Marcin Pilinski | Searcharxiv

arXiv2026

ECLIPSE: An Evolutionary Computation Library for Instrumentation Prototyping in Scientific Engineering

Designing scientific instrumentation often requires exploring large, highly constrained design spaces using computationally expensive physics simulations. These simulators pose substantial challenges for integrating evolutionary computation (EC) into scientific design workflows. EC typically requires numerous design evaluations, making the integration of slow, low-throughput simulators challenging, as they are optimized for accuracy and ease of use rather than throughput. We present ECLIPSE, an evolutionary computation framework built to interface directly with complex, domain-specific simulation tools while supporting flexible geometric and parametric representations of scientific hardware. ECLIPSE provides a modular architecture consisting of (1) Individuals, which encode hardware designs using domain-aware, physically constrained representations; (2) Evaluators, which prepare simulation inputs, invoke external simulators, and translate the simulator's outputs into fitness measures; and (3) Evolvers, which implement EC algorithms suitable for this domain. We evolve solutions for two novel space-science applications: 3D antennas optimized for directional sensitivity and spacecraft geometries optimized for drag reduction. Notably, we identify antennas with directional sensitivity roughly comparable to the expected sensitivity of two-antenna interferometric arrays, representing potential cost-savings. ECLIPSE enables interdisciplinary teams of physicists, engineers, and EC researchers to collaboratively explore designs for scientific hardware while leveraging existing domain-specific simulation software.

cs.NE↗

arXiv2025

Thermospheric Density, Composition, and Temperature from GOES-R/SUVI Solar Occultations

A new dataset of atomic oxygen and molecular nitrogen number density profiles, along with thermospheric temperature profiles between 180 and 500 km, has been developed. These profiles are derived from solar occultation measurements made by SUVI on the GOES-R satellites, using the 17.1, 19.5, and 30.4 nm channels. Discussed is the novel approach and methods for using EUV solar occultation images to measuring the thermospheric state. Measurement uncertainties are presented as a function of tangent altitude. At 250 km, number density random uncertainties are found to be 8% and 17% for O and N2, respectively, and the random uncertainty for neutral temperature at 250 km was found to be 3%. The impact of effective cross section uncertainty on retrieval bias was assessed, revealing that, as expected, the largest effects occur where O and N2 are minor absorbers. In contrast, total mass density and O/N2 ratios exhibit substantially lower sensitivity, with biases that remain small or nearly constant with altitude. Total mass density comparisons with the MSIS model show good agreement at the dusk terminator, with an average difference of -2%, but larger discrepancies at dawn, with an average difference of -26%. These discrepancies are more prominent during quiet solar conditions, suggesting an overestimation of densities by MSIS during these conditions. Density comparisons with the IDEA and Dragster assimilative models show dawn/dusk percent differences of -24%/-2% and +2%/+13%, respectively. The dataset is available through the NOAA GOES-R L2 pipeline for eclipse seasons from Sept. 2018 onward and is expected to continue through 2035. As this measurement relies only on real-time NOAA space weather SUVI images, these profiles could be produced in real-time, supporting critical space weather monitoring and prediction, and filling in a current measurement gap of thermospheric temperature and density.

astro-ph.EP↗