Measurement of cesium $8P_{J}{rightarrow}$ $6P_{J’}$ electric quadrupole transition probabilities using fluorescence spectroscopy

Kavli Affiliate: Jing Wang | First 5 Authors: Jing Wang, Yuki Miyamoto, Hideaki Hara, Minoru Tanaka, Motomichi Tashiro | Summary: Fluorescence spectra of the $8P_{J}{rightarrow}$ $6P_{J’}$ ($J$ and $J’$ = 3/2, 1/2) electric quadrupole transition of cesium atoms have been observed with a heated cesium vapor cell. We determined the ratio of the transition probabilities […]


Continue.. Measurement of cesium $8P_{J}{rightarrow}$ $6P_{J’}$ electric quadrupole transition probabilities using fluorescence spectroscopy

Measurement of cesium $8P_{J}rightarrow 6P_{J’}$ electric quadrupole transition probabilities using fluorescence spectroscopy

Kavli Affiliate: Jing Wang | First 5 Authors: Jing Wang, Yuki Miyamoto, Hideaki Hara, Minoru Tanaka, Motomichi Tashiro | Summary: Fluorescence spectra of the $8P_{J} rightarrow 6P_{J’}$ ($J$ and $J’$ = 3/2, 1/2) electric quadrupole transition of cesium atoms have been observed with a heated cesium vapor cell. We determined the ratio of the transition […]


Continue.. Measurement of cesium $8P_{J}rightarrow 6P_{J’}$ electric quadrupole transition probabilities using fluorescence spectroscopy

TransAnaNet: Transformer-based Anatomy Change Prediction Network for Head and Neck Cancer Patient Radiotherapy

Kavli Affiliate: Jing Wang | First 5 Authors: Meixu Chen, Kai Wang, Michael Dohopolski, Howard Morgan, Jing Wang | Summary: Early identification of head and neck cancer (HNC) patients who would experience significant anatomical change during radiotherapy (RT) is important to optimize patient clinical benefit and treatment resources. This study aims to assess the feasibility […]


Continue.. TransAnaNet: Transformer-based Anatomy Change Prediction Network for Head and Neck Cancer Patient Radiotherapy

Dynamic Deep Factor Graph for Multi-Agent Reinforcement Learning

Kavli Affiliate: Ran Wang | First 5 Authors: Yuchen Shi, Shihong Duan, Cheng Xu, Ran Wang, Fangwen Ye | Summary: This work introduces a novel value decomposition algorithm, termed textit{Dynamic Deep Factor Graphs} (DDFG). Unlike traditional coordination graphs, DDFG leverages factor graphs to articulate the decomposition of value functions, offering enhanced flexibility and adaptability to […]


Continue.. Dynamic Deep Factor Graph for Multi-Agent Reinforcement Learning

Dynamic Deep Factor Graph for Multi-Agent Reinforcement Learning

Kavli Affiliate: Ran Wang | First 5 Authors: Yuchen Shi, Shihong Duan, Cheng Xu, Ran Wang, Fangwen Ye | Summary: This work introduces a novel value decomposition algorithm, termed textit{Dynamic Deep Factor Graphs} (DDFG). Unlike traditional coordination graphs, DDFG leverages factor graphs to articulate the decomposition of value functions, offering enhanced flexibility and adaptability to […]


Continue.. Dynamic Deep Factor Graph for Multi-Agent Reinforcement Learning

Advancing Head and Neck Cancer Survival Prediction via Multi-Label Learning and Deep Model Interpretation

Kavli Affiliate: Jing Wang | First 5 Authors: Meixu Chen, Kai Wang, Jing Wang, , | Summary: A comprehensive and reliable survival prediction model is of great importance to assist in the personalized management of Head and Neck Cancer (HNC) patients treated with curative Radiation Therapy (RT). In this work, we propose IMLSP, an Interpretable […]


Continue.. Advancing Head and Neck Cancer Survival Prediction via Multi-Label Learning and Deep Model Interpretation

Very Long Baseline Array Observations of Parsec-scale Radio Emission in Dual Active Galactic Nuclei

Kavli Affiliate: Luis C. Ho | First 5 Authors: Wancheng Xu, Lang Cui, Xiang Liu, Tao An, Hongmin Cao | Summary: It is believed that dual active galactic nuclei (dual AGN) will form during galaxies merge. Studying dual-AGN emission can provide valuable insights into galaxy merging and evolution. To investigate parsec-scale radio emission properties, we […]


Continue.. Very Long Baseline Array Observations of Parsec-scale Radio Emission in Dual Active Galactic Nuclei

Large Scale Overdensity of Lyman Break Galaxies Around the z=6.3 Ultraluminous Quasar J0100+2802

Kavli Affiliate: Linhua Jiang | First 5 Authors: Maria Pudoka, Feige Wang, Xiaohui Fan, Jinyi Yang, Jaclyn Champagne | Summary: We study the environment of the z=6.33 ultraluminous quasar SDSS J010013.02+280225.8 (J0100) to understand its association with large-scale structure. Theoretical models propose high-redshift quasars as markers of galaxy overdensities residing in the most massive dark […]


Continue.. Large Scale Overdensity of Lyman Break Galaxies Around the z=6.3 Ultraluminous Quasar J0100+2802

Semi-supervised Symmetric Matrix Factorization with Low-Rank Tensor Representation

Kavli Affiliate: Ran Wang | First 5 Authors: Yuheng Jia, Jia-Nan Li, Wenhui Wu, Ran Wang, | Summary: Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ability of SNMF. The previous methods introduce the pairwise constraints from the local perspective, i.e., […]


Continue.. Semi-supervised Symmetric Matrix Factorization with Low-Rank Tensor Representation

Semi-supervised Symmetric Non-negative Matrix Factorization with Low-Rank Tensor Representation

Kavli Affiliate: Ran Wang | First 5 Authors: Yuheng Jia, Jia-Nan Li, Wenhui Wu, Ran Wang, | Summary: Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ability of SNMF. The previous methods introduce the pairwise constraints from the local perspective, i.e., […]


Continue.. Semi-supervised Symmetric Non-negative Matrix Factorization with Low-Rank Tensor Representation