The AGORA High-Resolution Galaxy Simulations Comparison Project VII: Satellite quenching in zoom-in simulation of a Milky Way-mass halo

Kavli Affiliate: Tom Abel | First 5 Authors: R. Rodríguez-Cardoso, S. Roca-Fàbrega, Minyong Jung, Thinh Huu Nguyen, Ji-hoon Kim | Summary: Context: Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group (LG), satellite quenching has been shown to be highly […]


Continue.. The AGORA High-Resolution Galaxy Simulations Comparison Project VII: Satellite quenching in zoom-in simulation of a Milky Way-mass halo

The AGORA High-Resolution Galaxy Simulations Comparison Project VII: Satellite quenching in zoom-in simulation of a Milky Way-mass halo

Kavli Affiliate: Tom Abel | First 5 Authors: R. Rodríguez-Cardoso, S. Roca-Fàbrega, Minyong Jung, Thinh H. Nguyen, Ji-hoon Kim | Summary: Context: Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group (LG), satellite quenching has been shown to be highly […]


Continue.. The AGORA High-Resolution Galaxy Simulations Comparison Project VII: Satellite quenching in zoom-in simulation of a Milky Way-mass halo

The {it AGORA} High-resolution Galaxy Simulations Comparison Project. VIII: Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at $1<z<5$

Kavli Affiliate: Tom Abel | First 5 Authors: Minyong Jung, Ji-hoon Kim, Thinh H. Nguyen, Ramon Rodriguez-Cardoso, Santi Roca-Fàbrega | Summary: We investigate how differences in the stellar feedback produce disks with different morphologies in Milky Way-like progenitors over 1 $leq z leq 5$, using eight state-of-the-art cosmological hydrodynamics simulation codes in the textit{AGORA} project. […]


Continue.. The {it AGORA} High-resolution Galaxy Simulations Comparison Project. VIII: Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at $1<z<5$

The {it AGORA} High-resolution Galaxy Simulations Comparison Project. VIII: Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at $1<z<5$

Kavli Affiliate: Tom Abel | First 5 Authors: Minyong Jung, Ji-hoon Kim, Thinh H. Nguyen, Ramon Rodriguez-Cardoso, Santi Roca-Fàbrega | Summary: We investigate how differences in the stellar feedback produce disks with different morphologies in Milky Way-like progenitors over 1 $leq z leq 5$, using eight state-of-the-art cosmological hydrodynamics simulation codes in the textit{AGORA} project. […]


Continue.. The {it AGORA} High-resolution Galaxy Simulations Comparison Project. VIII: Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at $1<z<5$

OTI on FIRE: Testing the Efficacy of Orbital Torus Imaging to Recover the Galactic Potential

Kavli Affiliate: Lina Necib | First 5 Authors: Micah Oeur, Sarah R. Loebman, Adrian M. Price-Whelan, Arpit Arora, Lina Necib | Summary: Orbital Torus Imaging (OTI) is a dynamical inference method for determining the Milky Way’s gravitational potential using stellar survey data. OTI uses gradients in stellar astrophysical quantities, such as element abundances, as functions […]


Continue.. OTI on FIRE: Testing the Efficacy of Orbital Torus Imaging to Recover the Galactic Potential

The THESAN-ZOOM project: Star formation efficiency from giant molecular clouds to galactic scale in high-redshift starbursts

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Zihao Wang, Xuejian Shen, Mark Vogelsberger, Hui Li, Rahul Kannan | Summary: Star formation in galaxies is inherently complex, involving the interplay of physical processes over a hierarchy of spatial scales. In this work, we investigate the connection between global (galaxy-scale) and local (cloud-scale) star formation efficiencies […]


Continue.. The THESAN-ZOOM project: Star formation efficiency from giant molecular clouds to galactic scale in high-redshift starbursts

The Emergence of Little Red Dots from Binary Massive Black Holes

Kavli Affiliate: Xian Chen | First 5 Authors: Kohei Inayoshi, Jinyi Shangguan, Xian Chen, Luis C. Ho, Zoltan Haiman | Summary: Little red dots (LRDs) are a newly identified class of broad-line active galactic nuclei (AGN) with a distinctive v-shape spectrum characterized by red optical and blue UV continuum emission. Their high abundance at redshifts […]


Continue.. The Emergence of Little Red Dots from Binary Massive Black Holes

KMT-2022-BLG-1818Lb,c: A Cold Super-Jupiter with a Saturn Sibling

Kavli Affiliate: Subo Dong | First 5 Authors: Hongyu Li, Jiyuan Zhang, Cheongho Han, Weicheng Zang, Youn Kil Jung | Summary: We present the discovery and analysis of the sixth microlensing two-planet system, KMT-2022-BLG-1818Lb,c, detected by a follow-up program targeting high-magnification events. Both planets are subject to the well-known ”Close/Wide” degeneracy, although for the first […]


Continue.. KMT-2022-BLG-1818Lb,c: A Cold Super-Jupiter with a Saturn Sibling

KMT-2022-BLG-1818Lb,c: A Cold Super-Jupiter with a Saturn Sibling

Kavli Affiliate: Subo Dong | First 5 Authors: Hongyu Li, Jiyuan Zhang, Cheongho Han, Weicheng Zang, Youn Kil Jung | Summary: We present the discovery and analysis of the sixth microlensing two-planet system, KMT-2022-BLG-1818Lb,c, detected by a follow-up program targeting high-magnification events. Both planets are subject to the well-known ”Close/Wide” degeneracy, although for the first […]


Continue.. KMT-2022-BLG-1818Lb,c: A Cold Super-Jupiter with a Saturn Sibling

From First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation

Kavli Affiliate: Xian Chen | First 5 Authors: Jie Cao, Chloe Qianhui Zhao, Xian Chen, Shuman Wang, Christian Schunn | Summary: Producing large volumes of high-quality, timely feedback poses significant challenges to instructors. To address this issue, automation technologies-particularly Large Language Models (LLMs)-show great potential. However, current LLM-based research still shows room for improvement in […]


Continue.. From First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation