[pt] Nas últimas décadas, interações entre luz e matéria provaram ser uma ferramenta versátil para medir e controlar sistemas mecânicos, encontrando aplicações desde detecção de forças até resfriamento ao estado fundamental de nanoesferas. Nesta dissertação, nós apresentamos algumas das ferramentas teóricas necessárias para descrever interferômetros, pinças ópticas e cavidades ópticas, constituintes fundamentais da caixa de ferramentas optomecânica. No regime clássico, estudamos o campo eletromagnético circulante em interferômetros lineares e mostramos como encontrar o campo resultante transmitido, apresentando exemplos de cavidades ópticas com um número arbitrário de elementos dispersivos. Nós também estudamos as forças de pressão de radiação que feixes ópticos podem imprimir em partículas dielétricas e mostramos como o aprisionamento óptico 3D é possível em focos claros e escuros. A potencial aplicação para captura de organismos vivos é estudada. No regime quântico, nós estudamos como o campo ressonante de cavidades ópticas pode interagir de forma dispersiva com diferentes sistemas mecânicos, dando origem a uma dinâmica quântica fechada emaranhante. Ao considerar uma nuvem ultra resfriada de átomos interagindo com dois modos ópticos, mostramos o surgimento de emaranhamento óptico que evidencia a natureza não-clássica do conjunto atômico macroscópico. A viabilidade experimental deste experimento com tecnologia atual é estudada. Além disso, nós investigamos o cenário em que uma pinça óptica posiciona uma partícula levitada dentro de uma cavidade óptica de forma que os fótons da pinça espalhados pela partícula possam sobreviver dentro da cavidade. Já foi demonstrado que esta interação, chamada de espalhamento coerente, pode resfriar nanopartículas até números de fônons menores do que um, atingindo profundamente o regime quântico. Nós mostramos que esta interação também pode gerar emaranhamento mecânico entre muitas partículas levitadas, mesmo em um ambiente a temperatura de 300K. Um resumo sobre sistemas de variáveis contínuas e a caixa de ferramentas numérica customizada usada ao longo deste trabalho são apresentados. / [en] Over the last decades, light-matter interactions have proven to be a versatile tool to measure and control mechanical systems, finding application from force sensing to ground state cooling of nanospheres. In this dissertation, we present some of the theoretical tools that describe interferometers, optical tweezers and optical cavities, fundamental constituents of the optomechanical toolbox. In the classical regime, we study the circulating electromagnetic field within linear interferometers and show how one can find the resulting transmitted field, presenting examples of optical cavities with an arbitrary number of dispersive elements. Moreover, we also study the radiation-pressure forces that optical beams can imprint on dielectric particles and show how 3D optical trapping is possible in both bright and dark focuses. Potential application to trapping of living organisms is studied. In the quantum regime, we study how the resonant field of optical cavities can dispersivelly interact with different mechanical systems, giving rise to an entangling closed quantum dynamics. When considering an ultracold cloud of atoms interacting with two optical modes, we show the emergence of optical entanglement which evidences the nonclassical nature of the macroscopic atomic ensemble. The experimental feasibility of this experiment with current technology is studied. Furthermore, we investigate the scenario where a finely tuned optical tweezer places a trapped particle inside an optical cavity such that the tweezer s scattered photons can survive inside the cavity. This so-called coherent scattering interaction has been shown to cool nanoparticles to phonon numbers lower than one deep into the quantum regime. We show that it also can generate mechanical entanglement between many levitated particles even in a room temperature environment. An overview on continuous variable systems and the custom numerical toolbox used throughout this work are presented.

Spontaneous parametric down conversion (SPDC) is used to generate quantum entangled photons through a non-linear crystal. The entanglement of photons is demonstrated by observing the effects of indistinguishability on photons, first through time and energy, then by polarization. The Hong-Ou-Mandel (HOM) effect was also demonstrated. A theoretical derivation of the effect of a non 50/50 beam splitter (BS) is also investigated. The energy of the photons was changed by varying the temperature of the crystal whilst the time difference was changed by varying the relative position of two mirrors. Results showed a clear effect from indistinguishability on both energy and time.

In a strongly correlated material the localized electrons, typically the electrons in the 3d-orbitals, become entangled with each other through the Coulomb interaction. However, these electrons also interact with more mobile (itinerant) electrons in the s- and p-orbitals. The latter process called screening as it effectively reduces the strength of the interaction between the 3d-electrons. A less studied and often neglected effect of the screening is that it also entangles the 3d-electrons with the itinerant electrons, which is equivalent to a leakage of quantum information from the 3delectrons to the environment. This process leads to decoherence since it causes the 3d-electrons to effectively lose some of their quantum mechanical properties. But what does this mean for our understanding of strongly correlated materials and can this decoherence effect be of such magnitude that neglecting it may qualitatively affect the calculated material properties? This is the question this report tries to answer, but for a minimal impurity model consisting of an atom and a few surrounding bath orbitals. / I korrelerade atomer kan lokaliserade elektroner, som elektroner i 3d orbitaler, bli kvantmekaniskt sammanflätade med varandra genom coulomb-växelverkan. Dessa elektroner kan även växelverka med mer mobila elektroner, som elektroner i s- och p-orbitaler. Denna process kallas för skärmning eftersom den effektivt sätt reducerar styrkan på repulsionen mellan elektronerna i 3d-orbitalerna. En mindre känd och ofta ignorerad effekt från skärmningen är att elektronerna i 3d-orbitalerna blir kvantmekaniskt sammanflätade med de mobila elektronerna på ett irreversibelt sätt. Detta är ekvivalent med att information om d-elektronernas position läcker ut till omgivningen. Denna informationsläcka kallas för dekoherens eftersom den ledertill att d-elektronerna förlorar en del av sina kvantmekaniska egenskaper. Frågan blir således vad dekoherens kan ha för betydelse för starkt korrelerade materials egenskaper. Kan denna effekt vara av sådan magnitud att det ger oss en helt felaktig bild om den negligeras? Detta är vad denna rapport syftar till att svara på.

Phase transitions are fundamental phenomena in (quantum) many-body systems. They are associated with changes in the macroscopic physical properties of the system in response to the alteration in the conditions controlled by one or more parameters, like temperature or coupling constants. Quantum phase transitions are particularly intriguing as they reveal new insights into the fundamental nature of matter and the laws of physics. The study of phase transitions in such systems is crucial in aiding our understanding of how materials behave in extreme conditions, which are difficult to replicate in laboratory, and also the behavior of exotic states of matter with unique and potentially useful properties like superconductors and superfluids. Moreover, this understanding has other practical applications and can lead to the development of new materials with specific properties or more efficient technologies, such as quantum computers. Hence, detecting the transition point from one phase of matter to another and constructing the corresponding phase diagram is of great importance for examining many-body systems and predicting their response to external perturbations. Traditionally, phase transitions have been identified either through analytical methods like mean field theory or numerical simulations. The pinpointing of the critical value normally involves the measure of specific quantities such as local observables, correlation functions, energy gaps, etc. reflecting the changes in the physics through the transition. However, the latter approach requires prior knowledge of the system to calculate the order parameter of the transition, which is uniquely associated to its universality class. Recently, another method has gained more and more attention in the physics community. By using raw and very general representative data of the system, one can resort to machine learning techniques to distinguish among patterns within the data belonging to different phases. The relevance of these techniques is rooted in the ability of a properly trained machine to efficiently process complex data for the sake of pursuing classification tasks, pattern recognition, generating brand new data and even developing decision processes. The aim of this thesis is to explore phase transitions from this new and promising data-centric perspective. On the one hand, our work is focused on the developement of new machine learning architectures using state-of-the-art and interpretable models. On the other hand, we are interested in the study of the various possible data which can be fed to the artificial intelligence model for the mapping of a quantum many-body system phase diagram. Our analysis is supported by numerical examples obtained via matrix-product-states (MPS) simulations for several one-dimensional zero-temperature systems on a lattice such as the XXZ model, the Extended Bose-Hubbard model (EBH) and the two-species Bose Hubbard model (BH2S). In Part I, we provide a general introduction to the background concepts for the understanding of the physics and the numerical methods used for the simulations and the analysis with deep learning. In Part II, we first present the models of the quantum many-body systems that we study. Then, we discuss the machine learning protocol to identify phase transitions, namely anomaly detection technique, that involves the training of a model on a dataset of normal behavior and use it to recognize deviations from this behavior on test data. The latter can be applied for our purpose by training in a known phase so that, at test-time, all the other phases of the system are marked as anomalies. Our method is based on Generative Adversarial Networks (GANs) and improves the networks adopted by the previous works in the literature for the anomaly detection scheme taking advantage of the adversarial training procedure. Specifically, we train the GAN on a dataset composed of bipartite entanglement spectra (ES) obtained from Tensor Network simulations for the three aforementioned quantum systems. We focus our study on the detection of the elusive Berezinskii-Kosterlitz-Thouless (BKT) transition that have been object of intense theoretical and experimental studies since its first prediction for the classical two-dimensional XY model. The absence of an explicit symmetry breaking and its gappless-to-gapped nature which characterize such a transition make the latter very subtle to be detected, hence providing a challenging testing ground for the machine-driven method. We train the GAN architecture on the ES data in the gapless side of BKT transition and we show that the GAN is able to automatically distinguish between data from the same phase and beyond the BKT. The protocol that we develop is not supposed to become a substitute to the traditional methods for the phase transitions detection but allows to obtain a qualitative map of a phase diagram with almost no prior knowledge about the nature and the arrangement of the phases -- in this sense we refer to it as agnostic -- in an automatic fashion. Furthermore, it is very general and it can be applied in principle to all kind of representative data of the system coming both from experiments and numerics, as long as they have different patterns (even hidden to the eye) in different phases. Since the kind of data is crucially linked with the success of the detection, together with the ES we investigate another candidate: the probability density function (PDF) of a globally U(1) conserved charge in an extensive sub-portion of the system. The full PDF is one of the possible reductions of the ES which is known to exhibit relations and degeneracies reflecting very peculiar aspects of the physics and the symmetries of the system. Its patterns are often used to tell different kinds of phases apart and embed information about non-local quantum correlations. However, the PDF is measurable, e.g. in quantum gas microscopes experiments, and it is quite general so that it can be considered not only in the cases of the study but also in other systems with different symmetries and dimensionalities. Both the ES and the PDF can be extracted from the simulation of the ground state by dividing the one-dimensional chain into two complementary subportions. For the EBH we calculate the PDF of the bosonic occupation number in a wide range of values of the couplings and we are able to reproduce the very rich phase diagram containing several phases (superfluid, Mott insulator, charge density wave, phase separation of supersolid and superfluid and the topological Haldane insulator) just with an educated gaussian fit of the PDF. Even without resorting to machine learning, this analysis is instrumental to show the importance of the experimentally accessible PDF for the task. Moreover, we highlight some of its properties according to the gapless and gapped nature of the ground state which require a further investigation and extension beyond zero-temperature regimes and one-dimensional systems. The last chapter of the results contains the description of another architecture, namely the Concrete Autoencoder (CAE) which can be used for detecting phase transitions with the anomaly detection scheme while being able to automatically learn what the most relevant components of the input data are. We show that the CAE can recognize the important eigenvalues out of the entire ES for the EBH model in order to characterize the gapless phase. Therefore the latter architecture can be used to provide not only a more compact version of the input data (dimensionality reduction) -- which can improve the training -- but also some meaningful insights in the spirit of machine learning interpretability. In conclusion, in this thesis we describe two advances in the solution to the problem of phase recognition in quantum many-body systems. On one side, we improve the literature standard anomaly detection protocol for an automatic and agnostic identification of the phases by employing the GAN network. Moreover, we implement and test an explainable model which can make the interpretation of the results easier. On the other side we put the focus on the PDF as a new candidate quantity for the scope of discerning phases of matter. We show that it contains a lot of information about the many-body state being very general and experimentally accessible.

No description available.

The aim of this paper is to gain a greater understanding of the meaning-making process behind Finland and Sweden’s decision to join NATO in 2022, and by so, deviate from their long-standing tradition of military non-alignment. Instead of solely pointing to the Russian invasion of Ukraine as the official reason for NATO membership this paper suggests that the concept of strategic culture can provide one with a greater understanding of their decision to join NATO. Resulting in the question: How can the concept of strategic culture help us understand the decision by Sweden and Finland to apply for NATO membership in 2022, despite their longstanding tradition of non-military alignment? With the concept of strategic culture, the analytical framework argues that the decision-making in Finland and Sweden was shaped by historical experiences that in turn influenced their strategic culture, which worked as a shaping context for their respective strategic behaviour. This is done through an entanglement analysis, a close reading and interpretation of the empirical material such as books, peer-reviewed articles, statements, government reports, and speeches, to demonstrate if the decision to join NATO followed Finland and Sweden’s typical strategic behaviour. This paper argues that the decision to join NATO did not represent a shift in the two state’s respective behaviour, instead the decision was in line with the strategic behaviour the states have followed since the end of the Cold War. Hence, the decision to join NATO demonstrates a sign of continuity rather than a historical shift in their foreign and security policy.

No description available.

No description available.

Yes / Satellite QKD/FSO systems, which facilitate quantum key distribution (QKD) over free-space optical (FSO) links between satellites and ground stations, present a promising pathway toward achieving global security in upcoming sixth-generation (6G) wireless communications. Our study focuses on a superior type of these systems, the satellite EB/CV-QKD/FSO, which utilizes the continuous-variable (CV) method for quantum state representation and the entanglement-based (EB) scheme for QKD implementation. We propose the use of optical phase-shift keying (QPSK) signaling and dual-threshold/heterodyne detection (DT/HD) receivers to bolster the reliability and feasibility of satellite EB/CV-QKD/FSO systems. Closed-form expressions for key system performance metrics are derived using improved channel modeling. Numerical results are presented to showcase the effects of channel impairments on the system performance. We also provide recommendations for optimal system setup parameters, aiming to enhance performance. / Ministry of Information and Communications (Vietnam) (Grant Number: DT.26/23). Asia Pacific Network Information Centre (APNIC) Foundation under the Switch! Project

Vision has always been one of the most important cognitive tools of human beings. In this regard, the development of image sensors opens up the potential to view objects that our eyes cannot see. One of the most promising capability in some image sensors is their single-photon sensitivity that provides information at the ultimate fundamental limit of light. Time-resolved single-photon avalanche diode (SPAD) image sensors bring a new dimension as they measure the arrival time of incident photons with a precision in the order of hundred picoseconds. In addition to this characteristic, they can be fabricated in complementary metal-oxide-semiconductor (CMOS) technology enabling the integration of complex signal processing blocks at the pixel level. These unique features made CMOS SPAD sensors a prime candidate for a broad spectrum of applications. This thesis is dedicated to the optimization and characterization of quantum imagers based on the SPADs as part of the E.U. funded SUPERTWIN project to surpass the fundamental diffraction limit known as the Rayleigh limit by exploiting the spatio-temporal correlation of entangled photons. The first characterized sensor is a 32×32-pixel SPAD array, named “SuperEllen”, with in-pixel time-to-digital converters (TDC) that measure the spatial cross-correlation functions of a flux of entangled photons. Each pixel features 19.48% fill-factor (FF) in 44.64-μm pitch fabricated in a 150-nm CMOS standard technology. The sensor is fully characterized in several electro-optical experiments, in order to be used in quantum imaging measurements. Moreover, the chip is calibrated in terms of coincidence detection achieving the minimal coincidence window determined by the SPAD jitter. The second developed sensor in the context of SUPERTWIN project is a 224×272-pixel SPAD-based array called “SuperAlice”, a multi-functional image sensor fabricated in a 110-nm CMOS image sensor technology. SuperAlice can operate in multiple modes (time-resolving or photon counting or binary imaging mode). Thanks to the digital intrinsic nature of SPAD imagers, they have an inherent capability to achieve a high frame rate. However, running at high frame rate means high I/O power consumption and thus inefficient handling of the generated data, as SPAD arrays are employed for low light applications in which data are very sparse over time and space. Here, we present three zero-suppression mechanisms to increase the frame rate without adversely affecting power consumption. A row-skipping mechanism that is implemented in both SuperEllen and SuperAlice detects the absence of SPAD activity in a row to increase the duty cycle. A current-based mechanism implemented in SuperEllen ignores reading out a full frame when the number of triggered pixels is less than a user-defined value. A different zero-suppression technique is developed in the SuperAlice chip that is based on jumping through the non-zero pixels within one row. The acquisition of TDC-based SPAD imagers can be speeded up further by storing and processing events inside the chip without the need to read out all data. An on-chip histogramming architecture based on analog counters is developed in a 150-nm CMOS standard technology. The test structure is a 16-bin histogram with 9 bit depth for each bin. SPAD technology demonstrates its capability in other applications such as automotive that demands high dynamic range (HDR) imaging. We proposed two methods based on processing photon arrival times to create HDR images. The proposed methods are validated experimentally with SuperEllen obtaining >130 dB dynamic range within 30 ms of integration time and can be further extended by using a timestamping mechanism with a higher resolution.