Connection between galaxy morphology and dark-matter halo structure I: a running threshold for thin discs and size predictors from the dark sector

Kavli Affiliate: Luis C. Ho | First 5 Authors: Jinning Liang, Fangzhou Jiang, Houjun Mo, Andrew Benson, Avishai Dekel | Summary: We present a series of studies on the connection between galaxy morphology and the structure of host dark-matter (DM) haloes using cosmological simulations. In this work, we introduce a new kinematic decomposition scheme that […]


Continue.. Connection between galaxy morphology and dark-matter halo structure I: a running threshold for thin discs and size predictors from the dark sector

Empowering Segmentation Ability to Multi-modal Large Language Models

Kavli Affiliate: Jing Wang | First 5 Authors: Yuqi Yang, Peng-Tao Jiang, Jing Wang, Hao Zhang, Kai Zhao | Summary: Multi-modal large language models (MLLMs) can understand image-language prompts and demonstrate impressive reasoning ability. In this paper, we extend MLLMs’ output by empowering MLLMs with the segmentation ability. The extended MLLMs can both output language […]


Continue.. Empowering Segmentation Ability to Multi-modal Large Language Models

Structure-preserving, weighted implicit-explicit schemes for multi-phase incompressible Navier-Stokes/Darcy coupled nonlocal Allen-Cahn model

Kavli Affiliate: Ke Wang | First 5 Authors: Meng Li, Ke Wang, Nan Wang, , | Summary: A multitude of substances exist as mixtures comprising multiple chemical components in the natural world. These substances undergo morphological changes under external influences. the phase field model coupled with fluid flow, the dynamic movement and evolution of the […]


Continue.. Structure-preserving, weighted implicit-explicit schemes for multi-phase incompressible Navier-Stokes/Darcy coupled nonlocal Allen-Cahn model

Mono- and oligochromatic extreme-mass ratio inspirals

Kavli Affiliate: Pau Amaro Seoane | First 5 Authors: Pau Amaro Seoane, Yiren Lin, Kostas Tzanavaris, , | Summary: The gravitational capture of a stellar-mass object by a supermassive black hole represents a unique probe of warped spacetime. The small object, typically a stellar-mass black hole, describes a very large number of cycles before crossing […]


Continue.. Mono- and oligochromatic extreme-mass ratio inspirals

Mono- and oligochromatic extreme-mass ratio inspirals

Kavli Affiliate: Pau Amaro Seoane | First 5 Authors: Pau Amaro Seoane, Yiren Lin, Kostas Tzanavaris, , | Summary: The gravitational capture of a stellar-mass object by a supermassive black hole represents a unique probe of warped spacetime. The small object, typically a stellar-mass black hole, describes a very large number of cycles before crossing […]


Continue.. Mono- and oligochromatic extreme-mass ratio inspirals

Neural Downscaling for Complex Systems: from Large-scale to Small-scale by Neural Operator

Kavli Affiliate: Jing Wang | First 5 Authors: Pengyu Lai, Jing Wang, Rui Wang, Dewu Yang, Haoqi Fei | Summary: Predicting and understanding the chaotic dynamics in complex systems is essential in various applications. However, conventional approaches, whether full-scale simulations or small-scale omissions, fail to offer a comprehensive solution. This instigates exploration into whether modeling […]


Continue.. Neural Downscaling for Complex Systems: from Large-scale to Small-scale by Neural Operator

Tell machine learning potentials what they are needed for: Simulation-oriented training exemplified for glycine

Kavli Affiliate: Ran Wang | First 5 Authors: Fuchun Ge, Ran Wang, Chen Qu, Peikun Zheng, Apurba Nandi | Summary: Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surface (PES) in many chemical simulations, e.g., geometry optimizations, frequency calculations, molecular dynamics, and Monte Carlo computations. However, there […]


Continue.. Tell machine learning potentials what they are needed for: Simulation-oriented training exemplified for glycine

Tell machine learning potentials what they are needed for: Simulation-oriented training exemplified for glycine

Kavli Affiliate: Ran Wang | First 5 Authors: Fuchun Ge, Ran Wang, Chen Qu, Peikun Zheng, Apurba Nandi | Summary: Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surfaces (PES) in many chemical simulations. The MLPs are often evaluated with the root-mean-square errors on the test set […]


Continue.. Tell machine learning potentials what they are needed for: Simulation-oriented training exemplified for glycine

Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

Kavli Affiliate: Li Xin Li | First 5 Authors: The LHAASO Collaboration, Zhen Cao, F. Aharonian, Q. An, A. Axikegu | Summary: We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, […]


Continue.. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

Tidal evolution of cored and cuspy dark matter halos

Xiaolong Du, Andrew Benson, Zhichao Carton Zeng, Tommaso Treu, Annika H. G. Peter | Summary: [[{“value”:”The internal structure and abundance of dark matter halos and subhalos are powerful probes of the nature of dark matter. In order to compare observations with dark matter models, accurate theoretical predictions of these quantities are needed. We present a […]


Continue.. Tidal evolution of cored and cuspy dark matter halos