescales. Here, we show that two retrotransposons,ShellderandSpoink, invaded the genomes of multiple species of themelanogastersubgroup within the last 50 years. Through horizontal transfer,Spoinkspread inD. melanogasterduring the 1980s, while bothShellderandSpoinkinvadedD. simulansin the 1990s. Possibly following hybridization,D. simulansinfected the island endemic speciesD. mauritiana(Mauritius) andD. sechellia(Seychelles) with both TEs after 1995. In the same approximate time-frame,Shellderalso invadedD. teissieri, a species confined to sub-Saharan Africa. We find that the donors ofShellderandSpoinkare likely AmericanDrosophilaspecies from thewillistoni,cardini, andrepletagroups. Thus, the described cascade of TE invasions could only become feasible afterD. melanogasterandD. simulansextended their distributions into the Americas 200 years ago, likely aided by human activity. Our work reveals that cascades of TE invasions, likely initiated by human-mediated range expansions, could have an impact on the genomic and phenotypic evolution of geographically dispersed species. Within a few decades, TEs could invade many species, including island endemics, with distributions very distant from the donor of the TE. 

Abstract Trait-based approaches are revolutionizing our understanding of high-diversity ecosystems by providing insights into the principles underlying key ecological processes, such as community assembly, species distribution, resilience, and the relationship between biodiversity and ecosystem functioning. In 2016, the Coral Trait Database advanced coral reef science by centralizing trait information for stony corals (i.e., Subphylum Anthozoa, Class Hexacorallia, Order Scleractinia). However, the absence of trait data for soft corals, gorgonians, and sea pens (i.e., Class Octocorallia) limits our understanding of ecosystems where these organisms are significant members and play pivotal roles. To address this gap, we introduce the Octocoral Trait Database, a global, open-source database of curated trait data for octocorals. This database houses species- and individual-level data, complemented by contextual information that provides a relevant framework for analyses. The inaugural dataset, OctocoralTraits v2.2, contains over 97,500 global trait observations across 98 traits and over 3,500 species. The database aims to evolve into a steadily growing, community-led resource that advances future marine science, with a particular emphasis on coral reef research.