Quantum enhanced probing of multilayered-samples

Quantum sensing exploits quantum phenomena to enhance the detection and estimation of classical parameters of physical systems and biological entities, particularly so as to overcome the inefficiencies of its classical counterparts. A particularly promising approach within quantum sensing is Quantum Optical Coherence Tomography which relies on non-classical light sources to reconstruct the internal structure of multilayered materials. Compared to traditional classical probing, Quantum Optical Coherence Tomography provides enhanced-resolution images and is unaffected by even-order dispersion. One of the main limitations of this technique lies in the appearance of artifacts and echoes, i.e. fake structures that appear in the coincidence interferogram, which hinder the retrieval of information required for tomography scans. Here, by utilizing a full theoretical model, in combination with a fast genetic algorithm to post-process the data, we successfully extract the morphology of complex multilayered samples and thoroughly distinguish real interfaces, artifacts, and echoes. We test the effectiveness of the model and algorithm by comparing its predictions to experimentally-generated interferograms through the controlled variation of the pump wavelength. Our results could potentially lead to the development of practical high-resolution probing of complex structures and non-invasive scanning of photo-degradable materials for biomedical imaging/sensing, clinical applications, and materials science

Researches on Non-standard Optics for Advanced Gravitational Waves Interferometers

This thesis presents a collection of different researches on non-standard optics in view of enhancing the performances of the Advanced Gravitational waves interferometric detectors, where the thermal noise of the test masses is expected to be a limiting factor for their sensitivity. We provide a quantitative analysis of the impact of non-Gaussian beams on different kinds of thermal noises. We developed the theory of mesa beam, in view of a future implementation in advanced GW interferometers of the mesa beam idea, focusing on the analytical derivation of the quantities (i.e. beam width, divergence, propagation factor), which are chosen as ISO standard reference parameters for the characterization of an optical beam. We also analytically proved a new duality relation between optical cavities with non-spherical mirrors. The interest of the GW community in this new beam technology led us to the construction and testing of a prototype mesa beam Fabry-Perot cavity with Mexican-hat mirror. Part of the work of this thesis was devoted to the development of new simulation programs of optical systems. These programs provided the theoretical expected behaviour of our experiment, in particular cavity modes structure and misalignments sensitivity to be confronted with the experimental results. We also explored another complementary way of reducing the mirror thermal noise, beside the beam shaping, that is the multi-layered coating thickness optimization. We show it to be effective in reducing the coating noise and explore the possible implications for GW interferometers in terms of sensitivity. During this analysis we developed an independent model for the coating effective elastic parameters, which is based on the well understood subject of homogenization theory.Comment: Ph.D. thesis, University of Pisa & LIGO-Caltech, 185 page

An Investigation of Interference Lithography Applications using Evanescent Fields

Since the dawn of large scale integrated circuitry photolithography has been the primary means of pattern production. Over the following 60 years the size of these patterns has shrunk massively, along with the consequent increase in the complexity of the photolithography process. The demand for smaller, more powerful, and more energy efficient computational devices requires further shrinking of the patterns. The development of processes for further pattern size reduction however is not a simple one, thus a great deal of research and investments has been focused towards it. The research within this thesis is aimed at discovering new methods and techniques for photolithography pattern reduction by exploiting fields in an interference lithography setting. Previously it was shown that dielectric resonant underlayers could be employed to enhance the depth of field for evanescent interference lithography. This however is limited by the availability of transparent high refractive index dielectric layers. To extend this to higher effective refractive indices an investigation into applying Herpin effective media within resonant underlayers was carried out. These underlayers were shown to be effective for combinations which have propagating fields within at least one layer; for combinations where all layers were evanescent however, the method broke down. Investigations into generic resonant underlayers also led to the development of a resonant overlayer method for increasing the evanescent field strength within a PR layer while allowing thicker and/or lower refractive index IMLs. Further to this a new form of BARC for hyper-NA photolithography termed an evanescent-coupled ARC was developed. These ARCs rely on evanescently-coupled dielectric or surface state polariton resonators to produce destructive interference within the PR. The properties and design constraints for each of these systems was explored and two experimental designs developed. Experiment verification of evanescent-coupled ARCs was successfully demonstrated for a SiO2jHfO2 dielectric resonator based ARC. Demonstration of a MgF2jCr surface state polariton resonator based ARC was partially demonstrated with resonance within the underlayer and the consequent alteration of the PR standing wave pattern observed. The use of prism coupling for interference lithography is limited by the maximum refractive index of the coupling prism; above this refractive index all fields are evanescent and no energy will coupled into the PR. To overcome this limit grating coupled evanescent near-field interference lithography methods are employed. The higher order diffraction orders from the grating can have NAs far greater than the refractive index of naturally occurring materials, thus patterning with these diffraction orders produces far smaller interference pitches than prism coupled systems are capable of. Grating coupled systems involve the use of evanescent fields, plasmonic resonances,as well as coupled resonators all within subwavelength scales, consequently simulation and optimization of these systems is very computationally intensive. To improve this a genetic algorithm process was applied to reduce the computational time for optimization, and to allow the use of an inverse design process. Application of this method produced an order of magnitude improvement in optimization time compared to a full parameter sweep. Models including resonant overlayers, overlayers and underlayers, as well as those employing extremely high NAs and/or higher |m| diffraction orders were produced. Simulations showed that extremely high NAs up to 20 may theoretically be used for patterning of structures with a pitch of lambda/40 equating to a full pitch of 10.1 nm with an exposing wavelength of 405 nm

Design and Optimisation of Optical Metasurfaces Using Deep Learning

This thesis centres on the design, processing, and fabrication of tunable optical metamaterials. It incorporates physics-based simulation, deep learning (DL), and thin film fabrication techniques to offer a comprehensive exploration of the field of optical metamaterials. Placing stiff resonators on a flexible substrate is a common type of mechanically tunable metasurface, whose optical responses are tuned by dynamically adjusting the spacing between resonators by applying mechanical force. However, the significant modulus mismatch between materials causes stress concentration at the interface, leading to crack propagation and delamination at lower strain levels (20-50%), and limiting the optical tunability of the structure. To address this challenge, we propose two designs to manipulate stress distribution. Under mechanical force, the structure enables localised deformation, redirecting stress from critical areas. This mechanism minimises the accumulation of stress in the interface, thereby diminishing the risk of material failure and improving stretchability up to 120% compared to traditional designs. This extreme stretchability leads to a 143 nm resonance shift, which is almost twice as large as that of conventional geometry. A universal machine learning (ML)-based approach was developed to optimise the metasurface design across three key aspects: geometric parameters, material development, and free-form shape configuration. In design parameters optimisation, a fully connected neural network (FCNN) was developed with a mean absolute error (MAE) of 0.0051, recommending a single geometry with a 104 order of magnitude decrease in computational time when compared to finite element method (FEM) simulations used for data generation. The suggested structure provides extensive coverage of the colour space, encompassing 27.65% of the standard RGB (sRGB) space. For the materials development part, an inverse design (ID) network was combined with effective medium approximation (EMA), navigating infinite materials composition space to identify new compositions for custom applications. The last network was tasked to explore boundless free-form shape space to propose the one for the on-demand optical properties with MAE of 0.21. The accuracy of all networks was experimentally validated

Defect and thickness inspection system for cast thin films using machine vision and full-field transmission densitometry

Quick mass production of homogeneous thin film material is required in paper, plastic, fabric, and thin film industries. Due to the high feed rates and small thicknesses, machine vision and other nondestructive evaluation techniques are used to ensure consistent, defect-free material by continuously assessing post-production quality. One of the fastest growing inspection areas is for 0.5-500 micrometer thick thin films, which are used for semiconductor wafers, amorphous photovoltaics, optical films, plastics, and organic and inorganic membranes. As a demonstration application, a prototype roll-feed imaging system has been designed to inspect high-temperature polymer electrolyte membrane (PEM), used for fuel cells, after being die cast onto a moving transparent substrate. The inspection system continuously detects thin film defects and classifies them with a neural network into categories of holes, bubbles, thinning, and gels, with a 1.2% false alarm rate, 7.1% escape rate, and classification accuracy of 96.1%. In slot die casting processes, defect types are indicative of a misbalance in the mass flow rate and web speed; so, based on the classified defects, the inspection system informs the operator of corrective adjustments to these manufacturing parameters. Thickness uniformity is also critical to membrane functionality, so a real-time, full-field transmission densitometer has been created to measure the bi-directional thickness profile of the semi-transparent PEM between 25-400 micrometers. The local thickness of the 75 mm x 100 mm imaged area is determined by converting the optical density of the sample to thickness with the Beer-Lambert law. The PEM extinction coefficient is determined to be 1.4 D/mm and the average thickness error is found to be 4.7%. Finally, the defect inspection and thickness profilometry systems are compiled into a specially-designed graphical user interface for intuitive real-time operation and visualization.M.S.Committee Chair: Tequila Harris; Committee Member: Levent Degertekin; Committee Member: Wayne Dale