Le chemin parcouru par la lumière, lors de sa propagation dans l’Univers, est altéré par la présence d’objets massifs. Cela entraine une déformation des images de galaxies lointaines. La mesure de cet effet, dit de lentille gravitationnelle faible, nous permet de sonder la structure, aux grandes échelles, de notre Univers. En particulier, nous pouvons ainsi étudier la distribution de la matière noire et les propriétés de l’Energie Sombre, proposée comme origine de l’accélération de l’expansion de l’Univers. L’étude de l'effet de lentille gravitationnelle faible constitue l’un des objectifs scientifiques principaux d'Euclid, un télescope spatial de l’Agence Spatiale Européenne en cours de construction.En pratique, ce signal est obtenu en mesurant la forme des galaxies. Toute image produite par un instrument optique est altérée par sa fonction d’étalement du point (PSF). Celle-ci a diverses origines : diffraction, imperfections dans les composantes optiques de l’instrument, effets atmosphériques (pour les télescopes au sol)… Puisque la PSF affecte aussi les formes des galaxies, il est crucial de la prendre en compte lorsque l’on étudie l’effet de lentille gravitationnelle faible, ce qui nécessite de très bien connaître la PSF elle-même.Celle-ci varie en fonction de la position dans le plan focal. Une mesure de la PSF, à certaines positions, est donnée par l’observation d’étoiles non-résolues dans le champ, à partir desquelles on peut construire un modèle de PSF. Dans le cas d’Euclid, ces images d’étoiles seront sous-échantillonnée ; aussi le modèle de PSF devra-t-il contenir une étape de super-résolution. En raison de la très large bande d’intégration de l’imageur visible d’Euclid, il sera également nécessaire de capturer les variations en longueur d’onde de la PSF.La contribution principale de cette thèse consiste en le développement de méthodes novatrices d’estimation de la PSF, reposant sur plusieurs outils : la notion de représentation parcimonieuse, et le transport optimal numérique. Ce dernier nous permet de proposer la première méthode capable de fournir un modèle polychromatique de la PSF, construit uniquement à partir d’images sous-échantillonnées d’étoiles et leur spectre. Une étude de la propagation des erreurs de PSF sur la mesure de forme de galaxies est également proposée. / As light propagates through the Universe, its path is altered by the presence of massive objects. This causes a distortion of the images of distant galaxies. Measuring this effect, called weak gravitational lensing, allows us to probe the large scale structure of the Universe. This makes it a powerful source of cosmological insight, and can in particular be used to study the distribution of dark matter and the nature of Dark Energy. The European Space Agency’s upcoming Euclid mission is a spaceborne telescope with weak lensing as one of its primary science objectives.In practice, the weak lensing signal is recovered from the measurement of the shapes of galaxies. The images obtained by any optical instrument are altered by its Point Spread Function (PSF), caused by various effects: diffraction, imperfect optics, atmospheric turbulence (for ground-based telescopes)… Since the PSF also alters galaxy shapes, it is crucial to correct for it when performing weak lensing measurements. This, in turn, requires precise knowledge of the PSF itself.The PSF varies depending on the position of objects within the instrument’s focal plane. Unresolved stars in the field provide a measurement of the PSF at given positions, from which a PSF model can be built. In the case of Euclid, star images will suffer from undersampling. The PSF model will thus need to perform a super-resolution step. In addition, because of the very wide band of its visible instrument, variations of the PSF with the wavelength of incoming light will also need to be accounted for.The main contribution of this thesis is the building of novel PSF modelling approaches. These rely on sparsity and numerical optimal transport. The latter enables us to propose the first method capable of building a polychromatic PSF model, using no information other than undersampled star images, their position and spectra. We also study the propagation of errors in the PSF to the measurement of galaxy shapes.

Thesis advisor: Betty Leask / Universities around the world are increasingly adopting internationalization strategies, which call attention to intentionality in using the curriculum and strategic regional networks as ways to achieve university agendas. Internationalization of the curriculum (IoC) endeavors are typically led by a select group of individuals within a single university, and often struggle to gain diverse wide-spread support within the university community (Leask, 2013). However, university networks, which demand interconnectivity, have been argued to “constitute the core of internationalisation,” and present varied academic opportunities for engagement that expand channels of information sharing and knowledge creation (de Wit & Callan, 1995, p.89). Therefore, university networks have unexplored potential in providing unique learning opportunities for member institutions’ faculty and staff in internationalizing their curricula, while advancing their institution’s internationalization agenda. Through a framework of network theories, professional learning theory, and an internationalization of the curriculum conceptual framework, this study investigated faculty and staff engagement with one network, and how their engagement has influenced conceptualizations of internationalization of the curriculum. Drawing from semi-structured interviews with fourteen members of faculty and staff from two of five universities in a European university network, the results demonstrate that this network supports faculty and staff in contextualizing and conceptualizing internationalization. The analysis points to the differences in conceptualizations of IoC, depending on the level of faculty and staff engagement with the network. The diverse representation of faculty and staff at network events created significant interactions where individuals were able to validate and share their experiences and expertise related to internationalizing curriculum, as well as critically examine their own approaches and university policies. Faculty and staff engagement with the network resulted in mature conceptualizations of internationalizing curriculum, and contributed to a greater adaptability to working in changing, intercultural environments. The study suggests that engagement in this network is conducive to the internationalization of one’s academic Self, and to fostering a greater sense of regional camaraderie (Sanderson, 2008). Finally, the results of this study demonstrate one university network’s ability to engage an increasing mass of reflective faculty and staff that are aware of internationalization and its implications for their learning environments. The contributions of this study are significant for university leaders, scholars, and practitioners, and especially those working in the nuanced intersection of internationalizing curricula and university networks. / Thesis (MA) — Boston College, 2020. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Leadership and Higher Education.

abstract: Social media has become an important means of user-centered information sharing and communications in a gamut of domains, including news consumption, entertainment, marketing, public relations, and many more. The low cost, easy access, and rapid dissemination of information on social media draws a large audience but also exacerbate the wide propagation of disinformation including fake news, i.e., news with intentionally false information. Disinformation on social media is growing fast in volume and can have detrimental societal effects. Despite the importance of this problem, our understanding of disinformation in social media is still limited. Recent advancements of computational approaches on detecting disinformation and fake news have shown some early promising results. Novel challenges are still abundant due to its complexity, diversity, dynamics, multi-modality, and costs of fact-checking or annotation. Social media data opens the door to interdisciplinary research and allows one to collectively study large-scale human behaviors otherwise impossible. For example, user engagements over information such as news articles, including posting about, commenting on, or recommending the news on social media, contain abundant rich information. Since social media data is big, incomplete, noisy, unstructured, with abundant social relations, solely relying on user engagements can be sensitive to noisy user feedback. To alleviate the problem of limited labeled data, it is important to combine contents and this new (but weak) type of information as supervision signals, i.e., weak social supervision, to advance fake news detection. The goal of this dissertation is to understand disinformation by proposing and exploiting weak social supervision for learning with little labeled data and effectively detect disinformation via innovative research and novel computational methods. In particular, I investigate learning with weak social supervision for understanding disinformation with the following computational tasks: bringing the heterogeneous social context as auxiliary information for effective fake news detection; discovering explanations of fake news from social media for explainable fake news detection; modeling multi-source of weak social supervision for early fake news detection; and transferring knowledge across domains with adversarial machine learning for cross-domain fake news detection. The findings of the dissertation significantly expand the boundaries of disinformation research and establish a novel paradigm of learning with weak social supervision that has important implications in broad applications in social media. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2020

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21558号 / 理博第4465号 / 新制||理||1641(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 大西 明, 教授 青木 慎也, 教授 田中 貴浩 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

Superradiance is an enhanced decay of an excited system of emitters resulting from their mutual coupling. This thesis is focused on superradiance of the emitters coupled via their interaction with a plasmonic nanoparticle. So-called plasmon-mediated superradiance results in even stronger enhancement of the decay rate as the nanoparticle serves as an additional decay chanel. We have developed a quantum model of the system of emitters coupled to a plasmonic nanoparticle, which allows us to differentiate between a pure dephasing and decay processes. We show that the pure dephasing can destroy the cooperative effect leading to superradiance. Furthermore, we have studied how the direct mutual coupling between emitters affects time evolution of the system in dependence on its configuration, and we show conditions when a decay of the system is dramatically decreased by direct coupling.

This project is focused on construction of source of modulation signal for microwave beacon. The output signal is the same as signal, which is generated by PC software WSJT (Weak Signal by Joe Taylor) on PC sound card output. Signal on device output is modulated using by WSJT modulation and its specific JT4 mode. The device output has I and Q components of signal.

We study two interacting particles in a random potential chain by a transfer matrix method which allows a correct handling of the symmetry of the two- particle wave function, but introduces an artificial ¨bag¨ interaction. The dependence of the two-particle localization length lambta 2on disorder, interaction strength and range is investigated. Our results demonstrate that the recently proposed enhancement of lambta 2 as compared to the results for single particles is vanishingly small for a Hubbard interaction. For longer-range interactions, we observe a small enhancement but with a different disorder dependence than proposed previously.

This thesis focuses on the development and analysis of efficient simulation and inference techniques for Markovian pure jump processes with a view towards applications in dense communication networks. These techniques are especially relevant for modeling networks of smart devices —tiny, abundant microprocessors with integrated sensors and wireless communication abilities— that form highly complex and diverse communication networks. During 2010, the number of devices connected to the Internet exceeded the number of people on Earth: over 12.5 billion devices. By 2015, Cisco’s Internet Business Solutions Group predicts that this number will exceed 25 billion. The first part of this work proposes novel numerical methods to estimate, in an efficient and accurate way, observables from realizations of Markovian jump processes. In particular, hybrid Monte Carlo type methods are developed that combine the exact and approximate simulation algorithms to exploit their respective advantages. These methods are tailored to keep a global computational error below a prescribed global error tolerance and within a given statistical confidence level. Indeed, the computational work of these methods is similar to the one of an exact method, but with a smaller constant. Finally, the methods are extended to systems with a disparity of time scales. The second part develops novel inference methods to estimate the parameters of Markovian pure jump process. First, an indirect inference approach is presented, which is based on upscaled representations and does not require sampling. This method is simpler than dealing directly with the likelihood of the process, which, in general, cannot be expressed in closed form and whose maximization requires computationally intensive sampling techniques. Second, a forward-reverse Monte Carlo Expectation-Maximization algorithm is provided to approximate a local maximum or saddle point of the likelihood function of the parameters given a set of observations. The third part is devoted to applications in communication networks where also mean field or fluid approximations techniques, to substantially reduce the computational work of simulating large communication networks are explored. These methods aim to capture the global behaviour of systems with large state spaces by using an aggregate approximation, which is often described by means of a non-linear dynamical system.

In this thesis, our research focus on a weak second order stochastic Runge–Kutta method applied to a system of stochastic differential equations known as the Gatheral Model. We approximate numerical solutions to this system and investigate the rate of convergence of our method. Both call and put options are priced using Monte-Carlo simulation to investigate the order of convergence. The numerical results show that our method is consistent with the theoretical order of convergence of the Monte-Carlo simulation. However, in terms of the Runge-Kutta method, we cannot accept the consistency of our method with the theoretical order of convergence without further research.

The primary result from this dissertation is following inequality: d(B) ≤ min(2^< wd(B),sup{λ^c(B): λ < wd(B)}) in ZFC, where B is a homogeneous complete Boolean algebra, d(B) is the density, wd(B) is the weak density, and c(B) is the cellularity of B. Chapter II of this dissertation is a general overview of homogeneous complete Boolean algebras. Assuming the existence of a weakly inaccessible cardinal, we give an example of a homogeneous complete Boolean algebra which does not attain its cellularity. In chapter III, we prove that for any integer n > 1, wd_2(B) = wd_n(B). Also in this chapter, we show that if X⊂B is κ—weakly dense for 1 < κ < sat(B), then sup{wd_κ(B):κ < sat(B)} = d(B). In chapter IV, we address the following question: If X is weakly dense in a homogeneous complete Boolean algebra B, does there necessarily exist b € B\{0} such that {x∗b: x ∈ X} is dense in B|b = {c € B: c ≤ b}? We show that the answer is no for collapsing algebras. In chapter V, we give new proofs to some well known results concerning supporting antichains. A direct consequence of these results is the relation c(B) < wd(B), i.e., the weak density of a homogeneous complete Boolean algebra B is at least as big as the cellularity. Also in this chapter, we introduce discernible sets. We prove that a discernible set of cardinality no greater than c(B) cannot be weakly dense. In chapter VI, we prove the main result of this dissertation, i.e., d(B) ≤ min(2^< wd(B),sup{λ^c(B): λ < wd(B)}). In chapter VII, we list some unsolved problems concerning this dissertation.