Extracting Multimodal Learngene in CLIP: Unveiling the Multimodal Generalizable Knowledge

Kavli Affiliate: Jing Wang | First 5 Authors: Ruiming Chen, Junming Yang, Shiyu Xia, Xu Yang, Jing Wang | Summary: CLIP (Contrastive Language-Image Pre-training) has attracted widespread attention for its multimodal generalizable knowledge, which is significant for downstream tasks. However, the computational overhead of a large number of parameters and large-scale pre-training poses challenges of […]


Continue.. Extracting Multimodal Learngene in CLIP: Unveiling the Multimodal Generalizable Knowledge

Overmassive Black holes live in compact galaxies in the early Universe

Kavli Affiliate: Ran Wang | First 5 Authors: Yuxuan Wu, Tao Wang, Daizhong Liu, Qinghua Tan, Luis C. Ho | Summary: A significant population of quasars have been found to exist within the first Gyr of cosmic time. Most of them have high black hole (BH) masses ($M_{rm BH} sim 10^{8-10} M_{odot}$) with an elevated […]


Continue.. Overmassive Black holes live in compact galaxies in the early Universe

The ASAS-SN Low Surface Brightness Survey I: Proof-of-Concept and Potential Applications

Kavli Affiliate: Subo Dong | Summary:The ASAS-SN Low Surface Brightness Survey utilizes the $sim7$ years of g-band CCD data from ASAS-SN (The All-Sky Automated Survey for Supernovae) to create stacked images of the entire sky. It is significantly deeper than previous photographic surveys. Our median/95th percentile cumulative exposure time per field is 58.1/86.8 hours, and […]


Continue.. The ASAS-SN Low Surface Brightness Survey I: Proof-of-Concept and Potential Applications

Anomalous Superfluid Density in Pair-Density-Wave Superconductors

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Qijin Chen, Rufus Boyack, K. Levin, | Summary: We study the superfluid density $n_s(T)$ of pair-density-wave (PDW) superconductors; this determines where they are unstable and establishes signatures of their unusual order. Here we compute $n_s(T)$ for the 2D unidirectional PDW superconducting phases that emerge from […]


Continue.. Anomalous Superfluid Density in Pair-Density-Wave Superconductors

Anomalous Superfluid Density in Pair-Density-Wave Superconductors

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Ke Wang, , , | Summary: Pair-density-wave (PDW) states — exotic superconductors with spatially modulated order — are a long-sought-after phase of quantum materials, with the potential to unravel the mysteries of high-$T_c$ cuprates and other strongly correlated superconductors. Yet, surprisingly, a key signature of […]


Continue.. Anomalous Superfluid Density in Pair-Density-Wave Superconductors

Acceleration and Collimation of the Two-Sided Jets in the Nearby Low-luminosity Active Galactic Nucleus NGC 4261 (3C 270)

Kavli Affiliate: Luis C. Ho | First 5 Authors: Xi Yan, Lang Cui, Kazuhiro Hada, Sandor Frey, Ru-sen Lu | Summary: We study the acceleration and collimation of the two-sided jets in the nearby low-luminosity active galactic nucleus NGC 4261 (3C 270) using archival multifrequency, multi-epoch Very Long Baseline Array data. By applying multiple analysis […]


Continue.. Acceleration and Collimation of the Two-Sided Jets in the Nearby Low-luminosity Active Galactic Nucleus NGC 4261 (3C 270)

Sub-Parsec Acceleration and Collimation of NGC 4261’s Twin Jets

Kavli Affiliate: Luis C. Ho | First 5 Authors: Xi Yan, Xi Yan, , , | Summary: We report the first robust evidence for a co-spatial sub-parsec acceleration and collimation zone (ACZ) in the twin jets of the nearby low-luminosity active galactic nucleus (LLAGN) NGC 4261. This result is derived from multifrequency Very Long Baseline […]


Continue.. Sub-Parsec Acceleration and Collimation of NGC 4261’s Twin Jets

FerroAI: A Deep Learning Model for Predicting Phase Diagrams of Ferroelectric Materials

Kavli Affiliate: Xian Chen | First 5 Authors: Chenbo Zhang, Xian Chen, , , | Summary: Composition-temperature phase diagrams are crucial for designing ferroelectric materials, however predicting them accurately remains challenging due to limited phase transformation data and the constraints of conventional methods. Here, we utilize natural language processing (NLP) to text-mine 41,597 research articles, […]


Continue.. FerroAI: A Deep Learning Model for Predicting Phase Diagrams of Ferroelectric Materials

Physics-informed Machine Learning Analysis for Nanoscale Grain Mapping by Synchrotron Laue Microdiffraction

Kavli Affiliate: Xian Chen | First 5 Authors: Ka Hung Chan, Xinyue Huang, Nobumichi Tamura, Xian Chen, | Summary: Understanding the grain morphology, orientation distribution, and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional materials. Synchrotron X-ray Laue microdiffraction is a powerful technique for characterizing crystal structures and […]


Continue.. Physics-informed Machine Learning Analysis for Nanoscale Grain Mapping by Synchrotron Laue Microdiffraction

A Metallicity Catalog of Very Metal-poor Main-sequence Turn-off and Red Giant Stars from LAMOST DR10

Kavli Affiliate: Huawei Zhang | Summary:We present a catalog of 8,440 candidate very metal-poor (VMP; [Fe/H] < -2.0) main-sequence turn-off (MSTO) and red giant stars in the Milky Way, identified from low-resolution spectra in LAMOST DR10. More than 7,000 of these candidates are brighter than G ~ 16, making them excellent targets for high-resolution spectroscopic […]


Continue.. A Metallicity Catalog of Very Metal-poor Main-sequence Turn-off and Red Giant Stars from LAMOST DR10