Ground state of low-dimensional dipolar gases: Linear and zigzag chains

We study the ground-state phase diagram of ultracold dipolar gases in highly anisotropic traps. Starting from a one-dimensional geometry, by ramping down the transverse confinement along one direction, the gas reaches various planar distributions of dipoles. At large linear densities, when the dipolar gas exhibits a crystal-like phase, critical values of the transverse frequency exist below which the configuration exhibits transverse patterns. These critical values are found by means of a classical theory, and are in full agreement with classical Monte Carlo simulations. The study of the quantum system is performed numerically with Monte Carlo techniques and shows that the quantum fluctuations smoothen the transition and make it completely disappear in a gas phase. These predictions could be experimentally tested and would allow one to reveal the effect of zero-point motion on self-organized mesoscopic structures of matter waves, such as the transverse pattern of the zigzag chain.

Structural phase transitions in low-dimensional ion crystals

A chain of singly charged particles, confined by a harmonic potential, exhibits a sudden transition to a zigzag configuration when the radial potential reaches a critical value, depending on the particle number. This structural change is a phase transition of second order, whose order parameter is the crystal displacement from the chain axis. We study analytically the transition using Landau theory and find full agreement with numerical predictions by Schiffer [Phys. Rev. Lett. 70, 818 (1993)] and Piacente [Phys. Rev. B 69, 045324 (2004)]. Our theory allows us to determine analytically the system's behavior at the transition point.

Human pose tracking in low dimensional space enhanced by limb correction

This paper proposes a two-level 3D human pose tracking method for a specific action captured by several cameras. The generation of pose estimates relies on fitting a 3D articulated model on a Visual Hull generated from the input images. First, an initial pose estimate is constrained by a low dimensional manifold learnt by Temporal Laplacian Eigenmaps. Then, an improved global pose is calculated by refining individual limb poses. The validation of our method uses a public standard dataset and demonstrates its accurate and computational efficiency. © 2011 IEEE.

Structural and electronic properties of Ce overlayers and low-dimensional Pt-Ce alloys on Pt{111}

The structural, thermal, chemisorptive, and electronic properties of Ce on Pt{111} are studied by photoemission, Auger spectroscopy, scanning tunnel microscope (STM), and low-energy electron diffraction (LEED). Stranski-Krastanov-like growth of low-density Ce layers is accompanied by substantial valence charge transfer from Ce to Pt: in line with this, the measured dipole moment and polarizability of adsorbed Ce at low coverages are 7.2 x 10(-30) C m and similar to 1.3x10(-29) m(3), respectively. Pt-Ce intermixing commences at similar to 400 K and with increasing temperature a sequence of five different ordered surface alloys evolves. The symmetry, periodicities, and rotational epitaxy observed by LEED are in good accord with the STM data which reveal the true complexity of the system. The Various bimetallic surface phases are based on growth of crystalline Pt5Ce, a hexagonal layer structure consisting of alternating layers of Pt2Ce and Kagome nets of Pt atoms. This characteristic ABAB layered arrangement of the surface alloys is clearly imaged, and chemisorption data permit a distinction to be made between the more reactive Pt2Ce layer and the less reactive Pt Kagome net. Either type of layer can appear at the surface as the terminating structure, thicker films exhibiting unit mesh parameters characteristic of the bulk alloy.

Containing the Nanometer "Pandora-Box": Cross-Layer Design Techniques for Variation Aware Low Power Systems

The demand for richer multimedia services, multifunctional portable devices and high data rates can only been visioned due to the improvement in semiconductor technology. Unfortunately, sub-90 nm process nodes uncover the nanometer Pandora-box exposing the barriers of technology scaling-parameter variations, that threaten the correct operation of circuits, and increased energy consumption, that limits the operational lifetime of today's systems. The contradictory design requirements for low-power and system robustness, is one of the most challenging design problems of today. The design efforts are further complicated due to the heterogeneous types of designs ( logic, memory, mixed-signal) that are included in today's complex systems and are characterized by different design requirements. This paper presents an overview of techniques at various levels of design abstraction that lead to low power and variation aware logic, memory and mixed-signal circuits and can potentially assist in meeting the strict power budgets and yield/quality requirements of future systems.

Tools for analysing configuration interaction wavefunctions

The configuration interaction (CI) approach to quantum chemical calculations is a well-established means of calculating accurately the solution to the Schrodinger equation for many-electron systems. It represents the many-body electron wavefunction as a sum of spin-projected Slater determinants of orthogonal one-body spin-orbitals. The CI wavefunction becomes the exact solution of the Schrodinger equation as the length of the expansion becomes infinite, however, it is a difficult quantity to visualise and analyse for many-electron problems. We describe a method for efficiently calculating the spin-averaged one- and two-body reduced density matrices rho(psi)((r) over bar; (r) over bar' ) and Gamma(psi)((r) over bar (1), (r) over bar (2); (r) over bar'(1), (r) over bar'(2)) of an arbitrary CI wavefunction Psi. These low-dimensional functions are helpful tools for analysing many-body wavefunctions; we illustrate this for the case of the electron-electron cusp. From rho and Gamma one can calculate the matrix elements of any one- or two-body spin-free operator (O) over cap. For example, if (O) over cap is an applied electric field, this field can be included into the CI Hamiltonian and polarisation or gating effects may be studied for finite electron systems. (C) 2003 Elsevier B.V. All rights reserved.

Moisture-Activated Rheological Structuring of Nonaqueous Poloxamine–Poly(Acrylic Acid) Systems Designed as Novel Biomedical Implants

This study reports the formulation/characterisation of novel polymeric platforms designed to behave as low-viscosity systems in the nonaqueous state, however, following uptake of aqueous ?uids, exhibit rheological structuring and mucoadhesion. The rheological/mechanical and mucoadhesive properties of platforms containing poly(acrylic acid) (PAA, 1%, 3%, 5%, w/w) and poloxamines (Tetronic 904, 901, 704, 701, 304), both in the absence and presence of phosphate buffered saline (PBS, pH 7.4) are described. With the exception of Tetronic 904, all formulations exhibited Newtonian ?ow in the nonaqueous state, whereas, all aqueous formulations displayed pseudoplastic ?ow. The consistency and viscoelastic properties were dependent on the concentrations of PAA and PBS and Tetronic grade. PBS signi?cantly increased the consistency, viscoelasticity and mucoadhesion, reaching a maximum at a de?ned concentration of PBS that was dependent on PAA concentration and Tetronic grade. Formulations containing Tetronic 904 exhibited greatest consistency and elasticity both prior to and after dilution with PBS. Increasing PAA concentration enhanced the mucoadhesive properties. Prolonged drug release of metronidazole was observed from formulations containing 10% (w/w) PBS, 3% and, particularly, 5% (w/w) PAA. It is suggested that the physicochemical properties of formulations containing 3% or 5% (w/w) PAA and Tetronic 904, would render them suitable platforms for administration to body cavities.

Rigorous conditions for food-web intervality in high-dimensional trophic niche spaces

Food webs represent trophic (feeding) interactions in ecosystems. Since the late 1970s, it has been recognized that food-webs have a surprisingly close relationship to interval graphs. One interpretation of food-web intervality is that trophic niche space is low-dimensional, meaning that the trophic character of a species can be expressed by a single or at most a few quantitative traits. In a companion paper we demonstrated, by simulating a minimal food-web model, that food webs are also expected to be interval when niche-space is high-dimensional. Here we characterize the fundamental mechanisms underlying this phenomenon by proving a set of rigorous conditions for food-web intervality in high-dimensional niche spaces. Our results apply to a large class of food-web models, including the special case previously studied numerically.

Evaluating Asymmetric Multicore Systems-on-Chip using Iso-Metrics

The end of Dennard scaling has pushed power consumption into a first order concern for current systems, on par with performance. As a result, near-threshold voltage computing (NTVC) has been proposed as a potential means to tackle the limited cooling capacity of CMOS technology. Hardware operating in NTV consumes significantly less power, at the cost of lower frequency, and thus reduced performance, as well as increased error rates. In this paper, we investigate if a low-power systems-on-chip, consisting of ARM's asymmetric big.LITTLE technology, can be an alternative to conventional high performance multicore processors in terms of power/energy in an unreliable scenario. For our study, we use the Conjugate Gradient solver, an algorithm representative of the computations performed by a large range of scientific and engineering codes.

Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.

General, PDB-based collective variables for protein folding

New, automated forms of data-analysis are required in order to understand the high-dimensional trajectories that are obtained from molecular dynamics simulations on proteins. Dimensionality reduction algorithms are particularly appealing in this regard as they allow one to construct unbiased, low-dimensional representations of the trajectory using only the information encoded in the trajectory. The downside of this approach is that different sets of coordinates are required for each different chemical systems under study precisely because the coordinates are constructed using information from the trajectory. In this paper we show how one can resolve this problem by using the sketch-map algorithm that we recently proposed to construct a low-dimensional representation of the structures contained in the protein data bank (PDB). We show that the resulting coordinates are as useful for analysing trajectory data as coordinates constructed using landmark configurations taken from the trajectory and that these coordinates can thus be used for understanding protein folding across a range of systems.

Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

Person Re-Identification using Deep Convnets with Multi-task Learning

Person re-identification involves recognizing a person across non-overlapping camera views, with different pose, illumination, and camera characteristics. We propose to tackle this problem by training a deep convolutional network to represent a person’s appearance as a low-dimensional feature vector that is invariant to common appearance variations encountered in the re-identification problem. Specifically, a Siamese-network architecture is used to train a feature extraction network using pairs of similar and dissimilar images. We show that use of a novel multi-task learning objective is crucial for regularizing the network parameters in order to prevent over-fitting due to the small size the training dataset. We complement the verification task, which is at the heart of re-identification, by training the network to jointly perform verification, identification, and to recognise attributes related to the clothing and pose of the person in each image. Additionally, we show that our proposed approach performs well even in the challenging cross-dataset scenario, which may better reflect real-world expected performance. 

Enhanced dynamical entanglement transfer with multiple qubits

We present two strategies to enhance the dynamical entanglement transfer from continuous-variable (CV) to finite-dimensional systems by employing multiple qubits. First, we consider the entanglement transfer to a composite finite-dimensional system of many qubits simultaneously interacting with a bipartite CV field. We show that, considering realistic conditions in the generation of CV entanglement, a small number of qubits resonantly coupled to the CV system are sufficient for an almost complete dynamical transfer of the entanglement. Our analysis also sheds further light on the transition between the microscopic and macroscopic behaviors of composite finite-dimensional systems coupled to bosonic fields (like atomic clouds interacting with light). Furthermore, we present a protocol based on sequential interactions of the CV system with some ancillary qubit systems and on subsequent measurements, allowing us to probabilistically convert CV entanglement into "almost-perfect" Bell pairs of two qubits. Our proposals are suited for realizations in various experimental settings, ranging from cavity-QED to cavity-integrated superconducting devices.