110 citations
- Chinese Academy of SciencesCN29 papers
- University of Science and Technology of ChinaCN23 papers
- National Astronomical ObservatoriesCN17 papers
- Nanjing UniversityCN9 papers
- Anqing Normal UniversityCN8 papers
- Henan Polytechnic UniversityCN6 papers
- Scuola Internazionale Superiore di Studi AvanzatiIT6 papers
- Shanghai Astronomical ObservatoryCN6 papers
- Beijing Normal UniversityCN5 papers
- Dalian University of TechnologyCN5 papers
- Nanjing Normal UniversityCN5 papers
- Shandong UniversityCN5 papers
67 papers
Discovery of an Unbound Flyby Companion of UBC 63: In the Immediate Aftermath of a Close Encounter
Samrat Biswas, Biman J Medhi, Sergio Messina +8
We re-investigate the open cluster UBC 63 using the Gaia DR3 data and show that, rather than being a single cluster as previously classified, it is a compelling candidate for a dou…
A model-independent test of the cosmic distance-duality relation using galaxy clusters and Type Ia supernovae matched pairs
Jian Hu, Yi Liu, Jian-Ping Hu +1
The cosmic distance-duality relation (CDDR), expressed as , is a fundamental relation in cosmology connecting luminosity distance () and angular diame…
The influence of the random numbers quality on the results in stochastic simulations and machine learning
Benjamin A. Antunes
Pseudorandom number generators (PRNGs) are ubiquitous in stochastic simulations and machine learning (ML), where they drive sampling, parameter initialization, regularization, and…
The Low-Frequency Spectra of Radio Pulsars
Ting Yu, Zhongli Zhang, Hongyu Gong +1
Low-frequency spectral studies of radio pulsars represent a key method for uncovering their emission mechanisms, magnetospheric structure, and signal interactions with the surround…
LAMOST medium-resolution spectroscopic survey of Galactic Open Clusters (LAMOST-MRS-O): An overview of survey plan and preliminary results
Xi Zhang, Chengzhi Liu, Jing Zhong +7
As part of the LAMOST medium-resolution spectroscopic survey, the LAMOST-MRS-O is a non-time domain survey that aims to perform medium-resolution spectral observations for member s…
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model
Guanwen Fang, Yao Dai, Zesen Lin +6
In this work, we update the unsupervised machine learning (UML) step by proposing an algorithm based on ConvNeXt large model coding to improve the efficiency of unlabeled galaxy mo…