352 research outputs found
Simple to Complex Cross-modal Learning to Rank
The heterogeneity-gap between different modalities brings a significant
challenge to multimedia information retrieval. Some studies formalize the
cross-modal retrieval tasks as a ranking problem and learn a shared multi-modal
embedding space to measure the cross-modality similarity. However, previous
methods often establish the shared embedding space based on linear mapping
functions which might not be sophisticated enough to reveal more complicated
inter-modal correspondences. Additionally, current studies assume that the
rankings are of equal importance, and thus all rankings are used
simultaneously, or a small number of rankings are selected randomly to train
the embedding space at each iteration. Such strategies, however, always suffer
from outliers as well as reduced generalization capability due to their lack of
insightful understanding of procedure of human cognition. In this paper, we
involve the self-paced learning theory with diversity into the cross-modal
learning to rank and learn an optimal multi-modal embedding space based on
non-linear mapping functions. This strategy enhances the model's robustness to
outliers and achieves better generalization via training the model gradually
from easy rankings by diverse queries to more complex ones. An efficient
alternative algorithm is exploited to solve the proposed challenging problem
with fast convergence in practice. Extensive experimental results on several
benchmark datasets indicate that the proposed method achieves significant
improvements over the state-of-the-arts in this literature.Comment: 14 pages; Accepted by Computer Vision and Image Understandin
Superconductivity in the Two-Orbital Hubbard Model of Infinite-Layer Nickelates
The pairing symmetry in infinite-layer nickelate superconductors has been an
intriguing problem under heated debates. In this work, we study a two-orbital
Hubbard model with one strongly correlated orbital and one more itinerant
orbital, by using an eight-site cellular dynamic mean field theory study.
We establish a superconducting phase diagram with ,
and wave pairing symmetries, based on which we clarify the roles of
various relevant parameters including hybridization , itinerant carrier
density and interaction . We show that the
inclusion of a less correlated band in general suppresses the
wave pairing. We demonstrate that the wave is
maximized when the orbital has a large Coulomb repulsion with intermediate
hybridization parameter. We perform fluctuation diagnostics to show that the
driving force behind the wave is the intraband
antiferromagnetic fluctuations in the orbital, while for the
wave, the pairing is mainly from the antiferromagnetic correlations residing on
the local - bond in real space.Comment: 8 pages, 5 figure
Charge Transfer and Zhang-Rice Singlet Bands in the Nickelate Superconductor under Pressure
Recently, a bulk nickelate superconductor is
discovered at pressures with a remarkable high transition temperature . Here, we study a Hubbard model with tight-binding parameters derived from
\textit{ab initio} calculations of , by employing large
scale determinant quantum Monte Carlo and cellular dynamical mean-field theory.
Our result suggests that the superexchange couplings in this system are
comparable to that of cuprates. The system is a charge transfer insulator as
hole concentration becomes four per site at large Hubbard . Upon hole
doping, two low-energy spin-singlet bands emerge in the system exhibiting
distinct correlation properties: while the one composed of the out-of-plane
Ni- and O- orbitals demonstrates strong antiferromagnetic
correlations and narrow effective bandwidth, the in-plane singlet band
consisting of the Ni- and O- orbitals is in general
more itinerant. Over a broad range of hole doping, the doped holes occupy
primarily the and orbitals, whereas the
and orbitals retain underdoped. We propose an effective model to capture the relevant physics and discuss the implications of our
result for comprehending the superconductivity.Comment: Hund's coupling is discusse
High-T superconductivity in based on the bilayer two-orbital t-J model
The recently discovered high-T superconductor LaNiO has
sparked renewed interest in the unconventional superconductivity. Here we study
the unconventional superconductivity in pressurized LaNiO based on
a bilayer two-orbital model, using the renormalized mean-field theory.
Our results reveal a robust wave pairing driven by the inter-layer
magnetic coupling, which exhibits a transition temperature within the
same order of magnitude as the experimentally observed K. We
obtain a comprehensive superconducting phase diagram in the doping plane.
Notably, the LaNiO under pressure is found situated roughly in the
optimal doping regime of the phase diagram. When the orbital
becomes close to half-filling, wave and pairing can emerge from the
system. We discuss the interplay between the Fermi surface topology and
different pairing symmetries. The stability of the wave pairing against
Hund's coupling and other magnetic exchange couplings is examined.Comment: 8 pages, 8 figure
Bilayer two-orbital model of LaNiO under pressure
The newly discovered Ruddlesden-Popper bilayer LaNiO reaches an
remarkable superconducting transition temperature = 80 K under a pressure
of above 14 GPa. Here we propose a minimal bilayer two-orbital model of the
high-pressure phase of LaNiO. Our model is constructed with the
Ni-3d, 3d orbitals by using Wannier downfolding of the
density functional theory calculations, which captures the key ingredients of
the material, such as band structure and Fermi surface topology. There are two
electron pockets , and one hole pocket on the Fermi
surface, in which the , pockets show mixing of two orbitals,
while the pocket is associated with Ni-d orbital. The RPA
spin susceptibility reveals a magnetic enhancement associating to the
d state. A higher energy model with O-p orbitals is also provided
for further study
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