The Gravitational-Wave Physics II: Progress

Kavli Affiliate: Kejia Lee | First 5 Authors: Ligong Bian, Rong-Gen Cai, Shuo Cao, Zhoujian Cao, He Gao | Summary: It has been a half-decade since the first direct detection of gravitational waves, which signifies the coming of the era of the gravitational-wave astronomy and gravitational-wave cosmology. The increasing number of the detected gravitational-wave events […]


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Modeling Dense Star Clusters in the Milky Way and Beyond with the Cluster Monte Carlo Code

Kavli Affiliate: Pau Amaro Seoane | First 5 Authors: Carl L. Rodriguez, Newlin C. Weatherford, Scott C. Coughlin, Pau Amaro Seoane, Katelyn Breivik | Summary: We describe the public release of the Cluster Monte Carlo Code (CMC) a parallel, star-by-star $N$-body code for modeling dense star clusters. CMC treats collisional stellar dynamics using H’enon’s method, […]


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Merging timescale for supermassive black hole binary in interacting galaxy NGC 6240

Kavli Affiliate: Rainer Spurzem | First 5 Authors: Margarita Sobolenko, Peter Berczik, Rainer Spurzem, , | Summary: One of the main possible way of creating the supermassive black hole (SMBH) is a so call hierarchical merging scenario. Central SMBHs at the final phase of interacting and coalescing host-galaxies are observed as SMBH binary (SMBHB) candidates […]


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Evolution of high-redshift quasar hosts and promotion of massive black hole seed formation

Kavli Affiliate: Kohei Inayoshi | First 5 Authors: Wenxiu Li, Kohei Inayoshi, Yu Qiu, , | Summary: High-redshift luminous quasars powered by accreting supermassive black holes (SMBHs) with mass $gtrsim 10^9 M_odot$ constrain their formation pathways. We investigate the formation of heavy seeds of SMBHs through gas collapse in the quasar host progenitors, using merger […]


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Optical coherent dot-product chip for sophisticated deep learning regression

Kavli Affiliate: Jing Wang | First 5 Authors: Shaofu Xu, Jing Wang, Haowen Shu, Zhike Zhang, Sicheng Yi | Summary: Optical implementations of neural networks (ONNs) herald the next-generation high-speed and energy-efficient deep learning computing by harnessing the technical advantages of large bandwidth and high parallelism of optics. However, due to the problems of incomplete […]


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External Calibrator in Global Signal Experiment for Detection of the Epoch of Reionization

Kavli Affiliate: Kejia Lee | First 5 Authors: Yan Huang, Xiang-Ping Wu, Quan Guo, Qian Zheng, Biying Li | Summary: We present a conceptual design study of external calibrators in the 21 cm experiment towards detecting the globally averaged radiation of the epoch of reionization (EoR). Employment of external calibrator instead of internal calibrator commonly […]


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Energy conversion from heat to electricity by highly reversible phase-transforming ferroelectrics

Kavli Affiliate: Xian Chen | First 5 Authors: Chenbo Zhang, Zhuohui Zeng, Zeyuan Zhu, Nobumichi Tamura, Xian Chen | Summary: Searching for performant multiferroic materials attracts general research interests in energy science as they have been increasingly exploited as the conversion media among thermal, electric, magnetic and mechanical energies by using their temperature-dependent ferroic properties. […]


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Breaching the limit: formation of GW190521-like and IMBH mergers in young massive clusters

Kavli Affiliate: Rainer Spurzem | First 5 Authors: Manuel Arca Sedda, Francesco Paolo Rizzuto, Thorsten Naab, Jeremiah Ostriker, Mirek Giersz | Summary: The LIGO-Virgo-Kagra collaboration (LVC) discovered recently GW190521, a gravitational wave (GW) source associated with the merger between two black holes (BHs) with mass $66$ M$_odot$ and $>85$ M$_odot$. GW190521 represents the first BH […]


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Learning Gaussian Graphical Models with Latent Confounders

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Alexander Franks, Sang-Yun Oh, , | Summary: Gaussian Graphical models (GGM) are widely used to estimate the network structures in many applications ranging from biology to finance. In practice, data is often corrupted by latent confounders which biases inference of the underlying true graphical structure. […]


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