5,675 research outputs found
Emergent orbitals in the cluster Mott insulator on a breathing Kagome lattice
Motivated by the recent developments on cluster Mott insulating materials
such as the cluster magnet LiZnMoO, we consider the strong
plaquette charge ordered regime of the extended Hubbard model on a breathing
Kagome lattice and reveal the properties of the cluster Mottness. The plaquette
charge order arises from the inter-site charge interaction and the collective
motion of three localized electrons on the hexagon plaquettes. This model leads
naturally to a reduction of the local moments by 2/3 as observed in
LiZnMoO. Furthermore, at low temperatures each hexagon plaquette
contains an extra orbital-like degree of freedom in addition to the remaining
spin 1/2. We explore the consequence of this emergent orbital degree of
freedom. We point out the interaction between the local moments is naturally
described by a Kugel-Khomskii spin-orbital model. We develop a parton approach
and suggest a spin liquid ground state with spinon Fermi surfaces for this
model. We further predict an emergent orbital order when the system is under a
strong magnetic field. Various experimental consequences for
LiZnMoO are discussed, including an argument that the charge
ordering much be short ranged if the charge per Mo is slightly off
stoichiometry.Comment: 12 pages, 13 figure
Study of the Hubbard model on the triangular lattice using dynamical cluster approximation and dual fermion methods
We investigate the Hubbard model on the triangular lattice at half-filling
using the dynamical cluster approximation (DCA) and dual fermion (DF) methods
in combination with continuous-time quantum Monte carlo (CT QMC) and
semiclassical approximation (SCA) methods. We study the one-particle properties
and nearest-neighbor spin correlations using the DCA method. We calculate the
spectral functions using the CT QMC and SCA methods. The spectral function in
the SCA and obtained by analytic continuation of the Pade approximation in CT
QMC are in good agreement. We determine the metal-insulator transition (MIT)
and the hysteresis associated with a first-order transition in the double
occupancy and nearest-neighbor spin correlation functions as a function of
temperature. As a further check, we employ the DF method and discuss the
advantages and limitation of the dynamical mean field theory (DMFT), DCA and
recently developed DF methods by comparing Green's functions. We find an
enhancement of antiferromagnetic (AF) correlations and provide evidence for
magnetically ordered phases by calculating the spin susceptibility.Comment: 6 pages, 7 figure
Holography of Wrapped M5-branes and Chern-Simons theory
We study three-dimensional superconformal field theories on wrapped
M5-branes. Applying the gauge/gravity duality and the recently proposed 3d-3d
relation, we deduce quantitative predictions for the perturbative free energy
of a Chern-Simons theory on hyperbolic 3-space. Remarkably, the perturbative
expansion is expected to terminate at two-loops in the large N limit. We check
the correspondence numerically in a number of examples, and confirm the N^3
scaling with precise coefficients.Comment: 5 pages, 2 figures. Some clarifications, references added, misprint
correcte
Holography of 3d-3d correspondence at Large N
We study the physics of multiple M5-branes compactified on a hyperbolic
3-manifold. On the one hand, it leads to the 3d-3d correspondence which maps an
superconformal field theory to a pure Chern-Simons theory on
the 3-manifold. On the other hand, it leads to a warped AdS geometry in
M-theory holographically dual to the superconformal field theory. Combining the
holographic duality and the 3d-3d correspondence, we propose a conjecture for
the large limit of the perturbative free energy of a Chern-Simons theory on
hyperbolic 3-manifold. The conjecture claims that the tree, one-loop and
two-loop terms all share the same scaling behavior and are proportional
to the volume of the 3-manifold, while the three-loop and higher terms are
suppressed at large . Under mild assumptions, we prove the tree and one-loop
parts of the conjecture. For the two-loop part, we test the conjecture
numerically in a number of examples and find precise agreement. We also confirm
the suppression of higher loop terms in a few examples.Comment: 37 pages, 7 figure
Doping a Mott Insulator: Physics of High Temperature Superconductivity
This article reviews the effort to understand the physics of high temperature
superconductors from the point of view of doping a Mott insulator. The basic
electronic structure of the cuprates is reviewed, emphasizing the physics of
strong correlation and establishing the model of a doped Mott insulator as a
starting point. A variety of experiments are discussed, focusing on the region
of the phase diagram close to the Mott insulator (the underdoped region) where
the behavior is most anomalous. We introduce Anderson's idea of the resonating
valence bond (RVB) and argue that it gives a qualitative account of the data.
The importance of phase fluctuation is discussed, leading to a theory of the
transition temperature which is driven by phase fluctuation and thermal
excitation of quasiparticles. We then describe the numerical method of
projected wavefunction which turns out to be a very useful technique to
implement the strong correlation constraint, and leads to a number of
predictions which are in agreement with experiments. The remainder of the paper
deals with an analytic treatment of the t-J model, with the goal of putting the
RVB idea on a more formal footing. The slave-boson is introduced to enforce the
constraint of no double occupation. The implementation of the local constraint
leads naturally to gauge theories. We give a rather thorough discussion of the
role of gauge theory in describing the spin liquid phase of the undoped Mott
insulator. We next describe the extension of the SU(2) formulation to nonzero
doping. We show that inclusion of gauge fluctuation provides a reasonable
description of the pseudogap phase.Comment: 69 pages, 36 fgiures. Submitted to Rev. Mod. Phy
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction
Object detection systems based on the deep convolutional neural network (CNN)
have recently made ground- breaking advances on several object detection
benchmarks. While the features learned by these high-capacity neural networks
are discriminative for categorization, inaccurate localization is still a major
source of error for detection. Building upon high-capacity CNN architectures,
we address the localization problem by 1) using a search algorithm based on
Bayesian optimization that sequentially proposes candidate regions for an
object bounding box, and 2) training the CNN with a structured loss that
explicitly penalizes the localization inaccuracy. In experiments, we
demonstrated that each of the proposed methods improves the detection
performance over the baseline method on PASCAL VOC 2007 and 2012 datasets.
Furthermore, two methods are complementary and significantly outperform the
previous state-of-the-art when combined.Comment: CVPR 201
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