Phase Diagram of the Hubbard Model: Beyond the Dynamical Mean Field

The Dynamical Cluster Approximation (DCA) is used to study non-local corrections to the dynamical mean field phase diagram of the two-dimensional Hubbard model. Regions of antiferromagnetic, d-wave superconducting, pseudo-gapped non-Fermi liquid, and Fermi liquid behaviors are found, in rough agreement with the generic phase diagram of the cuprates. The non-local fluctuations beyond the mean field both suppress the antiferromagnetism and mediate the superconductivity.Comment: 4 pages, 5 eps figures, submitted to PR

Noise-Activated Escape from a Sloshing Potential Well

We treat the noise-activated escape from a one-dimensional potential well of an overdamped particle, to which a periodic force of fixed frequency is applied. We determine the boundary layer behavior, and the physically relevant length scales, near the oscillating well top. We show how stochastic behavior near the well top generalizes the behavior first determined by Kramers, in the case without forcing. Both the case when the forcing dies away in the weak noise limit, and the case when it does not, are examined. We also discuss the relevance of various scaling regimes to recent optical trap experiments.Comment: 9 pages, no figures, REVTeX, expanded versio

Superconductivity in striped and multi-Fermi-surface Hubbard models: From the cuprates to the pnictides

Single- and multi-band Hubbard models have been found to describe many of the complex phenomena that are observed in the cuprate and iron-based high-temperature superconductors. Simulations of these models therefore provide an ideal framework to study and understand the superconducting properties of these systems and the mechanisms responsible for them. Here we review recent dynamic cluster quantum Monte Carlo simulations of these models, which provide an unbiased view of the leading correlations in the system. In particular, we discuss what these simulations tell us about superconductivity in the homogeneous 2D single-orbital Hubbard model, and how charge stripes affect this behavior. We then describe recent simulations of a bilayer Hubbard model, which provides a simple model to study the type and nature of pairing in systems with multiple Fermi surfaces such as the iron-based superconductors.Comment: Published as part of Superstripes 2011 (Rome) conference proceeding

Integration with Ontologies

One of today’s hottest IT topics is integration, as bringing together information from different sources and structures is not completely solved. The approach outlined here wants to illustrate how ontologies [Gr93] could help to support the integration process

Phase behavior of the Confined Lebwohl-Lasher Model

The phase behavior of confined nematogens is studied using the Lebwohl-Lasher model. For three dimensional systems the model is known to exhibit a discontinuous nematic-isotropic phase transition, whereas the corresponding two dimensional systems apparently show a continuous Berezinskii-Kosterlitz-Thouless like transition. In this paper we study the phase transitions of the Lebwohl-Lasher model when confined between planar slits of different widths in order to establish the behavior of intermediate situations between the pure planar model and the three-dimensional system, and compare with previous estimates for the critical thickness, i.e. the slit width at which the transition switches from continuous to discontinuous.Comment: Submitted to Physical Review

Buffering plasmons in nanoparticle waveguides at the virtual-localized transition

We study the plasmonic energy transfer from a locally excited nanoparticle (LE-NP) to a linear array of small NPs and we obtain the parametric dependence of the response function. An analytical expression allows us to distinguish the extended resonant states and the localized ones, as well as an elusive regime of virtual states. This last appears when the resonance width collapses and before it becomes a localized state. Contrary to common wisdom, the highest excitation transfer does not occur when the system has a well defined extended resonant state but just at the virtual-localized transition, where the main plasmonic modes have eigenfrequencies at the passband edge. The slow group velocity at this critical frequency enables the excitation buffering and hence favors a strong signal inside the chain. A similar situation should appear in many other physical systems. The extreme sensitivity of this transition to the waveguide and LE-NP parameters provides new tools for plasmonics.Comment: Regular article: 7 pages and 5 figure

Probably Safe or Live

This paper presents a formal characterisation of safety and liveness properties \`a la Alpern and Schneider for fully probabilistic systems. As for the classical setting, it is established that any (probabilistic tree) property is equivalent to a conjunction of a safety and liveness property. A simple algorithm is provided to obtain such property decomposition for flat probabilistic CTL (PCTL). A safe fragment of PCTL is identified that provides a sound and complete characterisation of safety properties. For liveness properties, we provide two PCTL fragments, a sound and a complete one. We show that safety properties only have finite counterexamples, whereas liveness properties have none. We compare our characterisation for qualitative properties with the one for branching time properties by Manolios and Trefler, and present sound and complete PCTL fragments for characterising the notions of strong safety and absolute liveness coined by Sistla

Automated Multi-sequence Cardiac MRI Segmentation Using Supervised Domain Adaptation

Left ventricle segmentation and morphological assessment are essential for improving diagnosis and our understanding of cardiomyopathy, which in turn is imperative for reducing risk of myocardial infarctions in patients. Convolutional neural network (CNN) based methods for cardiac magnetic resonance (CMR) image segmentation rely on supervision with pixel-level annotations, and may not generalize well to images from a different domain. These methods are typically sensitive to variations in imaging protocols and data acquisition. Since annotating multi-sequence CMR images is tedious and subject to inter- and intra-observer variations, developing methods that can automatically adapt from one domain to the target domain is of great interest. In this paper, we propose an approach for domain adaptation in multi-sequence CMR segmentation task using transfer learning that combines multi-source image information. We first train an encoder-decoder CNN on T2-weighted and balanced-Steady State Free Precession (bSSFP) MR images with pixel-level annotation and fine-tune the same network with a limited number of Late Gadolinium Enhanced-MR (LGE-MR) subjects, to adapt the domain features. The domain-adapted network was trained with just four LGE-MR training samples and obtained an average Dice score of ∼∼85.0% on the test set comprises of 40 LGE-MR subjects. The proposed method significantly outperformed a network without adaptation trained from scratch on the same set of LGE-MR training data

Tunable graphene-based polarizer

It is shown that an attenuated total reflection structure containing a graphene layer can operate as a tunable polarizer of the electromagnetic radiation. The polarization angle is controlled by adjusting the voltage applied to graphene via external gate. The mechanism is based on the resonant coupling of $p-$polarized electromagnetic waves to the surface plasmon-polaritons in graphene. The presented calculations show that, at resonance, the reflected wave is almost 100% $s-$polarized.Comment: submitted to the Applied Physics Letter