Evolution and distribution of superbubbles in simulated Milky Way-like galaxies

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Chengzhe Li, Hui Li, Wei Cui, Federico Marinacci, Laura V. Sales | Summary: Stellar feedback plays a crucial role in regulating baryon cycles of a galactic ecosystem, and may manifest itself in the formation of superbubbles in the interstellar medium. In this work, we used a set […]


Continue.. Evolution and distribution of superbubbles in simulated Milky Way-like galaxies

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

Antiferromagnetic Ground State, Charge Density Waves and Oxygen Vacancies Induced Metal-Insulator Transition in Pressurized La$_{3}$Ni$_{2}$O$_{7}$

Kavli Affiliate: Gang Su | First 5 Authors: Xin-Wei Yi, Ying Meng, Jia-Wen Li, Zheng-Wei Liao, Jing-Yang You | Summary: La$_{3}$Ni$_{2}$O$_{7}$ has garnered widespread interest recently due to its high-temperature superconductivity under pressure, accompanied by charge density wave (CDW) ordering and metal-insulator (MI) transitions in the phase diagram. Here, we reveal with comprehensive calculations that […]


Continue.. Antiferromagnetic Ground State, Charge Density Waves and Oxygen Vacancies Induced Metal-Insulator Transition in Pressurized La$_{3}$Ni$_{2}$O$_{7}$

Representing the dynamics of natural marmoset vocal behaviors in frontal cortex

Kavli Affiliate: Cory Miller | Authors: Jingwen Li, Mikio Christian Aoi and Cory Miller | Summary: Here we tested the respective contributions of primate premotor and prefrontal cortex to support vocal behavior. We applied a model-based GLM analysis that better accounts for the inherent variance in natural, continuous behaviors to characterize the activity of neurons […]


Continue.. Representing the dynamics of natural marmoset vocal behaviors in frontal cortex

Social state gates vision using three circuit mechanisms in Drosophila

Kavli Affiliate: Vanessa Ruta | Authors: Catherine E. Schretter, Tom Hindmarsh Sten, Nathan Klapoetke, Mei Shao, Aljoscha Nern, Marisa Dreher, Daniel Bushey, Alice A. Robie, Adam L. Taylor, Kristin M. Branson, Adriane Otopalik, Vanessa Ruta and Gerald M. Rubin | Summary: Animals are often bombarded with visual information and must prioritize specific visual features based […]


Continue.. Social state gates vision using three circuit mechanisms in Drosophila

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

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

Electrically controlled nonvolatile switching of single-atom magnetism in a Dy@C84 single-molecule transistor

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Wangqiang Shen, Yuan Shui, Jun Chen, Huaiqiang Wang | Summary: Single-atom magnetism switching is a key technique towards the ultimate data storage density of computer hard disks and has been conceptually realized by leveraging the spin bistability of a magnetic atom under a scanning tunnelling […]


Continue.. Electrically controlled nonvolatile switching of single-atom magnetism in a Dy@C84 single-molecule transistor