Search for: All records

Large deployable mesh reflectors play a critical role in satellite communications, Earth observation, and deep-space exploration, offering high-gain antenna performance through precisely shaped reflective surfaces. Traditional dynamic modeling approaches—such as wave-based and finite element methods—often struggle to accurately capture the complex behavior of three-dimensional reflectors due to oversimplifications of cable members. To address these challenges, this paper proposes a novel spatial discretization framework that systematically decomposes cable member displacements into boundary-induced and internal components in a global Cartesian coordinate system. The framework derives a system of ordinary differential equations for each cable member by enforcing the Lagrange’s equations, capturing both longitudinal and transverse internal displacement of the cable member. Numerical simulations of a two-dimensional cable-network structure and a center-feed parabolic deployable mesh reflector with 101 nodes illustrate the improved accuracy of the proposed method in predicting vibration characteristics across a broad frequency range. Compared to standard finite element analysis, the proposed method more effectively identifies both low- and high-frequency modes and offers robust convergence and accurate prediction for both frequency and transient responses of the structure. This enhanced predictive capability underscores the significance of incorporating internal cable member displacements for reliable dynamic modeling of large deployable mesh reflectors, ultimately informing better design, control, and on-orbit performance of future space-based reflector systems. 

Operators of web archives have two options for how to crawl pages from the web. Browser-based dynamic crawlers capture all of the resources on every page, but incur high compute overheads. Static browserless crawlers are more lightweight, but miss page resources which are fetched only when scripts are executed. In this paper, we make the case that a web archive does not have to make a binary choice between dynamic or static crawling. Instead, by using a browser for a carefully chosen small subset of crawls, an archive can significantly improve its ability to serve statically crawled pages with high fidelity. First, we show how to reuse crawled resources, both across pages and across multiple crawls of the same page over time. Second, by leveraging a dynamic crawl of a page, we show that subsequent static crawls of the page can be augmented to fetch resources without executing the scripts which request them. We estimate that, as long as 8.9% of page crawls use a browser, an archive can serve roughly 99% of the remaining statically crawled pages without any loss in fidelity, up from 55% without our techniques. 

Abstract This study examines December-January-February (DJF) soil moisture responses to multi-year (MY) and single-year (SY) La Niñas using a 2200-year CESM1 simulation, AGCM experiments, and observational data. Four regions where MY La Niñas amplify SY La Niñas’ impacts on soil moisture were identified: North America, Australia, the Middle East, and the Sahel. SY La Niñas typically cause soil moisture drying in the Middle East and North America and wetting in Australia and the Sahel. MY La Niñas enhance these effects in the second DJF due to the strengthening of precipitation anomalies or the accumulation of precipitation-induced soil moisture anomalies, except in the Sahel where wetting is driven in part by evapotranspiration anomalies. Soil moisture variations are linked to La Niña-induced sea surface temperature changes in the Indian Ocean (for Australia and the Middle East) and the Pacific Ocean (for North America). These amplified effects are largely supported by the observed MY La Niña events from 1948 to 2022. These findings emphasize the need to integrate MY La Niñas into regional agriculture and water resource management strategies to better anticipate and mitigate their impacts. 

Accepted by Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). 

Abstract The remarkable complexity of a topologically ordered many-body quantum system is encoded in the characteristics of its anyons. Quintessential predictions emanating from this complexity employ the Fibonacci string net condensate (Fib SNC) and its anyons: sampling Fib-SNC would estimate chromatic polynomials while exchanging its anyons would implement universal quantum computation. However, physical realizations remained elusive. We introduce a scalable dynamical string net preparation (DSNP) that constructs Fib SNC and its anyons on reconfigurable graphs suitable for near-term superconducting processors. Coupling the DSNP approach with composite error-mitigation on deep circuits, we create, measure, and braids Fibonacci anyons; charge measurements show 94% accuracy, and exchanging the anyons yields the expected golden ratioϕwith 98% average accuracy. We then sample the Fib SNC to estimate chromatic polynomial atϕ + 2 for several graphs. Our results establish the proof of principle for using Fib-SNC and its anyons for fault-tolerant universal quantum computation and aim at a classically hard problem.