Dark Entangled Steady States of Interacting Rydberg Atoms

We propose a scheme for rapid generation of high fidelity steady state entanglement between a pair of atoms. A two-photon excitation process towards long-lived Rydberg states with finite pairwise interaction, a dark state interference effect in the individual atoms, and spontaneous emission from their short-lived excited states lead to rapid, dissipative formation of an entangled steady state. We show that for a wide range of physical parameters, this entangled state is formed on a time scale given by the strengths of coherent Raman and Rabi fields applied to the atoms, while it is only weakly dependent on the Rydberg interaction strength.Comment: 4 Pages, 3 figures + Supplementary Information [Phys. Rev. Lett. 111, 033606

Robust Rydberg interaction gates with adiabatic passage

We show that with adiabatic passage, one can reliably drive two-photon optical transitions between the ground states and interacting Rydberg states in a pair of atoms. For finite Rydberg interaction strengths a new adiabatic pathway towards the doubly Rydberg excited state is identified when a constant detuning is applied with respect to an intermediate optically excited level. The Rydberg interaction among the excited atoms provides a phase that may be used to implement quantum gate operations on atomic ground state qubits.Comment: 5 pages, 4 figure

Dynamics of magnetic single domain particles embedded in a viscous liquid

Kinetic equations for magnetic nano particles dispersed in a viscous liquid are developed and analyzed numerically. Depending on the amplitude of an applied oscillatory magnetic field the particles orient their time averaged anisotropy axis perpendicular to the applied field for low magnetic field amplitudes and nearly parallel to the direction of the field for high amplitudes. The transition between these regions takes place in a narrow field interval. In the low field region the magnetic moment is locked to some crystal axis and the energy absorption in an oscillatory driving field is dominated by viscous losses associated with particle rotation in the liquid. In the opposite limit the magnetic moment rotates within the particle while its easy axis being nearly parallel to the external field direction oscillates. The kinetic equations are generalized to include thermal fluctuations. This leads to a significant increase of the power absorption in the low and intermediate field region with a pronounced absorption peak as function of particle size. In the high field region, on the other hand, the inclusion of thermal fluctuations reduces the power absorption. The illustrative numerical calculations presented are performed for magnetic parameters typical for iron oxide

Process Characterisation with Monte-Carlo Wave-Functions

We present a numerically efficient method for the characterisation of a quantum process subject to dissipation and noise. The master equation evolution of a maximally entangled state of the quantum system and a non-evolving ancilla system is simulated by Monte-Carlo wave-functions. We show how each stochastic state vectors provides quantities that are readily combined into an average process \chi-matrix. Our method significantly reduces the computational complexity in comparison with standard characterisation methods. It also readily provides an upper bound on the trace distance between the ideal and simulated process based on the evolution of only a single wave function of the entangled system.Comment: 8 pages, 5 figure

Filtering single atoms from Rydberg blockaded mesoscopic ensembles

We propose an efficient method to filter out single atoms from trapped ensembles with unknown number of atoms. The method employs stimulated adiabatic passage to reversibly transfer a single atom to the Rydberg state which blocks subsequent Rydberg excitation of all the other atoms within the ensemble. This triggers the excitation of Rydberg blockaded atoms to short lived intermediate states and their subsequent decay to untrapped states. Using an auxiliary microwave field to carefully engineer the dissipation, we obtain a nearly deterministic single-atom source. Our method is applicable to small atomic ensembles in individual microtraps and in lattice arrays

Exploring Integral Image Word Length Reduction Techniques for SURF Detector

Speeded Up Robust Features (SURF) is a state of the art computer vision algorithm that relies on integral image representation for performing fast detection and description of image features that are scale and rotation invariant. Integral image representation, however, has major draw back of large binary word length that leads to substantial increase in memory size. When designing a dedicated hardware to achieve real-time performance for the SURF algorithm, it is imperative to consider the adverse effects of integral image on memory size, bus width and computational resources. With the objective of minimizing hardware resources, this paper presents a novel implementation concept of a reduced word length integral image based SURF detector. It evaluates two existing word length reduction techniques for the particular case of SURF detector and extends one of these to achieve more reduction in word length. This paper also introduces a novel method to achieve integral image word length reduction for SURF detector.Comment: ICCEE 200

On-Board Vision Processing For Small UAVs: Time to Rethink Strategy

The ultimate research goal for unmanned aerial vehicles (UAVs) is to facilitate autonomy of operation. Research in the last decade has highlighted the potential of vision sensing in this regard. Although vital for accomplishment of missions assigned to any type of unmanned aerial vehicles, vision sensing is more critical for small aerial vehicles due to lack of high precision inertial sensors. In addition, uncertainty of GPS signal in indoor and urban environments calls for more reliance on vision sensing for such small vehicles. With off-line processing does not offer an attractive option in terms of autonomy, these vehicles have been challenging platforms to implement vision processing onboard due to their strict payload capacity and power budget. The strict constraints drive the need for new vision processing architectures for small unmanned aerial vehicles. Recent research has shown encouraging results with FPGA based hardware architectures. This paper reviews the bottle necks involved in implementing vision processing on-board, advocates the potential of hardware based solutions to tackle strict constraints of small unmanned aerial vehicles and finally analyzes feasibility of ASICs, Structured ASICs and FPGAs for use on future systems.Comment: 2009 NASA/ESA Conference on Adaptive Hardware and System

Lagrangean Approach to Gauge Symmetries for Mixed Constrained Systems and the Dirac Conjecture

The gauge symmetries of a general dynamical system can be systematically obtained following either a Hamiltonean or a Lagrangean approach. In the former case, these symmetries are generated, according to Dirac's conjecture, by the first class constraints. In the latter approach such local symmetries are reflected in the existence of so called gauge identities. The connection between the two becomes apparent, if one works with a first order Lagrangean formulation. We thereby confirm Dirac's conjecture. Our analysis applies to arbitrary constrained systems with first and second class constraints, and thus extends a previous analysis by one of the authors to such general systems. We illustrate our general results in terms of several examples.Comment: 28 pages, LaTe

From the BRST invariant Hamiltonian to the Field-Antifield Formalism

We study the relation between the lagrangian field-antifield formalism and the BRST invariant phase space formulation of gauge theories. Starting from the Batalin-Fradkin-Vilkovisky unitarized action, we demonstrate in a deductive way the equivalence of the phase space, and the lagrangian field-antifield partition functions for the case of irreducible first rank theories.Comment: 14 page

On Quantile Risk Measures and Their Domain

In the present paper we study quantile risk measures and their domain. Our starting point is that, for a probability measure $Q$ on the open unit interval and a wide class $\mathcal{L}_Q$ of random variables, we define the quantile risk measure $\varrho_Q$ as the map which integrates the quantile function of a random variable in $\mathcal{L}_Q$ with respect to $Q$. The definition of $\mathcal{L}_Q$ ensures that $\varrho_Q$ cannot attain the value $+\infty$ and cannot be extended beyond $\mathcal{L}_Q$ without losing this property. The notion of a quantile risk measure is a natural generalization of that of a spectral risk measure and provides another view at the distortion risk measures generated by a distribution function on the unit interval. In this general setting, we prove several results on quantile or spectral risk measures and their domain with special consideration of the expected shortfall