Urban vehicular traffic: fitting the data using a hybrid stochastic model. Part II

In this second part of our research we used the models presented in \emph{Modeling a vehicular traffic network. Part I} \cite{ogm1} to perform an analysis of the urban traffic as recorded by cameras distributed in a chosen sector of Tigre, a city in the province of Buenos Aires, Argentina. We found that the circulation of vehicles -- the traffic dynamics --, along a whole day, can be described by a hybrid model that is an adapted blend of model 2, for an open linear system, with model 3, which is nonlinear, developed in Part I. The objectives of this work were, firstly, to verify whether the vehicular flux can be modeled as an $n$-step stochastic process for its evolution, $n$ for the time. Secondly, to find out if the model, with its parameters fixed to describe the traffic of a single day, may adequately describe the traffic in other days. Thirdly, to propose changes in the already established set of the urban traffic rules in order to optimize the vehicular flow and to diminish the average time that a vehicle stays idle at the semaphores. We estimate that the goals were achieved satisfactorily within the margins of the experimental errors of the gathered data.Comment: 12 pages, 11 figure

Overcoming device unreliability with continuous learning in a population coding based computing system

The brain, which uses redundancy and continuous learning to overcome the unreliability of its components, provides a promising path to building computing systems that are robust to the unreliability of their constituent nanodevices. In this work, we illustrate this path by a computing system based on population coding with magnetic tunnel junctions that implement both neurons and synaptic weights. We show that equipping such a system with continuous learning enables it to recover from the loss of neurons and makes it possible to use unreliable synaptic weights (i.e. low energy barrier magnetic memories). There is a tradeoff between power consumption and precision because low energy barrier memories consume less energy than high barrier ones. For a given precision, there is an optimal number of neurons and an optimal energy barrier for the weights that leads to minimum power consumption

Semiconductor quantum dot - a quantum light source of multicolor photons with tunable statistics

We investigate the intensity correlation properties of single photons emitted from an optically excited single semiconductor quantum dot. The second order temporal coherence function of the photons emitted at various wavelengths is measured as a function of the excitation power. We show experimentally and theoretically, for the first time, that a quantum dot is not only a source of correlated non-classical monochromatic photons but is also a source of correlated non-classical \emph{multicolor} photons with tunable correlation properties. We found that the emitted photon statistics can be varied by the excitation rate from a sub-Poissonian one, where the photons are temporally antibunched, to super-Poissonian, where they are temporally bunched.Comment: 4 pages, 2 figure

Smooth quantum-classical transition in photon subtraction and addition processes

Recently Parigi et al. [Science 317, 1890 (2007)] implemented experimentally the photon subtraction and addition processes from/to a light field in a conditional way, when the required operations were produced successfully only upon the positive outcome of a separate measurement. It was verified that for a low intensity beam (quantum regime) the bosonic annihilation operator does indeed describe a single photon subtraction, while the creation operator describes a photon addition. Nonetheless, the exact formal expressions for these operations do not always reduce to these simple identifications, and in this connection here we deduce the general superoperators for multiple photons subtraction and addition processes and analyze the statistics of the resulting states for classical field states having an arbitrary intensity. We obtain closed analytical expressions and verify that for classical fields with high intensity (classical regime) the operators that describe photon subtraction and addition processes deviate significantly from simply annihilation and creation operators. Complementarily, we analyze in details such a smooth quantum-classical transition as function of beam intensity for both processes.Comment: 7 pages, 5 figures. To appear in Phys. Rev.

Collisional Semiclassical Aproximations in Phase-Space Representation

The Gaussian Wave-Packet phase-space representation is used to show that the expansion in powers of $\hbar$ of the quantum Liouville propagator leads, in the zeroth order term, to results close to those obtained in the statistical quasiclassical method of Lee and Scully in the Weyl-Wigner picture. It is also verified that propagating the Wigner distribution along the classical trajectories the amount of error is less than that coming from propagating the Gaussian distribution along classical trajectories.Comment: 20 pages, REVTEX, no figures, 3 tables include

Engineering Quantum Jump Superoperators for Single Photon Detectors

We study the back-action of a single photon detector on the electromagnetic field upon a photodetection by considering a microscopic model in which the detector is constituted of a sensor and an amplification mechanism. Using the quantum trajectories approach we determine the Quantum Jump Superoperator (QJS) that describes the action of the detector on the field state immediately after the photocount. The resulting QJS consists of two parts: the bright counts term, representing the real photoabsorptions, and the dark counts term, representing the amplification of intrinsic excitations inside the detector. First we compare our results for the counting rates to experimental data, showing a good agreement. Then we point out that by modifying the field frequency one can engineer the form of QJS, obtaining the QJS's proposed previously in an ad hoc manner