Entanglement Suppression, Enhanced Symmetry and a Standard-Model-like Higgs Boson

Kavli Affiliate: Marcela Carena | First 5 Authors: Marcela Carena, Ian Low, Carlos E. M. Wagner, Ming-Lei Xiao, | Summary: We study information-theoretic properties of scalar models containing two Higgs doublets $Phi_a$, where $a=1,2$ is the flavor quantum number. Considering the 2-to-2 scattering $Phi_a Phi_b to Phi_c Phi_d$ as a two-qubit system in the flavor […]


Continue.. Entanglement Suppression, Enhanced Symmetry and a Standard-Model-like Higgs Boson

Entanglement Suppression, Enhanced Symmetry and a Standard-Model-like Higgs Boson

Kavli Affiliate: Marcela Carena | First 5 Authors: Marcela Carena, Ian Low, Carlos E. M. Wagner, Ming-Lei Xiao, | Summary: We study information-theoretic properties of scalar models containing two Higgs doublets $Phi_a$, where $a=1,2$ is the flavor quantum number. Considering the 2-to-2 scattering $Phi_a Phi_b to Phi_c Phi_d$ as a two-qubit system in the flavor […]


Continue.. Entanglement Suppression, Enhanced Symmetry and a Standard-Model-like Higgs Boson

Entanglement Suppression, Enhanced Symmetry and a Standard-Model-like Higgs Boson

Kavli Affiliate: Marcela Carena | First 5 Authors: Marcela Carena, Ian Low, Carlos E. M. Wagner, Ming-Lei Xiao, | Summary: We study information-theoretic properties of scalar models containing two Higgs doublets $Phi_a$, where $a=1,2$ is the flavor quantum number. Considering the 2-to-2 scattering $Phi_a Phi_b to Phi_c Phi_d$ as a two-qubit system in the flavor […]


Continue.. Entanglement Suppression, Enhanced Symmetry and a Standard-Model-like Higgs Boson

Growth of Seed Black Holes in Galactic Nuclei

Kavli Affiliate: Rainer Spurzem | First 5 Authors: Rainer Spurzem, Francesco Rizzuto, Manuel Arca Sedda, Albrecht Kamlah, Peter Berczik | Summary: The evolution of dense star clusters is followed by direct high-accuracy N-body simulation. The problem is to first order a gravitational N-body problem, but stars evolve due to astrophysics and the more massive ones […]


Continue.. Growth of Seed Black Holes in Galactic Nuclei

Revise thermal winds of remnant neutron stars in gamma-ray bursts

Kavli Affiliate: Renxin Xu | First 5 Authors: Shuang Du, Tingting Lin, Shujin Hou, Renxin Xu, | Summary: It seems that the wealth of information revealed by the multi-messenger observations of the binary neutron star (NS) merger event, GW170817/GRB 170817A/kilonova AT2017gfo, places irreconcilable constraints to models of the prompt emission of this gamma-ray burst (GRB). […]


Continue.. Revise thermal winds of remnant neutron stars in gamma-ray bursts

Coronal Properties of Low-Accreting AGNs using Swift, XMM-Newton and NuSTAR Observations

Kavli Affiliate: Claudio Ricci | First 5 Authors: Arghajit Jana, Arka Chatterjee, Hsiang-Kuang Chang, Prantik Nandi, Rubinur K. | Summary: We studied the broadband X-ray spectra of {it Swift}/BAT selected low-accreting AGNs using the observations from {it XMM-Newton}, {it Swift}, and {it NuSTAR} in the energy range of $0.5-150$~keV. Our sample consists of 30 AGNs […]


Continue.. Coronal Properties of Low-Accreting AGNs using Swift, XMM-Newton and NuSTAR Observations

Generalizable and explainable prediction of potential miRNA-disease associations based on heterogeneous graph learning

Kavli Affiliate: Yi Zhou | First 5 Authors: Yi Zhou, Meixuan Wu, Chengzhou Ouyang, Min Zhu, | Summary: Biomedical research has revealed the crucial role of miRNAs in the progression of many diseases, and computational prediction methods are increasingly proposed for assisting biological experiments to verify miRNA-disease associations (MDAs). However, the generalizability and explainability are […]


Continue.. Generalizable and explainable prediction of potential miRNA-disease associations based on heterogeneous graph learning

Generalizable prediction of potential miRNA-disease associations based on heterogeneous graph learning

Kavli Affiliate: Yi Zhou | First 5 Authors: Yi Zhou, Meixuan Wu, Chengzhou Ouyang, Xinyi Wang, Min Zhu | Summary: Biomedical studies have revealed the crucial role of miRNAs in the progression of many diseases, and computational prediction methods are increasingly proposed for assisting biological experiments to verify miRNA-disease associations (MDAs). The generalizability is a […]


Continue.. Generalizable prediction of potential miRNA-disease associations based on heterogeneous graph learning