Transport in bilayer graphene near charge neutrality: Which scattering mechanisms are important?

Using the semiclassical quantum Boltzmann equation (QBE), we numerically calculate the DC transport properties of bilayer graphene near charge neutrality. We find, in contrast to prior discussions, that phonon scattering is crucial even at temperatures below 40K. Nonetheless, electron-electron scattering still dominates over phonon collisions allowing a hydrodynamic approach. We introduce a simple two-fluid hydrodynamic model of electrons and holes interacting via Coulomb drag and compare our results to the full QBE calculation. We show that the two-fluid model produces quantitatively accurate results for conductivity, thermopower, and thermal conductivity.Comment: 10 pages, 3 figure

Quantum Boltzmann equation for bilayer graphene

A-B stacked bilayer graphene has massive electron and hole-like excitations with zero gap in the nearest-neighbor hopping approximation. In equilibrium, the quasiparticle occupation approximately follows the usual Fermi-Dirac distribution. In this paper we consider perturbing this equilibrium distribution so as to determine DC transport coefficients near charge neutrality. We consider the regime $\beta |\mu| \lesssim 1$ (with $\beta$ the inverse temperature and $\mu$ the chemical potential) where there is not a well formed Fermi surface. Starting from the Kadanoff-Baym equations, we obtain the quantum Boltzmann equation of the electron and hole distribution functions when the system is weakly perturbed out of equilibrium. The effect of phonons, disorder, and boundary scattering for finite sized systems are incorporated through a generalized collision integral. The transport coefficients, including the electrical and thermal conductivity, thermopower, and shear viscosity, are calculated in the linear response regime. We also extend the formalism to include an external magnetic field. We present results from numerical solutions of the quantum Boltzmann equation. Finally, we derive a simplified two-fluid hydrodynamic model appropriate for this system, which reproduces the salient results of the full numerical calculations.Comment: 27 pages, 7 figures, fixed typos, add a section on a two-fluid mode

Bipartite graph partitioning and data clustering

Many data types arising from data mining applications can be modeled as bipartite graphs, examples include terms and documents in a text corpus, customers and purchasing items in market basket analysis and reviewers and movies in a movie recommender system. In this paper, we propose a new data clustering method based on partitioning the underlying bipartite graph. The partition is constructed by minimizing a normalized sum of edge weights between unmatched pairs of vertices of the bipartite graph. We show that an approximate solution to the minimization problem can be obtained by computing a partial singular value decomposition (SVD) of the associated edge weight matrix of the bipartite graph. We point out the connection of our clustering algorithm to correspondence analysis used in multivariate analysis. We also briefly discuss the issue of assigning data objects to multiple clusters. In the experimental results, we apply our clustering algorithm to the problem of document clustering to illustrate its effectiveness and efficiency.Comment: Proceedings of ACM CIKM 2001, the Tenth International Conference on Information and Knowledge Management, 200

Electron scattering in isotonic chains as a probe of the proton shell structure of unstable nuclei

Electron scattering on unstable nuclei is planned in future facilities of the GSI and RIKEN upgrades. Motivated by this fact, we study theoretical predictions for elastic electron scattering in the N=82, N=50, and N=14 isotonic chains from very proton-deficient to very proton-rich isotones. We compute the scattering observables by performing Dirac partial-wave calculations. The charge density of the nucleus is obtained with a covariant nuclear mean-field model that accounts for the low-energy electromagnetic structure of the nucleon. For the discussion of the dependence of scattering observables at low-momentum transfer on the gross properties of the charge density, we fit Helm model distributions to the self-consistent mean-field densities. We find that the changes shown by the electric charge form factor along each isotonic chain are strongly correlated with the underlying proton shell structure of the isotones. We conclude that elastic electron scattering experiments in isotones can provide valuable information about the filling order and occupation of the single-particle levels of protons.Comment: 13 pages; 19 figure

Interaction effects and charge quantization in single-particle quantum dot emitters

We discuss a theoretical model of an on-demand single-particle emitter that employs a quantum dot, attached to an integer or fractional quantum Hall edge state. Via an exact mapping of the model onto the spin-boson problem we show that Coulomb interactions between the dot and the chiral quantum Hall edge state, unavoidable in this setting, lead to a destruction of precise charge quantization in the emitted wave-packet. Our findings cast doubts on the viability of this set-up as a single-particle source of quantized charge pulses. We further show how to use a spin-boson master equation approach to explicitly calculate the current pulse shape in this set-up.Comment: 5+5 pages, 3 figures, fixed typos, update Supplement Material and update figure

Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning.

Motor skill learning induces long-lasting reorganization of dendritic spines, principal sites of excitatory synapses, in the motor cortex. However, mechanisms that regulate these excitatory synaptic changes remain poorly understood. Here, using in vivo two-photon imaging in awake mice, we found that learning-induced spine reorganization of layer (L) 2/3 excitatory neurons occurs in the distal branches of their apical dendrites in L1 but not in the perisomatic dendrites. This compartment-specific spine reorganization coincided with subtype-specific plasticity of local inhibitory circuits. Somatostatin-expressing inhibitory neurons (SOM-INs), which mainly inhibit distal dendrites of excitatory neurons, showed a decrease in axonal boutons immediately after the training began, whereas parvalbumin-expressing inhibitory neurons (PV-INs), which mainly inhibit perisomatic regions of excitatory neurons, exhibited a gradual increase in axonal boutons during training. Optogenetic enhancement and suppression of SOM-IN activity during training destabilized and hyperstabilized spines, respectively, and both manipulations impaired the learning of stereotyped movements. Our results identify SOM inhibition of distal dendrites as a key regulator of learning-related changes in excitatory synapses and the acquisition of motor skills

An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

While deep learning methods are increasingly being applied to tasks such as computer-aided diagnosis, these models are difficult to interpret, do not incorporate prior domain knowledge, and are often considered as a "black-box." The lack of model interpretability hinders them from being fully understood by target users such as radiologists. In this paper, we present a novel interpretable deep hierarchical semantic convolutional neural network (HSCNN) to predict whether a given pulmonary nodule observed on a computed tomography (CT) scan is malignant. Our network provides two levels of output: 1) low-level radiologist semantic features, and 2) a high-level malignancy prediction score. The low-level semantic outputs quantify the diagnostic features used by radiologists and serve to explain how the model interprets the images in an expert-driven manner. The information from these low-level tasks, along with the representations learned by the convolutional layers, are then combined and used to infer the high-level task of predicting nodule malignancy. This unified architecture is trained by optimizing a global loss function including both low- and high-level tasks, thereby learning all the parameters within a joint framework. Our experimental results using the Lung Image Database Consortium (LIDC) show that the proposed method not only produces interpretable lung cancer predictions but also achieves significantly better results compared to common 3D CNN approaches

How efficient is an integrative approach in archaeological geophysics? Comparative case studies from Neolithic settlements in Thessaly (Central Greece)

The geophysical prospection of Neolithic tells imposes specific challenges due to the preservation and nature of the architectural context and the multiple, usually disturbed, soil strata. Contrary to the usual application of a single method, this paper deals with the advantages of using an integrated geophysical approach through the employment of various methodologies to map the Neolithic cul-tural and environmental landscape of Thessalian tells (magoules) in Central Greece. The success and failure of each method in resolving the various features of the magoules are discussed in detail, and as a whole, they demonstrate the benefits of a manifold geophysical prospection of the sites

The influence of twin boundaries on the Flux Line Lattice structure in YBaCuO: a study by Small Angle Neutron Scattering

The influence of Twin Boundaries (TB) on the Flux Line Lattice(FLL) structure was investigated by Small Angle Neutron Scattering (SANS). YBaCuO single crystals possessing different TB densities were studied. The SANS experiments show that the TB strongly modify the structure of the FLL. The flux lines meander as soon as the magnetic field makes an angle with the TB direction. According to the value of this angle but also to the ratio of the flux lines density over the TB density, one observes that the FLL exhibits two different unit cells in the plane perpendicular to the magnetic field. One is the classical hexagonal and anisotropic cell while the other is affected by an additional deformation induced by the TB. We discuss a possible relation between this deformation and the increase of the critical current usually observed in heavily twinned samples.Comment: accepted for publication in Phys Rev