We introduce an approach to implement full coherent control on nanometer length scales. It is based on spatiotemporal modulation of the surface plasmon polariton (SPP) fields at the thick edge of a nanowedge. The SPP wavepackets propagating toward the sharp edge of this nanowedge are compressed and adiabatically concentrated at a nanofocus, forming an ultrashort pulse of local fields. The profile of the focused waveform as a function of time and one spatial dimension is completely coherently controlled. We establish the principal limits for the nanoconcentration of the terahertz (THz) radiation in metal/dielectric waveguides and determine their optimum shapes required for this nanoconcentration. We predict that the adiabatic compression of THz radiation from the initial spot size of vacuum wavelength ~300 μm to the unprecedented final size of 100-250 nm can be achieved, while the THz radiation intensity is increased by a factor of 10 to 250. This THz energy nanoconcentration will not only improve the spatial resolution and increase the signal/noise ratio for THz imaging and spectroscopy, but in combination with the recently developed sources of powerful THz pulses, will allow the observation of nonlinear THz effects and a variety of nonlinear spectroscopies (such as two-dimensional spectroscopy), which are highly informative. This should find a wide spectrum of applications in science, engineering, biomedical research and environmental monitoring. We also develop a theory of the spoof plasmons propagating at the interface between a dielectric and a real conductor. The deviation from a perfect conductor is introduced through a finite skin depth. The possibilities of guiding and focusing of spoof plasmons are considered. Geometrical parameters of the structure are found which provide a good guiding of such modes. Moreover, the limit on the concentration by means of planar spoof plasmons in case of non-ideal metal is established. These properties of spoof plasmons are of great interest for THz technology.

Yes / This paper presents a novel on-chip antenna using standard CMOS-technology based on metasurface implemented on two-layers polyimide substrates with a thickness of 500 μm. The aluminium ground-plane with thickness of 3 μm is sandwiched between the two-layers. Concentric dielectric-rings are etched in the ground-plane under the radiation patches implemented on the top-layer. The radiation patches comprise concentric metal-rings that are arranged in a 3 × 3 matrix. The antennas are excited by coupling electromagnetic energy through the gaps of the concentric dielectric-rings in the ground-plane using a microstrip feedline created on the bottom polyimide-layer. The open-ended feedline is split in three-branches that are aligned under the radiation elements to couple the maximum energy. In this structure, the concentric metal-rings essentially act as series left-handed capacitances CL that extend the effective aperture area of the antenna without affecting its dimensions, and the concentric dielectric rings etched in the ground-plane act as shunt left-handed inductors LL, which suppress the surface-waves and reduce the substrates losses that leads to improved bandwidth and radiation properties. The overall structure behaves like a metasurface that is shown to exhibit a very large bandwidth of 0.350–0.385 THz with an average radiation gain and efficiency of 8.15dBi and 65.71%, respectively. It has dimensions of 6 × 6 × 1 mm3 that makes it suitable for on-chip implementation. / This work is partially supported by RTI2018-095499-B-C31, Funded by Ministerio de Ciencia, Innovación y Universidades, Gobierno de España (MCIU/AEI/FEDER,UE), and innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424 and the fnancial support from the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/E022936/1. / Research Development Fund Publication Prize Award winner, March 2020

L’objectif de cette thèse était d’appliquer des méthodes d’analyse multivariées au traitement des données provenant de la spectroscopie de plasma induit par laser (LIBS) et de la spectroscopie térahertz (THz) dans le but d’accroître les performances analytiques de ces techniques.Les spectres LIBS provenaient de campagnes de mesures directes sur différents sites géologiques. Une approche univariée n’a pas été envisageable à cause d’importants effets de matrices et c’est pour cela qu’on a analysé les données provenant des spectres LIBS par réseaux de neurones artificiels (ANN). Cela a permis de quantifier plusieurs éléments mineurs et majeurs dans les échantillons de sol avec un écart relatif de prédiction inférieur à 20% par rapport aux valeurs de référence, jugé acceptable pour des analyses sur site. Dans certains cas, il a cependant été nécessaire de prendre en compte plusieurs modèles ANN, d’une part pour classer les échantillons de sol en fonction d’un seuil de concentration et de la nature de leur matrice, et d’autre part pour prédire la concentration d’un analyte. Cette approche globale a été démontrée avec succès dans le cas particulier de l’analyse du plomb pour un échantillon de sol inconnu. Enfin, le développement d’un outil de traitement par ANN a fait l’objet d’un transfert industriel.Dans un second temps, nous avons traité des spectres d’absorbance terahertz. Ce spectres provenaient de mesures d’absorbance sur des mélanges ternaires de Fructose-Lactose-acide citrique liés par du polyéthylène et préparés sous forme de pastilles. Une analyse semi-quantitative a été réalisée avec succès par analyse en composantes principales (ACP). Puis les méthodes quantitatives de régression par moindres carrés partiels (PLS) et de réseaux de neurons artificiels (ANN) ont permis de prédire les concentrations de chaque constituant de l’échantillon avec une valeur d’erreur quadratique moyenne inférieure à 0.95 %. Pour chaque méthode de traitement, le choix des données d’entrée et la validation de la méthode ont été discutés en détail. / The aim of this work was the application of multivariate methods to analyze spectral data from laser-induced breakdown spectroscopy (LIBS) and terahertz (THz) spectroscopy to improve the analytical ability of these techniques.In this work, the LIBS data were derived from on-site measurements of soil samples. The common univariate approach was not efficient enough for accurate quantitative analysis and consequently artificial neural networks (ANN) were applied. This allowed quantifying several major and minor elements into soil samples with relative error of prediction lower than 20% compared to reference values. In specific cases, a single ANN model didn’t allow to successfully achieving the quantitative analysis and it was necessary to exploit a series of ANN models, either for classification purpose against a concentration threshold or a matrix type, or for quantification. This complete approach based on a series of ANN models was efficiently applied to the quantitative analysis of unknown soil samples. Based on this work, a module of data treatment by ANN was included into the software Analibs of the IVEA company. The second part of this work was focused on the data treatment of absorbance spectra in the terahertz range. The samples were pressed pellets of mixtures of three products, namely fructose, lactose and citric acid with polyethylene as binder. A very efficient semi-quantitative analysis was conducted by using principal component analysis (PCA). Then, quantitative analyses based on partial least squares regression (PLS) and ANN allowed quantifying the concentrations of each product with a root mean square error (RMSE) lower than 0.95 %. All along this work on data processing, both the selection of input data and the evaluation of each model have been studied in details.

In this thesis, superconducting nanostructures for quantum detection of electromagnetic radiation are studied. In this regard, electrodynamics of topological excitations in 1D superconducting nanowires and 2D superconducting nanostrips is investigated. Topological excitations in superconducting nanowires and nanostrips lead to crucial deviation from the bulk properties. In 1D superconductors, topological excitations are phase slippages of the order parameter in which the magnitude of the order parameter locally drops to zero and the phase jumps by integer multiple of 2\pi. We investigate the effect of high-frequency field on 1D superconducting nanowires and derive the complex conductivity. Our study reveals that the rate of the quantum phase slips (QPSs) is exponentially enhanced under high-frequency irradiation. Based on this finding, we propose an energy-resolving terahertz radiation detector using superconducting nanowires. In superconducting nanostrips, topological fluctuations are the magnetic vortices. The motion of magnetic vortices result in dissipative processes that limit the efficiency of devices using superconducting nanostrips. It will be shown that in a multi-layer structure, the potential barrier for vortices to penetrate inside the structure is elevated. This results in significant reduction in dissipative process. In superconducting nanowire single photon detectors (SNSPDs), vortex motion results in dark counts and reduction of the critical current which results in low efficiency in these detectors. Based on this finding, we show that a multi-layer SNSPD is capable of approaching characteristics of an ideal single photon detector in terms of the dark count and quantum efficiency. It is shown that in a multi-layer SNSPD the photon coupling efficiency is dramatically enhanced due to the increase in the optical path of the incident photon.