Zobrazeno 11 - 20
of 46 289
pro vyhledávání: '"Zhang, Wen"'
We propose a theoretical scheme to enhance the sensitivity of a quantum fiber-optical gyroscope (QFOG) via a non-Gaussian-state probe based on quadrature measurements of the optical field. The non-Gaussian-state probe utilizes the product state compr
Externí odkaz:
http://arxiv.org/abs/2406.02217
This study investigates the excesses observed in the diphoton and $b\bar b$ data around $95\;{\rm GeV}$ within the framework of the $B-L$ supersymmetric model (B-LSSM). Comparing with the minimal supersymmetric standard model, the B-LSSM incorporates
Externí odkaz:
http://arxiv.org/abs/2406.01926
Accurately predicting antibody-antigen binding residues, i.e., paratopes and epitopes, is crucial in antibody design. However, existing methods solely focus on uni-modal data (either sequence or structure), disregarding the complementary information
Externí odkaz:
http://arxiv.org/abs/2405.20668
Accurate prediction of molecular properties is critical in the field of drug discovery. However, existing methods do not fully consider the fact that molecules in the real world usually possess multiple property labels, and complex high-order relatio
Externí odkaz:
http://arxiv.org/abs/2405.18724
Autor:
Zhang, Yichi, Chen, Zhuo, Guo, Lingbing, Xu, Yajing, Hu, Binbin, Liu, Ziqi, Zhang, Wen, Chen, Huajun
Multi-modal knowledge graph completion (MMKGC) aims to automatically discover new knowledge triples in the given multi-modal knowledge graphs (MMKGs), which is achieved by collaborative modeling the structural information concealed in massive triples
Externí odkaz:
http://arxiv.org/abs/2405.16869
This paper investigates the conformal isometry hypothesis as a potential explanation for the emergence of hexagonal periodic patterns in the response maps of grid cells. The hypothesis posits that the activities of the population of grid cells form a
Externí odkaz:
http://arxiv.org/abs/2405.16865
Autor:
Zhang, Yichi, Hu, Binbin, Chen, Zhuo, Guo, Lingbing, Liu, Ziqi, Zhang, Zhiqiang, Liang, Lei, Chen, Huajun, Zhang, Wen
Knowledge graphs (KGs) provide reliable external knowledge for a wide variety of AI tasks in the form of structured triples. Knowledge graph pre-training (KGP) aims to pre-train neural networks on large-scale KGs and provide unified interfaces to enh
Externí odkaz:
http://arxiv.org/abs/2405.13085
Publikováno v:
Phys. Rev. E 109, 054123 (2024)
In this study, we explore the quantum critical phenomena in generalized Aubry-Andr\'{e} models, with a particular focus on the scaling behavior at various filling states. Our approach involves using quantum fidelity susceptibility to precisely identi
Externí odkaz:
http://arxiv.org/abs/2405.13282
We investigate the topological gauge-theory terms and quantum criticality in spin-1 Kitaev chain with generic single-ion anisotropies (SIAs). The ground-state phase diagram, including Kitaev spin liquid (KSL) phase and gapless dimer phase, is determi
Externí odkaz:
http://arxiv.org/abs/2405.13281
Autor:
Huang, Feng, Zhang, Wen
Spectral graph convolutional network (SGCN) is a kind of graph neural networks (GNN) based on graph signal filters, and has shown compelling expressivity for modeling graph-structured data. Most SGCNs adopt polynomial filters and learn the coefficien
Externí odkaz:
http://arxiv.org/abs/2405.03296