egg changed the topic of #kspacademia to: https://git.io/JqLs2 | Dogs are cats. Spiders are cat interferometers. | Document well, for tomorrow you may get mauled by a ネコバス. | <UmbralRaptor> egg|nomz|egg: generally if your eyes are dewing over, that's not the weather. | <ferram4> I shall beat my problems to death with an engineer. | We can haz pdf | Logs: https://esper.irclog.whitequark.org/kspacademia
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<raptop> astronomers naming things: https://arxiv.org/abs/2410.18941
<galois> [arXiv] “PRODIGE -- envelope to disk with NOEMA. IV. An infalling gas bridge surrounding two Class 0/I systems in L1448N” C. Gieser, J. E. Pineda, D. M. Segura-Cox et al. — «Context. The formation of stars has been subject to extensive studies in the past decades from molecular cloud to protoplanetary disk scales. It is still not fully understood how the surrounding material in a protostellar system, that often shows asymmetric…»
<raptop> astronomers naming things: https://arxiv.org/abs/2410.18154
<galois> [arXiv] “A measurement of atmospheric circular polarization with POLARBEAR” Takuro Fujino, Satoru Takakura, Shahed Shayan Arani et al. — «At millimeter wavelengths, the atmospheric emission is circularly polarized owing to the Zeeman splitting of molecular oxygen by the Earth's magnetic field. We report a measurement of the signal in the 150 GHz band using 3 years of observations of the \textsc{Polarbear} project. Although the…»
<galois> [url] POSEIDON’s documentation — POSEIDON 2024 documentation | poseidon-retrievals.readthedocs.io
<galois> [arXiv] “POSEIDON: A Multidimensional Atmospheric Retrieval Code for Exoplanet Spectra” Ryan J. MacDonald — «Spectroscopic observations of exoplanet atmospheres can reveal the chemical composition, temperature, cloud properties, and (potentially) the habitability of these distant worlds. The inference of such properties is generally enabled by Bayesian atmospheric retrieval algorithms. However, until recently, many retrieval…»
<raptop> astronomers naming things: https://arxiv.org/abs/2410.18875
<galois> [arXiv] “Exploring the Universe with SNAD: Anomaly Detection in Astronomy” Alina A. Volnova, Patrick D. Aleo, Anastasia Lavrukhina et al. — «SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and classification of various astronomical…»
<raptop> astronomers naming things: https://arxiv.org/abs/2410.18899
<galois> [arXiv] “SKATR: A Self-Supervised Summary Transformer for SKA” Ayodele Ore, Caroline Heneka, Tilman Plehn — «The Square Kilometer Array will initiate a new era of radio astronomy by allowing 3D imaging of the Universe during Cosmic Dawn and Reionization. Modern machine learning is crucial to analyse the highly structured and complex signal. However, accurate training data is expensive to simulate, and supervised learning may not…»
<raptop> astronomers naming things: https://arxiv.org/abs/2410.18549
<galois> [arXiv] “Estimating early coronal mass ejection propagation direction with DIRECD during the severe May 8 and follow-up June 8, 2024 events” Shantanu Jain, Tatiana Podladchikova, Astrid M. Veronig et al. — «On May 8, 2024, solar active region 13664 produced an X-class flare, several M-class flares, and multiple Earth-directed Coronal Mass Ejections (CMEs). The initial CME caused coronal dimmings, characterized by localized…»
<raptop> astronomers naming things: https://arxiv.org/abs/2410.18562
<galois> [arXiv] “Prediction of Large Solar Flares Based on SHARP and HED Magnetic Field Parameters” Xuebao Li, Xuefeng Li, Yanfang Zheng et al. — «The existing flare prediction primarily relies on photospheric magnetic field parameters from the entire active region (AR), such as Space-Weather HMI Activity Region Patches (SHARP) parameters. However, these parameters may not capture the details the AR evolution preceding flares. The…»
<raptop> !meow
<galois> 喵
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