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Concept# Théorie

Résumé

Une théorie (du grec theoria, « contempler, observer, examiner ») est un ensemble cohérent, si elle prétend à la scientificité, d'explications, de notions ou d'idées sur un sujet précis, pouvant inclure des lois et des hypothèses, induites par l'accumulation de faits provenant de l'observation, l'expérimentation ou, dans le cas des mathématiques, déduites d'une base axiomatique donnée : théorie des matrices, des torseurs, des probabilités. Elle ne doit pas être confondue avec un principe philosophique contrairement aux principes observés et provisoirement admis suggérés par l'expérience, ni avec une hypothèse. Le terme de théoricien, qui désigne un scientifique, s'oppose à celui de technicien, qui désigne celui qui met en pratique une science particulière.
La philosophie des sciences précise qu'une théorie scientifique doit respecter plusieurs critères, comme la correspondance entre les principes théoriques et les phénomènes observés. Une théorie doit également permettre de réaliser d

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PHYS-739: Conformal Field theory and Gravity

This course is an introduction to the non-perturbative bootstrap approach to Conformal Field Theory and to the Gauge/Gravity duality, emphasizing the fruitful interplay between these two ideas.

CH-351: Molecular dynamics and Monte-Carlo simulations

Introduction to molecular dynamics and Monte-Carlo simulation methods.

PHYS-314: Quantum physics II

L'objectif de ce cours est de familiariser l'étudiant avec les concepts, les méthodes et les conséquences de la physique quantique. En particulier, le moment cinétique, la théorie de perturbation, les systèmes à plusieurs particules, les symétries, et les corrélations quantique seront traité

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Science

thumb|Allégorie de la Science par Jules Blanchard, située sur le parvis de l'hôtel de ville de Paris.
La (du latin scientia, « connaissance », ) est dans son sens premier « la somme des connaissance

Sociologie

La sociologie est une discipline des sciences sociales qui a pour objectif de rechercher des explications et des compréhensions typiquement sociales, et non pas mentales ou biophysiques, à des phéno

Physique

La physique est la science qui essaie de comprendre, de modéliser et d'expliquer les phénomènes naturels de l'Univers. Elle correspond à l'étude du monde qui nous entoure sous toutes ses formes, des

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Quantum Field Theory(QFT) as one of the most promising frameworks to study high energy and condensed matter physics, has been mostly developed by perturbative methods. However, perturbative methods can only capture a small island of the space of QFTs.QFT in hyperbolic space can be used to link the conformal bootstrap and massive QFT. Conformal boundary correlators also can be studied by their general properties such as unitarity, crossing symmetry and analicity. On the other hand, by sending the curvature radius to infinity we reach to the flat-space limit in hyperbolic space. This allows us to use conformal bootstrap methods to study massive QFT in one higher dimension and calculate observables like scattering amplitudes or finding bounds on the couplings of theory. The main goal of my research during my Ph.D. would be to study QFTs in hyperbolic space to better understand strongly coupled QFTs.Hamiltonian truncation is a numerical method to study strongly coupled QFTs by imposing a UV cutoff. We use this method to study strongly coupled QFT in hyperbolic space background. For simplicity, we start with scalar field theory in 2-dimensional AdS. We expect to extract the spectrum of our theory as a function of AdS curvature and find the boundary correlation functions.

This thesis is a contribution to financial statistics. One of the principal concerns of investors is the evaluation of portfolio risk. The notion of risk is vague, but in finance it is always linked to possible losses. In this thesis, we present some measures allowing the valuation of risk with the help of Bayesian methods. An exploratory analysis of data is presented to describe the sampling properties of financial time series. This analysis allows us to understand the origins of the daily returns studied in this thesis. Moreover, a discussion of different models is presented. These models make strong assumptions on investor behaviour, which are not always satisfied. This exploratory analysis shows some differences between the behaviour anticipated under equilibrium models, and that of real data. The Bayesian approach has been chosen because it allows one to incorporate all the variability, in particular that associated with model choice. The models studied in this thesis allow one to take heteroskedasticity into account, as well as particular shapes of the tails of returns. ARCH type models and models based on extreme value theory are studied. One original aspect of this thesis is its use of Bayesian analysis to detect change points in financial time series. We suppose that a market has two phases, and that it switches from a state to the other at random. Another new contribution is a model integrating heteroskedasticity and time dependence of extreme values, by superposition of the model proposed by Bortot and Coles (2003) and a GARCH process. This thesis uses simulation intensively for the estimation of risk measures. The drawback of simulation is the amount of time needed to obtain accurate estimates. However, simulation allows one to produce results when direct calculation is not feasible. For example, simulation allows one to compute risk estimates for time horizons greater than one day. The methods presented in this thesis are illustrated on simulated data, and on real data from European and American markets. This thesis involved the construction of a library containing C and S code to perform risk analysis using GARCH and extreme value theory models. The results show that model uncertainty can be incorporated, and that risk measures for time horizons greater than one can be obtained by simulation. The methods presented in this thesis have a natural representation involving conditioning. Thus, they permit the computation of both conditional and unconditional risk estimates. Three methods are described: the GARCH method; the two-state GARCH method; and the HBC method. Unconditional risk estimation using the GARCH method is satisfactory on data which seem stationary, but not reliable on data which are non-stationary, such as data with change points. The two-state GARCH model does a little better, but gives very satisfactory results when the risk is estimated conditionally on time. The HBC method does not give satisfactory results.

WHY do certain leaders’ management of organizational resources encourage creative people engaged in New Product Development (NPD) to achieve high performance, on time, while other leaders’ practices foster frustration and delays? In this research project I attempt to understand the WHY and HOW of leaders’ management of organizational resources in the context of Csikszentmihalyi’s phenomenon of Flow. Flow is most likely to occur when people perceive a balance between the challenge of a situation and their professional abilities to deal with the challenge. “Being in the flow” increases peoples’ focus and attention, the latter being a prerequisite for high creativity, on the tasks and problems at hand and boosts their commitment to deliver their projects on time. Following the above-mentioned reasoning, I assume that if leaders manage organizational resources to create an optimal balance between challenging situations and the skills of their creative people, these managerial practices would likely result in enhancing the output of the NPD process, and decreasing the delays, or, in other words, accelerating the NPD cycle. To explore this research question, first, I developed a conceptual model called CLIC: “Creative-Learning Innovation Cycle”. The CLIC is characterized by its uniqueness in highlighting the impact of the feedback received from the commercialization process on the managerial practices of leadership for creativity of the components of the work environment. The work environment directly affects the state of flow of creative people, and, subsequently, both the quality and speed of their learning and creativity processes. The CLIC combines Sanchez’s model of an organization’s learning process, Amabile’s componential theory of creativity, and, Csikszentmihalyi and Bakker’s State of Flow concept. Second, I tested the CLIC through two main research methods. I conducted exploratory and action research with a successful global innovation manager and two companies wrestling to accelerate their NPD processes in a changing work environment. The two companies deal with components and technological innovations. They differ in size, continent and products. Both companies innovate products related to health issues in an industry where high regulatory requirements are imposed. I also conducted a lab experiment in which 27 Masters students (18 males, 9 females) who were enrolled in an “Innovation Management” course voluntarily participated. The mean age was 23.5 years. The academic language was English. The exploration of the CLIC model in the course of conducting the comparative studies among the successful global innovation manager, the two companies, and the results of the lab experiment led to the emergence of a new theory about flow in work situations and organizational resources management. The theory defines and prioritizes five organizational resources that have to be managed during the NPD stages to let creative people experience a “state of flow” during their work. The foundation of the theory is that, following the impacts of feedback received from the external world, leaders’ managerial practices of organizational resources affect the state of flow of the people involved in the NPD process in an inverted U shape. Based on this inverted U shape and, as per the CLIC model, this theory prioritized the following five organizational resources to manage flow during the NPD stages: v A. Planning stage 1. Involving creative people in early market feedback during the planning stage would enhance their work absorption and their attention on the problems they are facing. B. Development stage 2. Putting creative people in direct communication with all the people who interact with the product and bring meaning to it, 3. Extending on a rational basis the time lines proposed by creative people, 4. And integrating the customer in the NPD process, mainly during testing phases, are likely to positively influence the intrinsic motivation of the creative people during the development stage. Hence, creative people would be committed to reach their goals by deploying their expertise to its utmost level without counting their working hours. C. Commercialization stage 5. Allow creative people to directly solicit and experience feedback from the VOC during the commercialization stage. This could constitute an enriching and joyful experience for them. In sum, the prioritization of these organizational resources during the NPD stages might constitute a beneficial roadmap to the managerial practices that should be used by leaders. The application of this theory by the leaders would regulate the balance between a challenging situation and the skills of the creative people, so the latter might be in the “state of flow”. Probable effects may be a boosted and an accelerated outcome of the NPD process, leading the organization to thrive in this seldom static world. Some leaders knew WHAT to do and HOW to enhance the creativity of their collaborators. However the understanding of the WHY that drives these managerial practices needed additional elucidation. This research project attempted to provide a potential answer to “WHY” leaders’ practices might enhance or hinder their collaborators’ state of flow; and, in finding the answer, it was thought that leaders and their collaborators may simultaneously enjoy work and savor life.