ORCID Profile
0000-0002-8683-5038
Current Organisation
University of Tokyo
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Publisher: American Physical Society (APS)
Date: 16-06-2020
Publisher: American Physical Society (APS)
Date: 16-06-2021
Publisher: American Physical Society (APS)
Date: 21-06-2021
Publisher: American Physical Society (APS)
Date: 17-08-2018
Publisher: Springer Science and Business Media LLC
Date: 15-04-2020
Publisher: Springer Science and Business Media LLC
Date: 10-2020
Abstract: The electron (anti-)neutrino component of the T2K neutrino beam constitutes the largest background in the measurement of electron (anti-)neutrino appearance at the far detector. The electron neutrino scattering is measured directly with the T2K off-axis near detector, ND280. The selection of the electron (anti-)neutrino events in the plastic scintillator target from both neutrino and anti-neutrino mode beams is discussed in this paper. The flux integrated single differential charged-current inclusive electron (anti-)neutrino cross-sections, dσ/dp and dσ/d cos( θ ), and the total cross-sections in a limited phase-space in momentum and scattering angle ( p 300 MeV/c and θ ≤ 45°) are measured using a binned maximum likelihood fit and compared to the neutrino Monte Carlo generator predictions, resulting in good agreement.
Publisher: American Physical Society (APS)
Date: 02-06-2020
Publisher: American Physical Society (APS)
Date: 26-01-2021
Publisher: American Physical Society (APS)
Date: 21-07-2020
Publisher: Hindawi Limited
Date: 20-11-2019
DOI: 10.1155/2019/2680972
Abstract: Complex networks in reality may suffer from target attacks which can trigger the breakdown of the entire network. It is therefore pivotal to evaluate the extent to which a network could withstand perturbations. The research on network robustness has proven as a potent instrument towards that purpose. The last two decades have witnessed the enthusiasm on the studies of network robustness. However, existing studies on network robustness mainly focus on multilayer networks while little attention is paid to multipartite networks which are an indispensable part of complex networks. In this study, we investigate the robustness of multipartite networks under intentional node attacks. We develop two network models based on the largest connected component theory to depict the cascading failures on multipartite networks under target attacks. We then investigate the robustness of computer-generated multipartite networks with respect to eight node centrality metrics. We discover that the robustness of multipartite networks could display either discontinuous or continuous phase transitions. Interestingly, we discover that larger number of partite sets of a multipartite network could increase its robustness which is opposite to the phenomenon observed on multilayer networks. Our findings shed new lights on the robust structure design of complex systems. We finally present useful discussions on the applications of existing percolation theories that are well studied for network robustness analysis to multipartite networks. We show that existing percolation theories are not amenable to multipartite networks. Percolation on multipartite networks still deserves in-depth efforts.
No related grants have been discovered for Yoshinari Hayato.