科学研究
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2023.08.16
Simulating the first stars, galaxies, and black holes in the Universe
Prof. John Wise from Georgia Tech and the director at the Center for Relativistic Astrophysics (CRA)Host: Song Huan
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2023.08.15
Dynamics of Transneptunian Objects under the Influence of a Rogue Planet (Thesis Talk) 海王星外天体在流浪行星影响下的动力学
Over the past two decades, our knowledge of the Solar System’s transneptunian region (often called the Kuiper Belt) has been gradually increasing. Observational surveys have greatly expanded the inventory of Trans-Neptunian Objects (TNOs), which are distant icy bodies thought to be relics from the giant planet formation era.In the distant Kuiper Belt, several striking features seem to challeng...
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2023.08.14
Inferred stellar parameters from 220 million XP spectra using an empirical forward model
Gaia data release 3 (GDR3) provides a trove of 220 million low-resolution BP/RP (XP) fluxcalibrated spectra. In order to properly exploit the XP spectra, we need to accurately model them as a function of stellar type, extinction and distance. We build a machine-learning model based on the subset of XP stars with LAMOST LRS counterparts, whose stellar types are precisely determined by the higher...
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2023.08.11
KiDS-1000: Cosmology with improved cosmic shear measurements
Weak gravitational lensing by large-scale structure, also known as cosmic shear, plays a crucial role in modern cosmology, powerfully probing the Universe's matter distribution. Interestingly, recent cosmic shear results from the KiDS, DES, and HSC surveys show an intriguing discrepancy with Planck's CMB observations concerning the amplitude of matter fluctuations. In this talk, I will discuss ...
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2023.07.28
Towards Optimal Inference of Cosmological Large Scale Structures with Neural Quantile Estimation
Traditional analysis of cosmological Large Scale Structures assumes that the likelihood is Gaussian, which unfortunately is not optimal and may even be biased in the non linear regime. Simulation Based Inference (SBI), also known as Likelihood Free Inference or Implicit Likelihood Inference, directly models the Bayesian optimal posterior, but typically needs a large number of simulations to con...
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