Energy-momentum tensor in thermal strong-field QED with unstable vacuum

The mean value of the one-loop energy-momentum tensor in thermal QED with electric-like background that creates particles from vacuum is calculated. The problem differes essentially from calculations of effective actions (similar to that of Heisenberg--Euler) in backgrounds that do not violate the stability of vacuum. The role of a constant electric background in the violation of both the stability of vacuum and the thermal character of particle distribution is investigated. Restrictions on the electric field and its duration under which one can neglect the back-reaction of created particles are established.Comment: 7 pages, Talk presented at Workshop "Quantum Field Theory under the Influence of External Conditions", Leipzig, September 17-21, 2007; introduction extended, version accepted for publication in J.Phys.

Light deflection in Weyl gravity: critical distances for photon paths

The Weyl gravity appears to be a very peculiar theory. The contribution of the Weyl linear parameter to the effective geodesic potential is opposite for massive and nonmassive geodesics. However, photon geodesics do not depend on the unknown conformal factor, unlike massive geodesics. Hence light deflection offers an interesting test of the Weyl theory. In order to investigate light deflection in the setting of Weyl gravity, we first distinguish between a weak field and a strong field approximation. Indeed, the Weyl gravity does not turn off asymptotically and becomes even stronger at larger distances. We then take full advantage of the conformal invariance of the photon effective potential to provide the key radial distances in Weyl gravity. According to those, we analyze the weak and strong field regime for light deflection. We further show some amazing features of the Weyl theory in the strong regime.Comment: 20 pages, 9 figures (see published version for a better resolution, or online version at stacks.iop.org/CQG/21/1897

Long-distance radiative coupling between quantum dots in photonic crystal dimers

We study the mutual interaction between two identical quantum dots coupled to the normal modes of two-site photonic crystal molecules in a planar waveguide geometry, i.e. photonic crystal dimers. We find that the radiative coupling between the two quantum emitters is maximized when they are in resonance with either the bonding or the antibonding modes of the coupled cavity system. Moreover, we find that such effective interdot coupling is sizable, in the meV range, and almost independent from the cavities distance, as long as a normal mode splitting exceeding the radiative linewidth can be established (strong cavity-cavity coupling condition). In realistic and high quality factor photonic crystal cavity devices, such distance can largely exceed the emission wavelength, which is promising for long distance entanglement generation between two qubits in an integrated nanophotonic platform. We show that these results are robust against position disorder of the two quantum emitters within their respective cavities.Comment: 10 pages, 6 figure

Parametric and nonparametric identification of shell and tube heat exchanger mathematical model

Parametric and nonparametric models of a shell and tube heat exchanger are studied. Such models are very important because they provide information about controlling a system operation. Without the model, the control task would be difficult for tuning of controller. For many years, researchers have studied these models; however, their models are still less satisfactory since they are not in general form. This problem is caused by two key issues, namely, multiple unknown parameters and highly nonlinear structures. Energy balances have been set-up for condition of unknown parameters which involved, among others, temperature, flow rate, density and heat capacity. The identification process produces a dynamic model of the heat exchanger which is developed based on a lumped parameter system. The model developed is single input single output whereas input signal is hot water flow rate and the output is cold water temperature. The general form of the model obtained could have parametric model structures such as auto regressive with external input, average auto regressive moves with external input, output error or box-jenkins. The study in this thesis aims to solve the general form through parametric and nonparametric models which has been proposed as candidate models. Both candidate models have been implemented and tested by applying several data sets constructed in lab experiments. The first finding is the derivation of the dynamic model in the general form of the transfer function in s domain, and it has been proven that it has parametric model structure. The second finding is the first order without delay time transfer function of the nonparametric model where they have gain is 35.20C and time constant 7200s. These have proven to fulfill that the measured experimental data contains calculated error that is no than more 2%. The third finding is the parametric model obtained has proven that the measured experimental data contains calculated error level that is very satisfactory, i.e. less than 1%. This error has been determined based on the final prediction error for each model structure used. The best model has been chosen, i.e. bj31131. It has the smallest values of the loss function and final prediction error of 0.0023, and it has high values of the best fits, i.e. 96.84%. Parameter optimization has been calculated to determine minimization or maximization of functions which involved the parameter studied. It is used to find a set of design parameters that can in some way be defined as optimal. The first until the third findings are minor contribution while the parameter optimization has been a major contribution

A Predictive Algorithm For Wetlands In Deep Time Paleoclimate Models

Methane is a powerful greenhouse gas produced in wetland environments via microbial action in anaerobic conditions. If the location and extent of wetlands are unknown, such as for the Earth many millions of years in the past, a model of wetland fraction is required in order to calculate methane emissions and thus help reduce uncertainty in the understanding of past warm greenhouse climates. Here we present an algorithm for predicting inundated wetland fraction for use in calculating wetland methane emission fluxes in deep time paleoclimate simulations. The algorithm determines, for each grid cell in a given paleoclimate simulation, the wetland fraction predicted by a nearest neighbours search of modern day data in a space described by a set of environmental, climate and vegetation variables. To explore this approach, we first test it for a modern day climate with variables obtained from observations and then for an Eocene climate with variables derived from a fully coupled global climate model (HadCM3BL-M2.2). Two independent dynamic vegetation models were used to provide two sets of equivalent vegetation variables which yielded two different wetland predictions. As a first test the method, using both vegetation models, satisfactorily reproduces modern data wetland fraction at a course grid resolution, similar to those used in paleoclimate simulations. We then applied the method to an early Eocene climate, testing its outputs against the locations of Eocene coal deposits. We predict global mean monthly wetland fraction area for the early Eocene of 8 to 10 × 106km2 with corresponding total annual methane flux of 656 to 909 Tg, depending on which of two different dynamic global vegetation models are used to model wetland fraction and methane emission rates. Both values are significantly higher than estimates for the modern-day of 4 × 106km2 and around 190Tg (Poulter et. al. 2017, Melton et. al., 2013

Single polymer gating of channels under a solvent gradient

We study the effect of a gradient of solvent quality on the coil-globule transition for a polymer in a narrow pore. A simple self-attracting self-avoiding walk model of a polymer in solution shows that the variation in the strength of interaction across the pore leads the system to go from one regime (good solvent) to the other (poor solvent) across the channel. This may be thought analogous to thermophoresis, where the polymer goes from the hot region to the cold region under the temperature gradient. The behavior of short chains is studied using exact enumeration whilst the behavior of long chains is studied using transfer matrix techniques. The distribution of the monomer density across the layer suggests that a gate-like effect can be created, with potential applications as a sensor.Comment: 5 Pages, 7 Figures, Accepted in Phys. Rev. E (2013