101 citations
- Peking UniversityCN113 papers
- Chinese Academy of SciencesCN25 papers
- University of Chinese Academy of SciencesCN18 papers
- National Astronomical ObservatoriesCN15 papers
- Astronomy and SpaceAU12 papers
- Shanghai Jiao Tong UniversityCN12 papers
- Centre National de la Recherche ScientifiqueFR11 papers
- Collaborative Innovation Center of Quantum MatterCN11 papers
- University of ChicagoUS10 papers
- Sorbonne UniversitéFR9 papers
- The University of TokyoJP9 papers
- University of ArizonaUS9 papers
16 papers · 1 filter
Empirical Near-Infrared Spectral Templates from SPHEREx: Disentangling AGN and Host-Galaxy Emission
Wenke Ren, Hengxiao Guo, Zhenya Zheng +9
SPHEREx conducts the first all-sky near-infrared spectral survey over 0.75-5.0 m, spanning the transition from host-galaxy starlight to AGN-heated torus emission and enabling sp…
Detection of a parsec-scale, compact, and fading ejecta from an accreting massive black hole
Chao Li, Ning Chang, Jun Yang +2
Dwarf galaxies, characterized by their low luminosities and masses, are excellent candidates for searches for intermediate-mass black holes (IMBHs), particularly when they show str…
Great Disappearance Acts Generative Search and Shadow Banning
Danny Friedmann
The internet, once celebrated as a decentralized public sphere, is increasingly undermined by practices such as generative search and shadow banning, which divert traffic and suppr…
Translating Spin-Adapted RPA to Spin-Adapted TDDFT
Xiaoyu Zhang, Tai Wang
Linear-response TDDFT based on open-shell references may produce spin-mixed excited states, particularly when the response space is not spin complete. Spin-adapted RPA was develope…
Full-polarization millimeter wavelength variability of Sagittarius A* during the 2018 EHT campaign
Ezequiel Albentosa-Ruiz, Jasmin E. Washington, Nicola Marchili +272
Sagittarius A* (Srg A*), the supermassive black hole at the center of the Milky Way, provides a unique laboratory to study accretion dynamics and plasma processes near the event ho…
GemS-T: Multi-Dimensional Grouping for Ultra-High Energy Efficiency in Spiking Transformer
Zecheng Hao, Shenghao Xie, Kang Chen +3
Spiking Neural Networks (SNNs) offer superior energy efficiency over Artificial Neural Networks (ANNs). However, they encounter significant deficiencies in training and inference m…