In this work, we study the backreaction of high-frequency gravitational waves on cosmological backgrounds. To describe the wave, we use the Isa- acson formalism, specifically the WKB approximation, which allows us to express the backreaction through an effective stress-energy tensor of the gra- vitational wave. First, we consider the inhomogeneous cosmological model of Charach and Malin, which contains gravitational waves and a massless scalar field mini- mally coupled to gravity. We show that although this is a spatially compacti- fied solution, it is possible to add a high-frequency perturbation and solve Einstein's equations with the effective stress-energy tensor in a consistent way. The bacreaction is of the same order as the influence of the scalar field. Second, we add multiple incoherent high-frequency waves to the homoge- neous Kasner background, and discuss the relation to the late-time limit of the Gowdy (vacuum Charach and Malin) model. 1

Orientador: Alberto Vazquez Saa / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-04T02:11:29Z (GMT). No. of bitstreams: 1 Dadam_Fabio_M.pdf: 999114 bytes, checksum: 86eea1cd6f96a55892393c5ee86c320f (MD5) Previous issue date: 2005 / Resumo: Oscilações de buracos negros adquiriram importância nos últimos anos devido a possibilidade de se comprovar a existência de tais corpos celestes por meio da detecção da radiação gravitacional emitida por eles. Nesse trabalho, o estudo da propagação de ondas de diferentes tipos incidentes em um buraco negro é apresentado sob o ponto de vista matematico. Inicialmente, são usados elementos de Geometria Diferencial a fim de se estabelecer a estrutura matemática da gravitação e, a partir de um conjunto de hipóteses, determinase uma família de soluções das Equações de Einstein que caracteriza os buracos negros (Schwarzschild, Reissner-Nordstrom, Kerr e Kerr-Newman). As Equações de Teukolsky, que governam as perturbações de buracos negros, são obtidas com a ajuda do formalismo de Newman-Penrose e transformadas em uma equação de onda unidimensional. Obedecendo a condições de fronteira especificas, soluções dessa equação para frequências complexas são então determinadas a partir de diferentes métodos semi-analiticos / Abstract: In the past few years, black hole oscillations became a very interesting research area mainly due to the possibility of proving the existence of such celestial bodies through the gravitational radiation emitted by them. In this work, the study of the propagation of different kinds of incident waves on a black hole is presented under the mathematical point of view. Initially, elements of differential geometry are used to establish the mathematical structure of gravitation and, under certain hypotheses, a family of solutions to the Einstein equations is obtained, describing the black holes (Schwarzschild, Reissner-Nordstr¨om, Kerr and Kerr-Newman). Teukolsky equations, which govern the black hole perturbations, are obtained with the aid of Newman-Penrose formalism and transformed to a one-dimensional wave equation. According to certain boundary conditions, solutions of this equation for complex frequencies are determined from different semi-analytic methods / Mestrado / Geometria / Mestre em Matemática

Cette thèse présente les résultats de la recherche de signaux d'ondes gravitationnelles transitoires de longue durée dans les données des deux premiers runs d'observation des détecteurs advanced LIGO et advanced Virgo. Ces ondes sont principalement émises par des étoiles à neutrons ou des trous noirs impliqués dans des phénomènes violents. Pour certaines sources, une modélisation impliquant une dynamique complexe et des instabilités hydrodynamiques peut prédire grossièrement la forme d'onde. Mais de manière générale, seulement l'information approximative sur la durée et la bande de fréquence est utilisée pour définir les limites de l'espace des paramètres de la recherche. Une méthode d'analyse temps-fréquence robuste aux incertitudes de la modélisation des signaux a donc été développé. En combinant les données de deux détecteurs de façon cohérente, la méthode permet de différencier les signaux recherchés du bruit de fond non gaussien des détecteurs. En l'absence de détection, nous avons placé des limites supérieures sur l'énergie émise et le taux attendu pour ces sources. Une recherche du signal attendu après la fusion de deux étoiles à neutrons observé en août 2017 (GW170817) a également était faite dans l'hypothèse où une étoile à neutrons supre-massive a été formée. Aucun signal n'a été identifié et j'ai montré que des détecteurs un ordre de grandeur plus sensibles auraient été nécessaires pour détecter un tel signal. / This thesis shows the results of the search of long duration transient gravitational waves using the data from the first two observation runs of advanced LIGO and advanced Virgo detectors. These long duration gravitational waves are mainly emitted by neutrons stars or black hole involved in extreme phenomena. For some sources, a modeling involving a complex dynamics and hydrodynamic instabilities can predict roughly the waveform. Nevertheless, for the general case, only a partial informations on the duration and frequency band are used to limits the parameters space. A time-frequency analysis, sturdy enough to modeling incertitude, has been developed and applied to the data. Combining data from two detectors in a coherent way, the analysis can distinguish between signal and detector's non gaussian background noise. In the absence of detection, we have placed upper limits on the energy emitted and the expected rate for these sources. A search for the expected signal emitted by the object created after the neutron stars coalescence and merger observed in August 2017 (GW170817) was also made assuming a supra-massive neutron star was created and survived hundred of seconds after the merger. No signal has been found and we have shown that detectors of an order of magnitude more sensible would have been required to detect a signal from this source.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21557号 / 理博第4464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 柴田 大, 教授 田中 貴浩, 教授 井岡 邦仁 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Les méthodes standard de détection du fond gravitationnel stochastique reposent sur l'hypothèse simplificatrice selon laquelle sa distribution ainsi que celle du bruit des détecteurs sont Gaussiennes. Nous proposons dans cette thèse des méthodes améliorées de détection du fond gravitationnel stochastique qui tiennent compte explicitement du caractère non-Gaussien de ces distributions. En utilisant un développement d'Edgeworth, nous obtenons dans un premier temps une expression analytique pour la statistique du rapport de vraisemblance en présence d'une distribution non Gaussienne du fonds gravitationnel stochastique. Cette expression généralise l'expression habituelle lorsque le coefficient de symétrie et le coefficient d'aplatissement de la distribution du fond stochastique sont non nuls. Sur la base de simulations stochastiques pour différentes distributions symétriques présentant des queues plus épaisses que celles de la distribution Gaussienne, nous montrons par ailleurs que le 4eme cumulant peut-être estimé avec une précision acceptable lorsque le ratio signal à bruit est supérieur à 1%, ce qui devrait permettre d'apporter des contraintes supplémentaires intéressantes sur les valeurs de paramètres issus des modèles astrophysiques et cosmologiques. Dans un deuxième temps, nous cherchons à analyser l'impact sur les méthodes de détection du fond gravitationnel stochastique de déviations par rapport à la normalité dans la distribution du bruit des détecteurs. / The new generation of interferometers should allow us to detect stochastic gravitational wave backgrounds that are expected to arise from a large number of random, independent, unresolved events of astrophysical or cosmological origin. Most detection methods for gravitational waves are based upon the assumption of Gaussian gravitational wave stochastic background signals and noise processes. Our main objective is to improve the methods that can be used to detect gravitational backgrounds in the presence of non-Gaussian distributions. We first maintain the assumption of Gaussian noise distributions so as to better focus on the impact of deviations from normality of the signal distribution in the context of the standard cross-correlation detection statistic. Using a 4th-order Edgeworth expansion of the unknown density for the signal and noise distributions, we first derive an explicit expression for the non-Gaussian likelihood ratio statistic, which is obtained as a function of the variance, but also skewness and kurtosis of the unknown signal and noise distributions. We use numerical procedures to generate maximum likelihood estimates for the gravitational wave distribution parameters for a set of symmetric heavy-tailed distributions, and we find that the fourth cumulant can be estimated with reasonable precision when the ratio between the signal and the noise variances is larger than 1%, which should be useful for analyzing the constraints on astrophysical and cosmological models. In a second step, we analyze the efficiency of the standard cross-correlation statistic in situations that also involve non-Gaussian noise distributions.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第20903号 / 理博第4355号 / 新制||理||1625(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 佐々木 節, 教授 柴田 大, 教授 川合 光 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(理学) / 甲第24409号 / 理博第4908号 / 新制||理||1701(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 柴田 大, 教授 井岡 邦仁, 教授 橋本 幸士 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

This is an exciting time for Gravitational Wave (GW) theory and observations. From a theoretical standpoint, the grand-challenge problem of the full evolution of a Binary Black Hole (BBH) system has been solved numerically, and a variety of source simulations are made available steadfastly. On the observational side, the first generation of state-of-the-art GW detectors, LIGO and Virgo, have achieved their design goal, collected data and provided astrophysically meaningful limits. The second generation of detectors are expected to start running by 2015. Inspired by this zeitgeist, this thesis focuses on the detection of potential GW signatures from the coalescence of BBH in ground-based laser interferometers. The LIGO Scientific Collaboration has implemented different algorithms to search for transient GW signatures, targeting different portions of the BBH coalescence waveform. This thesis has used the existing algorithms to study the detection potential of GW from colliding BBH in LIGO in a wide range of source parameters, such as mass and spin of the black holes, using a sample of data from the last two months of the S5 LIGO science run (14 Aug 2007 to 30 Sept 2007). This thesis also uses numerical relativity waveforms made available via the Numerical INJection Analysis project (NINJA). Methods such as the Chirplet based analysis and the use of multivariate classifiers to optimize burst search algorithms have been introduced in this thesis. These performance studies over a wide parameter space were designed to optimize the discovery potential of ground-based GW detectors and defining strategies for the search of BBH signatures in advanced LIGO data, as a step towards the realization of GW astronomy

Ground-based gravitational wave detectors are evolving at a rapid pace. In the five minutes that followed the first direct detection of gravitational waves, the Advanced LIGO and Advanced Virgo experiments have been subject to substantial upgrades, increasing their sensitivities by many times and allowing them to detect dozens of other gravitational wave signals. Third-generation ground-based interferometers (Einstein Telescope and Cosmic Explorer) and spaaace-based detectors (such as LISA) are being researched and planned to enter into function in the second half of the next decade. If successful, these experiments will allow the detection of thousands of signals coming from an ever-increasing range of cosmological sources. In the meantime, second-generation interferometers are approaching the conclusion of ambitious upgrades started with the end of the third observing run “O3” in march 2020. The work of this thesis revolves around the planning and the commissioning of the “Advanced Virgo plus” upgrade project, which aims to increase the detector’s sensitivity by a factor of two, allowing a ten times higher detection rate than the previous configuration. In particular, the main topic is the update of the interferometer longitudinal sensing and control scheme required by the upgrade in the detector’s optical configuration. The design and simulation of the new control scheme catried out in constant collaboration with the “Interferometer Sensing and Control” team, started minutes before the actual implementation of the upgrades. Following that, I participated in the full-time commissioning of the upgraded configuration, which started in January 2021 and is currently ongoing. We will first explain the new interferometer configuration, then go into the details of the lock-acquisition procedure, presenting the results of the related simulation studies and the commissioning. A particular focus will also be given to the simulations of the interferometer’s state at the end of the lock acquisition, called “steady-state”. In addition to the study and implementation of the current lock-acquisition procedure, the thesis will present simulation activities to study an alternative lock-acquisition technique that has not yet been implemented.

Deep learning has seen rapid evolution in the past decade, accomplishing tasks that were previously unimaginable. At the same time, researchers strive to better understand and interpret the underlying mechanisms of the deep models, which are often justifiably regarded as "black boxes". Overcoming this deficiency will not only serve to suggest better learning architectures and training methods, but also extend deep learning to scenarios where interpretability is key to the application. One such scenario is signal detection and estimation, with gravitational wave detection as a specific example, where classic methods are often preferred for their interpretability. Nonetheless, while classic statistical detection methods such as matched filtering excel in their simplicity and intuitiveness, they can be suboptimal in terms of both accuracy and computational efficiency. Therefore, it is appealing to have methods that achieve ``the best of both worlds'', namely enjoying simultaneously excellent performance and interpretability. In this thesis, we aim to bridge this gap between modern deep learning and classic statistical detection, by revisiting the signal detection problem from a new perspective. First, to address the perceived distinction in interpretability between classic matched filtering and deep learning, we state the intrinsic connections between the two families of methods, and identify how trainable networks can address the structural limitations of matched filtering. Based on these ideas, we propose two trainable architectures that are constructed based on matched filtering, but with learnable templates and adaptivity to unknown noise distributions, and therefore higher detection accuracy. We next turn our attention toward improving the computational efficiency of detection, where we aim to design architectures that leverage structures within the problem for efficiency gains. By leveraging the statistical structure of class imbalance, we integrate hierarchical detection into trainable networks, and use a novel loss function which explicitly encodes both detection accuracy and efficiency. Furthermore, by leveraging the geometric structure of the signal set, we consider using signal space optimization as an alternative computational primitive for detection, which is intuitively more efficient than covering with a template bank. We theoretical prove the efficiency gain by analyzing Riemannian gradient descent on the signal manifold, which reveals an exponential improvement in efficiency over matched filtering. We also propose a practical trainable architecture for template optimization, which makes use of signal embedding and kernel interpolation. We demonstrate the performance of all proposed architectures on the task of gravitational wave detection in astrophysics, where matched filtering is the current method of choice. The architectures are also widely applicable to general signal or pattern detection tasks, which we exemplify with the handwritten digit recognition task using the template optimization architecture. Together, we hope the this work useful to scientists and engineers seeking machine learning architectures with high performance and interpretability, and contribute to our understanding of deep learning as a whole.