Casimir Effect and Global Theory of Boundary Conditions

The consistency of quantum field theories defined on domains with external borders imposes very restrictive constraints on the type of boundary conditions that the fields can satisfy. We analyse the global geometrical and topological properties of the space of all possible boundary conditions for scalar quantum field theories. The variation of the Casimir energy under the change of boundary conditions reveals the existence of singularities generically associated to boundary conditions which either involve topology changes of the underlying physical space or edge states with unbounded below classical energy. The effect can be understood in terms of a new type of Maslov index associated to the non-trivial topology of the space of boundary conditions. We also analyze the global aspects of the renormalization group flow, T-duality and the conformal invariance of the corresponding fixed points.Comment: 11 page

Modelling and Nonlinear Model Predictive Control of a Twin Screw Feeder

In this work, a dynamic model of a twin screw feeder, for continuous tablet manufacturing, has been developed. In particular, a First Order Plus Dead Time (FOPDT) model has been suggested. The delayed dynamics depends on operating conditions, equipment design and physical properties of the bulk solid. Model parameters are estimated by fitting the model to experimental data. Due to the nonlinear input-output relationships and the time delays involved, a Nonlinear Model Predictive Control (NMPC) is investigated to maintain an accurate mass flow rate, with the ultimate goal to improve product homogeneity in an inherently complex process. The performance of the designed control system is found to be satisfactory in a wide operating range and its potential use in a continuous manufacturing process is worth being investigated in the future

Unit-cell design for antenna arrays efficiently matched to uni-travelling-carrier photodiodes

International audienceWe present an antenna array with a backing reflector that allows one to obtain efficient matching to integrated sources or loads with low input resistance. In the infinite array limit, it is possible to describe the proposed unit-cell as an equivalent network with closed-form expressions for its different constituents. This analytic approach enables the preliminary design of arrays with improved matching efficiency for optimum power transmission/reception. The proposed solution has enabled an improved matching to a uni-travelling-carrier photodiode with a maximum improvement of 3 dB in the radiated power with respect to a 72-Ω antenna, and featuring a 50% bandwidth

Single trajectory characterization via machine learning

[EN] In order to study transport in complex environments, it is extremely important to determine the physical mechanism underlying diffusion and precisely characterize its nature and parameters. Often, this task is strongly impacted by data consisting of trajectories with short length (either due to brief recordings or previous trajectory segmentation) and limited localization precision. In this paper, we propose a machine learning method based on a random forest architecture, which is able to associate single trajectories to the underlying diffusion mechanism with high accuracy. In addition, the algorithm is able to determine the anomalous exponent with a small error, thus inherently providing a classification of the motion as normal or anomalous (sub- or super-diffusion). The method provides highly accurate outputs even when working with very short trajectories and in the presence of experimental noise. We further demonstrate the application of transfer learning to experimental and simulated data not included in the training/test dataset. This allows for a full, high-accuracy characterization of experimental trajectories without the need of any prior information.This work has been funded by the Spanish Ministry MINECO (National Plan 15 Grant: FISICATEAMO No. FIS2016-79508-P, SEVEROOCHOA No. SEV-2015-0522, FPI), European Social Fund, Fundacio Cellex, Generalitat de Catalunya (AGAUR Grant No. 2017 SGR 1341 and CERCA/Program), ERC AdG OSYRIS, EU FETPRO QUIC, and the National Science Centre, Poland-Symfonia Grant No. 2016/20/W/ST4/00314. CM acknowledges funding from the Spanish Ministry of Economy and Competitiveness and the European Social Fund through the Ramon y Cajal program 2015 (RYC-2015-17896) and the BFU2017-85693-R and from the Generalitat de Catalunya (AGAUR Grant No. 2017SGR940). GM acknowledges financial support from Fundacio Social La Caixa. MAGM acknowledges funding from the Spanish Ministry of Education and Vocational Training (MEFP) through the Beatriz Galindo program 2018 (BEAGAL18/00203). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU.Munoz-Gil, G.; Garcia March, MA.; Manzo, C.; Martin-Guerrero, JD.; Lewenstein, M. (2020). Single trajectory characterization via machine learning. New Journal of Physics. 22(1):1-9. https://doi.org/10.1088/1367-2630/ab6065S1922

Negative differential resistance in molecular junctions: application to graphene ribbon junctions

Using self-consistent calculations based on Non-Equilibrium Green's Function (NEGF) formalism, the origin of negative differential resistance (NDR) in molecular junctions and quantum wires is investigated. Coupling of the molecule to electrodes becomes asymmetric at high bias due to asymmetry between its highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) levels. This causes appearance of an asymmetric potential profile due to a depletion of charge and reduction of screening near the source electrode. With increasing bias, this sharp potential drop leads to an enhanced localization of the HOMO and LUMO states in different parts of the system. The reduction in overlap, caused by localization, results in a significant reduction in the transmission coefficient and current with increasing bias. An atomic chain connected to two Graphene ribbons was investigated to illustrate these effects. For a chain substituting a molecule, an even-odd effect is also observed in the NDR characteristics.Comment: 8 pages, 8 figure