科学研究
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2024.12.24
Uncovering Early Galaxy Formation with JWST: A Modeling Perspective
The James Webb Space Telescope (JWST) is transforming our understanding on galaxy formation and evolution, revealing distant galaxies deep into the epoch of reionization and uncovering red sources that were simply unknown pre-JWST. In this talk, I will discuss two key areas, with a focus on the challenges in modeling the spectral energy distributions in the JWST era. First, a central science go...
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2024.12.20
TOI-880 Has An Aligned, Coplanar Multi-planet System [EN]
We present the stellar obliquity measurement of TOI-880 c (TOI-880.01) using Rossiter-McLaughlin (RM) observations obtained with the Keck Planet Finder (KPF). TOI-880 is a compact multi-transiting system with 3 transiting planets. Our independent analysis revealed that the host star is a K-type star. Planet b (TOI-880.02) has a radius of 2.23 ± 0.10R⊕ and an orbital period of 2.6 days; planet ...
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2024.12.19
Magnetospheric Radio Emissions: from Jupiter to exoplanets and stars [EN]
Jupiter's radio emissions have been intensively studied since their discovery some 70 years ago. Space missions have extended these studies to radio emissions from all planetary magnetospheres in the solar system. Main emission characteristics have been determined (source location, directivity, power, polarization, etc.) and their microscopic generation process elucidated (primarily the electro...
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2024.12.13
A potential mass-gap black hole in a wide binary with a circular orbit
The mass distribution of black holes identified through X-ray emission suggests a paucity of black holes in the mass range of 3 to 5 solar masses. Modified theories have been devised to explain this mass gap, and it is suggested that natal kicks during a supernova explosion can more easily disrupt binaries with lower-mass black holes. Although recent Laser Interferometer Gravitational-Wave Obse...
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2024.12.12
Trust me, I am an Astrophysics Foundation Model [EN]
As datasets continue to grow, machine learning/artificial intelligence (ML/AI) has taken on an increasingly large role in scientific analyses as both a practical necessity (to handle the data volumes) but also as a way to "bypass" theoretical models by learning directly from the data. However, this speed, complexity, and flexibility also have proved to be one of the main challenges involved in ...
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