Squeezing Optomechanics

Optomechanics studies the interaction between light and a mechanical resonator, enabled via radiation pressure. Employing a high finesse cavity it is possible to enhance this interaction, enabling the possibility of bringing macroscopic objects in a quantum superposition of states and possibly opening the way to the experi- mental study of quantum decoherence. The work carried out in this thesis consists in the developement and improvement of an experimental setup used to perform optomechanics experiment, that in the future will allow to experimentally investi- gate the foundations of quantum mechanics. The first part of this thesis deals with the developement of an optical system for cryogenic applications that matches the Gaussian mode of a SM optical fiber into a high Finesse optical cavity. We will discuss how a prototype has been designed and experimentally tested. In the second section will be investigated a technical problem encountered in the Pound-Drever-Hall (PDH) frequency stabilization setup implemented using optical fibers instead of free space optics. The presence of some wiggles in the PDH error signal, and a time dependent shift of its baseline makes difficult to lock the laser to the cavity for a sufficient amount of time to perform experiments. Numerical simulations and experiments will be performed in order to understand the origin of the problem, and to solve it. The last part of this work consists in the experimental study of the decay of a ther- momechanical squeezed state, a phenomenon that to the knowledge of the author has never been investigated yet. In particular we will create a thermal squeezed state by parametric modulation of the spring constant, and we will study its time evolution after we switch off this parametric modulation.ope

Recupero di frequenza e stima di canale nei sistemi FBMC

Studio di algoritmi per il recupero dell' offset in frequenza,e per la stima di canale, per sistemi FBMC su canali affetti da fadin

What residualizing predictors in regression analyses does (and what it does not do)

Psycholinguists are making increasing use of regression analyses and mixed-effects modeling. In an attempt to deal with concerns about collinearity, a number of researchers orthogonalize predictor variables by residualizing (i.e., by regressing one predictor onto another, and using the residuals as a stand-in for the original predictor). In the current study, the effects of residualizing predictor variables are demonstrated and discussed using ordinary least-squares regression and mixed-effects models. Some of these effects are almost certainly not what the researcher intended and are probably highly undesirable. Most importantly, what residualizing does not do is change the result for the residualized variable, which many researchers probably will find surprising. Further, some analyses with residualized variables cannot be meaningfully interpreted. Hence, residualizing is not a useful remedy for collinearity

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equation for neutral and ionic solutions, respectively. In the present work solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented to the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of a ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency, and allow for the treatment of different boundary conditions, as for example surface systems. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes

Statistical Inference for Ergodic Algorithmic Model (EAM), Applied to Hydrophobic Hydration Processes

Abstract: The thermodynamic properties of hydrophobic hydration processes can be represented in probability space by a Dual‐Structure Partition Function {DS‐PF} = {M‐PF} ∙ {T‐PF}, which is the product of a Motive Partition Function {M‐PF} multiplied by a Thermal Partition Function {T‐PF}. By development of {DS‐PF}, parabolic binding potential functions α) RlnKdual = (–ΔG°dual/T) ={f(1/T)*g(T)} and β) RTlnKdual = (–ΔG°dual) = {f(T)*g(lnT)} have been calculated. The resulting binding functions are “convoluted” functions dependent on the reciprocal interactions between the primary function f(1/T) or f(T) with the secondary function g(T) or g(lnT), respectively. The binding potential functions carry the essential thermodynamic information elements of each system. The analysis of the binding potential functions experimentally determined at different temperatures by means of the Thermal Equivalent Dilution (TED) principle has made possible the evaluation, for each compound, of the pseudo‐stoichiometric coefficient ξw, from the curvature of the binding potential functions. The positive value indicates convex binding functions (Class A), whereas the negative value indicates concave binding function (Class B). All the information elements concern sets of compounds that are very different from one set to another, in molecular dimension, in chemical function, and in aggregation state. Notwithstanding the differences between, surprising equal unitary values of niche (cavity) formation in Class A <hfor>A= –22.7 kJmol−1 ξw−1 sets with standard deviation σ= 3.1% and <sfor>A = –445JK−1mol−1ξw−1JK−1mol−1ξw−1 with standard deviation σ= 0.7%. Other surprising similarities have been found, demonstrating that all the data analyzed belong to the same normal statistical population. The Ergodic Algorithmic Model (EAM) has been applied to the analysis of important classes of reactions, such as thermal and chemical denaturation, denaturation of proteins, iceberg formation or reduction, hydrophobic bonding, and null thermal free energy. The statistical analysis of errors has shown that EAM has a general validity, well beyond the limits of our experiments. Specifically, the properties of hydrophobic hydration processes as biphasic systems generating convoluted binding potential functions, with water as the implicit solvent, hold for all biochemical and biological solutions, on the ground that they also are necessarily diluted solutions, statistically validated

Ergodic Algorithmic Model (EAM), with Water as Implicit Solvent, in Chemical, Biochemical, and Biological Processes

For many years, we have devoted our research to the study of the thermodynamic properties of hydrophobic hydration processes in water, and we have proposed the Ergodic Algorithmic Model (EAM) for maintaining the thermodynamic properties of any hydrophobic hydration reaction at a constant pressure from the experimental determination of an equilibrium constant (or other potential functions) as a function of temperature. The model has been successfully validated by the statistical analysis of the information elements provided by the EAM model for about fifty compounds. The binding functions are convoluted functions, RlnKeq = {f(1/T)* g(T)} and RTlnKeq = {f(T)* g(lnT)}, where the primary linear functions f(1/T) and f(T) are modified and transformed into parabolic curves by the secondary functions g(T) and g(lnT), respectively. Convoluted functions are consistent with biphasic dual-structure partition function, {DS-PF} = {M-PF} · {T-PF} · {ζw}, composed by ({M-PF} (Density Entropy), {T-PF}) (Intensity Entropy), and {ζw} (implicit solvent). In the present paper, after recalling the essential aspects of the model, we outline the importance of considering the solvent as “implicit” in chemical and biochemical reactions. Moreover, we compare the information obtained by computer simulations using the models till now proposed with “explicit” solvent, showing the mess of information lost without considering the experimental approach of the EAM model

An elastic-interface model for the mixed-mode bending test under cyclic loads

AbstractWe have developed a mechanical model of the mixed-mode bending (MMB) test, whereby the specimen is considered as an assemblage of two identical sublaminates, modelled as Timoshenko beams. The sublaminates are partly connected by a linearly elastic–brittle interface, transmitting stresses along both the normal and tangential directions with respect to the interface plane. The model is described by a set of suitable differential equations and boundary conditions. Based on the explicit solution of this problem and following an approach already adopted to model buckling-driven delamination growth in fatigue, we analyse the response of the MMB test specimen under cyclic loads. Exploiting the available analytical solution, we apply a fracture mode-dependent fatigue growth law. As a result, the number of cycles needed for a delamination to extend to a given length can be predicted

Measurement of cohesive laws from mixed bending-tension tests

The mixed bending-tension (MBT) test was proposed by Macedo et al. (2012) to assess the mode I interlaminar fracture toughness of composite laminates with very low bending stiffness and strength. Specimens obtained from such laminates may fail in bending prior to delamination growth, when tested using the double cantilever beam test (ASTM D5528-13). In the MBT test, the specimen with a pre-implanted delamination is adhesively bonded to two metal bars and then loaded in opening mode. Bennati et al. (2015) developed a mechanical model of the MBT test, where the two separating parts of the specimen are connected by a cohesive interface with bilinear traction-separation law. Accordingly, the specimen response can be subdivided into three stages: (i) linearly elastic behaviour, (ii) progressive material damage, and (iii) crack propagation. The theoretical predictions were in good agreement with the experimental results by Macedo et al. (2012) in the linearly elastic stage. Instead, only qualitative agreement was obtained for the subsequent stages. Here, we upgrade the previous model by introducing a piece-wise linear, discontinuous tractionseparation law for the cohesive zone (Valvo et al., 2015). We show how the global response of the specimen depends on the cohesive law parameters. Besides, we present an operative procedure to determine the cohesive law parameters based on the test measures

An enhanced beam-theory model of the mixed-mode bending (MMB) test – Part I: literature review and mechanical model

The paper presents a mechanical model of the mixed-mode bending (MMB) test used to assess the mixed-mode interlaminar fracture toughness of composite laminates. The laminated specimen is considered as an assemblage of two sublaminates partly connected by an elastic–brittle interface. The problem is formulated through a set of 36 differential equations, accompanied by suitable boundary conditions. Solution of the problem is achieved by separately considering the two subproblems related to the symmetric and antisymmetric parts of the loads, which for symmetric specimens correspond to fracture modes I and II, respectively. Explicit expressions are determined for the interfacial stresses, internal forces, and displacements