Adiabatic quantum search with atoms in a cavity driven by lasers

We propose an implementation of the quantum search algorithm of a marked item in an unsorted list of N items by adiabatic passage in a cavity-laser-atom system. We use an ensemble of N identical three-level atoms trapped in a single-mode cavity and driven by two lasers. In each atom, the same level represents a database entry. One of the atoms is marked by having an energy gap between its two ground states. Appropriate time delays between the two laser pulses allow one to populate the marked state starting from an initial entangled state within a decoherence-free adiabatic subspace. The time to achieve such a process is shown to exhibit the Grover speedup.Comment: 5 pages, 3 figure

A robust extension to the triple plane pressure mode matching method by filtering convective perturbations

Time-periodic CFD simulations are widely used to investigate turbomachinery components. The triple-plane pressure mode matching method (TPP) developed by Ovenden and Rienstra extracts the acoustic part in such simulations. Experience shows that this method is subject to significant errors when the amplitude of pseudo-sound is high compared to sound. Pseudo-sound are unsteady pressure fluctuations with a convective character. The presented extension to the TPP improves the splitting between acoustics and the rest of the unsteady flow field. The method is simple: i) the acoustic eigenmodes are analytically determined for a uniform mean flow as in the original TPP; ii) the suggested model for convective pressure perturbations uses the convective wavenumber as axial wavenumber and the same orthogonal radial shape functions as for the acoustic modes. The reliability is demonstrated on the simulation data of a low-pressure fan. As acoustic and convective perturbations are separated, the accuracy of the results increases close to sources, allowing a reduction of the computational costs by shortening the simulation domain. The extended method is as robust as the original one--giving the same results for the acoustic modes in absence of convective perturbations.Comment: Accepted 15-05-11 by International Journal of Aeroacoustics to be published in the special issue focusing on turbomachinery aeroacoustic

Quantitative estimates for the long time behavior of an ergodic variant of the telegraph process

Motivated by stability questions on piecewise deterministic Markov models of bacterial chemotaxis, we study the long time behavior of a variant of the classic telegraph process having a non-constant jump rate that induces a drift towards the origin. We compute its invariant law and show exponential ergodicity, obtaining a quantitative control of the total variation distance to equilibrium at each instant of time. These results rely on an exact description of the excursions of the process away from the origin and on the explicit construction of an original coalescent coupling for both velocity and position. Sharpness of the obtained convergence rate is discussed.Comment: Definitive version of former paper "Quantitative estimates for the long time behavior of a PDMP describing the movement of bacteria", now accepted in Advances in Applied Probability. Presentation changed. A diffusive scaling limit result is added. Sharpness of the long-time convergence rate is discussed. 20 pages, 3 figure

Do high-frequency financial data help forecast oil prices? The MIDAS touch at work : [version november 20, 2013]

The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency realtime VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil