Entanglement between two superconducting qubits via interaction with nonclassical radiation

We propose a scheme to physically interface superconducting nanocircuits and quantum optics. We address the transfer of quantum information between systems having different physical natures and defined in Hilbert spaces of different dimensions. In particular, we investigate the transfer of the entanglement initially in a nonclassical state of an infinite dimensional system to a pair of superconducting charge qubits. This setup is able to drive an initially separable state of the qubits into an almost pure, highly entangled state suitable for quantum information processing.

Quantum electronic transport in a configuration interaction basis

An overview of a many-body approach to calculation of electronic transport in molecular systems is given. The physics required to describe electronic transport through a molecule at the many-body level, without relying on commonly made assumptions such as the Landauer formalism or linear response theory, is discussed. Physically, our method relies on the incorporation of scattering boundary conditions into a many-body wavefunction and application of the maximum entropy principle to the transport region. Mathematically, this simple physical model translates into a constrained nonlinear optimization problem. A strategy for solving the constrained optimization problem is given. (C) 2004 Wiley Periodicals, Inc.

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.

Accumulation of entanglement in a continuous variable memory

We study entanglement accumulation in a memory built out of two continuous variable systems interacting with a qubit that mediates their indirect coupling. We show that, in contrast with the case of bidimensional Hilbert spaces, entanglement superior to one ebit can be accumulated in the memory, even though no entangled resource is used. The protocol is immediately implementable and we assess the role of the main imperfections.

Liquid monomer-powder particle interaction in acrylic bone cement

It is known that the method used to mix the liquid monomer and powder of PMMA bone cement influences the quality of the cement that is used in total joint replacements. Mixing theory indicates that the interaction between the liquid monomer and the powder is affected by a number of parameters, such as cement viscosity and degree of agitation, with this knowledge utilized in the design of cement mixing devices. Therefore, the objectives of this study were to: (i) obtain information on the interaction of the liquid monomer and the powder in the case of an PMMA bone cement, (ii) show how this knowledge can be applied to the design of an automated cement mixing device, and (iii) compare the porosity, bending modulus, and bending strength of one commercially-available cement prepared using the automated mixer and prepared using a conventional mixer that is in current clinical use. Experimental data indicated that increasing the velocity and decreasing the viscosity of the systems produced cement that improved mechanical properties, which may contribute to better mechanical integrity and, hence, reduced tendency for aseptic loosening, of cemented hip implants.

Characterisation of the Interaction of Lactate Dehydrogenase With Tween-20 Using Isothermal Titration Calorimetry, Interfacial Rheometry and Surface Tension Measurements

In this study the nature of the interaction between Tween-20 and lactate dehydrogenase (LDH) was investigated using isothermal titration calorimetry (ITC). In addition the effects of the protein and surfactant on the interfacial properties were followed with interfacial rheology and surface tension measurements in order to understand the mechanism by which the surfactant prevents protein adsorption to the air– water interface. Comparisons were made with Tween-40 and Tween-80 in order to further investigate the mechanism. ITC measurements indicated a weak, probably hydrophobic, interaction between Tween-20 and LDH. Prevention of LDH adsorption to the air–water interface by the Tween surfactants was correlated with surface energy rather than surfactant CMC. While surface pressure appears to be the main driving force for the displacement of LDH from the air–water interface by Tween-20 a solubilisation mechanism may exist for other protein molecules. More generally the results of this study highlight the value of the use of ITC and interfacial measurements in characterising the surface behaviour of mixed surfactant and protein systems.

Memory-Centric Hardware Synthesis from Dataflow Models

Generation of hardware architectures directly from dataflow representations is increasingly being considered as research moves toward system level design methodologies. Creation of networks of IP cores to implement actor functionality is a common approach to the problem, but often the memory sub-systems produced using these techniques are inefficiently utilised. This paper explores some of the issues in terms of memory organisation and accesses when developing systems from these high level representations. Using a template matching design study, challenges such as modelling memory reuse and minimising buffer requirements are examined, yielding results with significantly less memory requirements and costly off-chip memory accesses.

On-line Emotion Recognition in a 3-D Activation-Valence-Time Continuum using Acoustic and Linguistic Cues

For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.

SoC memory hierarchy derivation from dataflow graphs

Hardware synthesis from dataflow graphs of signal processing systems is a growing research area as focus shifts to high level design methodologies. For data intensive systems, dataflow based synthesis can lead to an inefficient usage of memory due to the restrictive nature of synchronous dataflow and its inability to easily model data reuse. This paper explores how dataflow graph changes can be used to drive both the on-chip and off-chip memory organisation and how these memory architectures can be mapped to a hardware implementation. By exploiting the data reuse inherent to many image processing algorithms and by creating memory hierarchies, off-chip memory bandwidth can be reduced by a factor of a thousand from the original dataflow graph level specification of a motion estimation algorithm, with a minimal increase in memory size. This analysis is verified using results gathered from implementation of the motion estimation algorithm on a Xilinx Virtex-4 FPGA, where the delay between the memories and processing elements drops from 14.2 ns down to 1.878 ns through the refinement of the memory architecture. Care must be taken when modeling these algorithms however, as inefficiencies in these models can be easily translated into overuse of hardware resources.

Multimodal Biometric Human Recognition for Perceptual Human-Computer Interaction

In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.

Statistical theory of finite Fermi systems with chaotic excited eigenstates

A theory of strongly interacting Fermi systems of a few particles is developed. At high excit at ion energies (a few times the single-parti cle level spacing) these systems are characterized by an extreme degree of complexity due to strong mixing of the shell-model-based many-part icle basis st at es by the residual two- body interaction. This regime can be described as many-body quantum chaos. Practically, it occurs when the excitation energy of the system is greater than a few single-particle level spacings near the Fermi energy. Physical examples of such systems are compound nuclei, heavy open shell atoms (e.g. rare earths) and multicharged ions, molecules, clusters and quantum dots in solids. The main quantity of the theory is the strength function which describes spreading of the eigenstates over many-part icle basis states (determinants) constructed using the shell-model orbital basis. A nonlinear equation for the strength function is derived, which enables one to describe the eigenstates without diagonalization of the Hamiltonian matrix. We show how to use this approach to calculate mean orbital occupation numbers and matrix elements between chaotic eigenstates and introduce typically statistical variable s such as t emperature in an isolated microscopic Fermi system of a few particles.

On the alignment of debris disks and their host stars' rotation axis -implications for spin-orbit misalignment in exoplanetary systems

It has been widely thought that measuring the misalignment angle between the orbital plane of a transiting exoplanet and the spin of its host star was a good discriminator between different migration processes for hot-Jupiters. Specifically, well-aligned hot-Jupiter systems (as measured by the Rossiter-McLaughlin effect) were thought to have formed via migration through interaction with a viscous disc, while misaligned systems were thought to have undergone a more violent dynamical history. These conclusions were based on the assumption that the planet-forming disc was well-aligned with the host star. Recent work by Lai et al. has challenged this assumption, and proposes that the star-disc interaction in the pre-main sequence phase can exert a torque on the star and change its rotation axis angle. We have estimated the stellar rotation axis of a sample of stars which host spatially resolved debris disks. Comparison of our derived stellar rotation axis inclination angles with the geometrically measured debris-disk inclinations shows no evidence for a misalignment between the two.