Quantum entangling power of adiabatically connected hamiltonians

The space of quantum Hamiltonians has a natural partition in classes of operators that can be adiabatically deformed into each other. We consider parametric families of Hamiltonians acting on a bi-partite quantum state-space. When the different Hamiltonians in the family fall in the same adiabatic class one can manipulate entanglement by moving through energy eigenstates corresponding to different value of the control parameters. We introduce an associated notion of adiabatic entangling power. This novel measure is analyzed for general $d\times d$ quantum systems and specific two-qubits examples are studiedComment: 5 pages, LaTeX, 2 eps figures included. Several non minor changes made (thanks referee) Version to appear in the PR

DreamCAM: A FPGA-based platform for smart camera networks

International audience—The main challenges in smart camera networks come from the limited capacity of network communications. Indeed, wireless protocols such as the IEEE 802.15.4 protocol target low data rate, low power consumption and low cost wireless networking in order to fit the requirements of sensor networks. Since nodes more and more often integrate image sensors, network bandwidth has become a strong limiting factor in application deployment. This means that data must be processed at the node level before being sent on the network. In this context, FPGA-based platforms, supporting massive data parallelism, offer large opportunities for on-board processing. We present in this paper our FPGA-based smart camera platform, called DreamCam, which is able to autonomously exchange processed information on an Ethernet network

Distributed FPGA-based smart camera architecture for computer vision applications

International audienceSmart camera networks (SCN) raise challenging issues in many fields of research, including vision processing, communication protocols, distributed algorithms or power management. Furthermore, application logic in SCN is not centralized but spread among network nodes meaning that each node must have to process images to extract significant features, and aggregate data to understand the surrounding environment. In this context, smart camera have first embedded general purpose processor (GPP) for image processing. Since image resolution increases, GPPs have reached their limit to maintain real-time processing constraint. More recently, FPGA-based platforms have been studied for their massive parallelism capabilities. This paper present our new FPGA-based smart camera platform supporting cooperation between nodes and run-time updatable image processing. The architecture is based on a full reconfigurable pipeline driven by a softcore

TOUGH2Viewer tutorial

TOUGH2Viewer is a Java program capable of displaying unstructured (Voronoi complying) grids, locally refined and structured grids (complying with the MESHMAKER iTOUGH2 format). In particular, TOUGH2Viewer allows to navigate through a 3D grid compatible with the iTOUGH2 data file format and see: (1) the thermodynamic variables and the material (namely, petrophysical properties) of each block; (2) maps of isovalues (2D) of all thermodynamic variables; (3) isosurfaces (3D) of all thermodynamic variables; (4) flows of mass and heat between blocks; (5) spatial profiles of thermodynamic variables, of a selected set of blocks, long a Cartesian directions; (6) time plot of thermodynamic variables of a selected block. All commands to manage a 3D visualization (zooming, pan, rotations) are CAD complying

HOG-Dot: A Parallel Kernel-Based Gradient Extraction for Embedded Image Processing

International audienceIn this paper we propose HOG-Dot, a method for the direct computation of the polar image gradients coordinates from the pixels values. The proposed algorithm, to be used as the first step of the Histogram of Oriented Gradient (HOG) pipeline, approximates the exact gradient with its projection onto a versor chosen among the projection plane set. Instead of non linear computations, the HOG-Dot method exploits linear operations while introducing a bounded approximation error with respect to other HOG approaches, thus resulting a more suitable solution for embedded devices. Concerning the state of the art, it also achieves improved accuracy with the mathematical spatial gradient formulation

Robustness against parametric noise of non ideal holonomic gates

Holonomic gates for quantum computation are commonly considered to be robust against certain kinds of parametric noise, the very motivation of this robustness being the geometric character of the transformation achieved in the adiabatic limit. On the other hand, the effects of decoherence are expected to become more and more relevant when the adiabatic limit is approached. Starting from the system described by Florio et al. [Phys. Rev. A 73, 022327 (2006)], here we discuss the behavior of non ideal holonomic gates at finite operational time, i.e., far before the adiabatic limit is reached. We have considered several models of parametric noise and studied the robustness of finite time gates. The obtained results suggest that the finite time gates present some effects of cancellation of the perturbations introduced by the noise which mimic the geometrical cancellation effect of standard holonomic gates. Nevertheless, a careful analysis of the results leads to the conclusion that these effects are related to a dynamical instead of geometrical feature.Comment: 8 pages, 8 figures, several changes made, accepted for publication on Phys. Rev.

Parallel Image Gradient Extraction Core For FPGA-based Smart Cameras

International audienceOne of the biggest efforts in designing pervasive Smart Camera Networks (SCNs) is the implementation of complex and computationally intensive computer vision algorithms on resource constrained embedded devices. For low-level processing FPGA devices are excellent candidates because they support massive and fine grain data parallelism with high data throughput. However, if FPGAs offers a way to meet the stringent constraints of real-time execution, their exploitation often require significant algorithmic reformulations. In this paper, we propose a reformulation of a kernel-based gradient computation module specially suited to FPGA implementations. This resulting algorithm operates on-the-fly, without the need of video buffers and delivers a constant throughput. It has been tested and used as the first stage of an application performing extraction of Histograms of Oriented Gradients (HOG). Evaluation shows that its performance and low memory requirement perfectly matches low cost and memory constrained embedded devices

The lid method for exhaustive exploration of metastable states of complex systems

The `lid' algorithm performs an exhaustive exploration of neighborhoods of local energy minima of energy landscapes. This paper describes an implementation of the algorithm, including issues of parallel performance and scalability. To illustrate the versatility of the approach and to stress the common features present in landscapes of quite different systems, we present selected results for 1) a spin glass, 2) a ferromagnet, 3) a covalent network model for glassy systems, and 4) a polymer. The exponential nature of the local density of states found in these systems and its relation to the ordering transition is briefly commented upon.Comment: RevTeX, 11 pages, 1 figur

The role of the Berry Phase in Dynamical Jahn-Teller Systems

The presence/absence of a Berry phase depends on the topology of the manifold of dynamical Jahn-Teller potential minima. We describe in detail the relation between these topological properties and the way the lowest two adiabatic potential surfaces get locally degenerate. We illustrate our arguments through spherical generalizations of the linear T x h and H x h cases, relevant for the physics of fullerene ions. Our analysis allows us to classify all the spherical Jahn-Teller systems with respect to the Berry phase. Its absence can, but does not necessarily, lead to a nondegenerate ground state.Comment: revtex 7 pages, 2 eps figures include

Chaos, Thermodynamics and Quantum Mechanics: an Application to Celestial Dynamics

We address the issue of the quantum-classical correspondence in chaotic systems using, as recently done by Zurek [e-print quant-ph/9802054], the solar system as a whole as a case study: this author shows that the classicality of the planetary motion is ensured by the environment-induced decoherence. We show that equivalent results are provided by the theories of spontaneous fluctuations and that these latter theories, in some cases, result in a still faster process of decoherence. We show that, as an additional benefit, the assumption of spontaneous fluctuation makes it possible to genuinely derive thermodynamics from mechanics, namely, without implicitly assuming thermodynamics.Comment: 9 pages, two tables included, RevTex. Concluding part of Sec. IV revised and shortene