Dynamics of a pulsed continuous variable quantum memory

We study the transfer dynamics of non-classical fluctuations of light to the ground-state collective spin components of an atomic ensemble during a pulsed quantum memory sequence, and evaluate the relevant physical quantities to be measured in order to characterize such a quantum memory. We show in particular that the fluctuations stored into the atoms are emitted in temporal modes which are always different than those of the readout pulse, but which can nevertheless be retrieved efficiently using a suitable temporal mode-matching technique. We give a simple toy model - a cavity with variable transmission - which accounts for the behavior of the atomic quantum memory.Comment: 6 pages, 5 figure

Atomic quantum memory: cavity vs single pass schemes

This paper presents a quantum mechanical treatment for both atomic and field fluctuations of an atomic ensemble interacting with propagating fields, either in Electromagnetically Induced Transparency or in a Raman situation. The atomic spin noise spectra and the outgoing field spectra are calculated in both situations. For suitable parameters both EIT and Raman schemes efficiently preserve the quantum state of the incident probe field in the transfer process with the atoms, although a single pass scheme is shown to be intrinsically less efficient than a cavity scheme

Extending Linear System Models to Characterize the Performance Bounds of a Fixating Active Vision System

If active vision systems are to be used reliably in practical applications, it is crucial to understand their limits and failure modes. In the work presented here, we derive, theoretically and experimentally, bounds on the performance of an active vision system in a fixation task. In particular, we characterize the tracking limits that are imposed by the finite field of view. Two classes of target motion are examined: sinusoidal motions, representative for targets moving with high turning rates, and constant-velocity motions, exemplary for slowly varying target movements. For each class of motion, we identify a linear model of the fixating system from measurements on a real active vision system and analyze the range of target motions that can be handled with a given field of view. To illustrate the utility of such performance bounds, we sketch how the tracking performance can be maximized by dynamically adapting optical parameters of the system to the characteristics of the target motion. The originality of our work arises from combining the theoretical analysis of a complete active vision system with rigorous performance measurements on the real system. We generate repeatable and controllable target motions with the help of two robot manipulators and measure the real-time performance of the system. The experimental results are used to verify or identify a linear model of the active vision system. A major difference to related work lies in analyzing the limits of the linear models that we develop. Active vision systems have been modeled as linear systems many times before, but the performance limits at which the models break down and the system loses its target have not attracted much attention so far. With our work we hope to demonstrate how the knowledge of such limits can be used to actually extend the performance of an active vision system

Consistent Approximations for the Optimal Control of Constrained Switched Systems

Though switched dynamical systems have shown great utility in modeling a variety of physical phenomena, the construction of an optimal control of such systems has proven difficult since it demands some type of optimal mode scheduling. In this paper, we devise an algorithm for the computation of an optimal control of constrained nonlinear switched dynamical systems. The control parameter for such systems include a continuous-valued input and discrete-valued input, where the latter corresponds to the mode of the switched system that is active at a particular instance in time. Our approach, which we prove converges to local minimizers of the constrained optimal control problem, first relaxes the discrete-valued input, then performs traditional optimal control, and then projects the constructed relaxed discrete-valued input back to a pure discrete-valued input by employing an extension to the classical Chattering Lemma that we prove. We extend this algorithm by formulating a computationally implementable algorithm which works by discretizing the time interval over which the switched dynamical system is defined. Importantly, we prove that this implementable algorithm constructs a sequence of points by recursive application that converge to the local minimizers of the original constrained optimal control problem. Four simulation experiments are included to validate the theoretical developments

Visual Observation of a Moving Agent

We address the problem of observing a moving agent. In particular, we propose a system for observing a manipulation process, where a robot hand manipulates an object. A discrete event dynamic systems (DEDS) frame work is developed for the hand/object interaction over time and a stabilizing observer is constructed. Low-level modules are developed for recognizing the events that causes state transitions within the dynamic manipulation system. The work examines closely the possibilities for errors, mistakes and uncertainties in the manipulation system, observer construction process and event identification mechanisms. The system utilizes different tracking techniques in order to observe and recognize the task in an active, adaptive and goal-directed manner

Underestimation of Visual Texture Slant by Human Observers: A Model

The perspective image of an obliquely inclined textured surface exhibits shape and density distortions of texture elements which allow a human observer to estimate the inclination angle of the surface. However, since the work of Gibson (1950) it has been known that, in the absence of other cues, humans tend to underestimate the slant angle of the surface, particularly when the texture is perceived as being irregular. The perspective distortions which affect texture elements also shift the projected spatial frequencies of the texture in systematic ways. Using a suitable local spectral filter to measure these frequency gradients, the inclination angle of the surface may be estimated. A computational model has been developed which performs this task using distributions of outputs from filters found to be a good description of simple cell receptive fields. However, for irregular textures the filter output distributions are more like those of regular textures at shallower angles of slant, leading the computational algorithm to underestimate the slant angle. This behavioral similarity between human and algorithm suggests the possibility that a similar visual computation is performed in cortex

Estimation of Textured Surface Inclination by Parallel Local Spectral Analysis

When an inclined, uniformly textured surface is viewed by an observer or imaged by a camera, the systematic distortions of the perspective transformation will induce a predictable distribution of shifts in the projected spatial frequencies which compose the texture. By measuring these shifts using a set of filters having suitable spatial, frequency, and orientation resolution, the inclination angles of the original textured surface may be estimated. An algorithm is presented which uses the amplitude distributions of 2D Gabor filters to perform such a calculation. Central to the algorithm is a pair of iteratively executed routines. The fist adjusts local sets of parameters to reduce the error between predicted and measured filter amplitudes. The second propagates the local parameters to neighboring regions to consolidate the estimates of inclination. The algorithm is capable of operating in parallel on any number of regions in the image and with a diverse set of filter inputs

Technique of quantum state transfer for a double Lambda atomic beam

The transfer technique of quantum states from light to collective atomic excitations in a double $\Lambda$ type system is extended to matter waves in this paper, as a novel scheme towards making a continuous atom laser. The intensity of the output matter waves is found to be determined by the initial relative phase of the two independent coherent probe lights, which may indicate an interesting method for the measurement of initial relative phase of two independent light sources.Comment: 5 pages, 2 figure

Receptive Fields for the Determination of Textured Surface Inclination

The image of a uniformly textured inclined surface exhibits systematic distortions which affect the projection of the spatial frequencies of which the texture is composed. Using a set of filters having suitable spatial, frequency and orientation resolution, the inclination angle of the textured surface may be estimated from the resulting spatial frequency gradients. Psychophysical experiments suggest that, in absence of other cues, humans perceive surface inclination from perspective distortions, suggesting the possibility of a specific neuronal mechanism in the visual system. Beginning with a low level filter model found to be an accurate and economical model for simple cell receptive fields, we have developed both algorithmic machine vision and neural network models to investigate physiologically plausible mechanisms for this behavior. The two models are related through a new class of receptive field formed in the hidden layer of a neural network which learned to solve the problem. This receptive field can also be described analytically from the analysis developed for the algorithmic study. This paper, then, offers a prediction for a new type of receptive field in cortex which may be involved in the perception of inclined textured surfaces