The incredible ability of human beings to quickly detect the prominent or salient regions in an image is often taken for granted. To be able to reproduce this intelligent ability in computer vision systems remains quite a challenge. This ability is of paramount importance to perception and image understanding since it accelerates the image analysis process, thereby allowing higher vision processes such as recognition to have a focus of attention. In addition to this, human eye fixation points occurring during the early stages of visual processing, often correspond to the loci of salient image regions. These regions provide us with assistance in determining the interesting parts of an image and they also lend support to our ability to discriminate between different objects in a scene. Salient regions attract our immediate attention without requiring an exhaustive scan of a scene. In essence, saliency can be defined as the quality of an image region that enables it to stand out in relation to its neighbors. Saliency is often approached in either one of two ways. The bottom-up saliency approach refers to mechanisms which are image-driven and independent of the knowledge in an image, whereas the top-down saliency approach refers to mechanisms which are task-oriented and make use of the prior knowledge about a scene. In this thesis, we present a bottom-up measure of saliency based on the relationships exhibited among image features. The perceived structure in an image is determined more by the relationships among features rather than the individual feature attributes. From this standpoint, we aim to capture the organization within an image by employing relational distributions derived from distance and gradient direction relationships exhibited between image primitives. The Rényi entropy of the relational distribution tends to be lower if saliency is exhibited for some image region in the local pixel neighborhood over which the distribution is defined. This notion forms the foundation of our measure. Correspondingly, results of our measure are presented in the form of a saliency map, highlighting salient image regions. We show results on a variety of real images from various datasets. We evaluate the performance of our measure in relation to a dominant saliency model and obtain comparable results. We also investigate the biological plausibility of our method by comparing our results to those captured by human fixation maps. In an effort to derive meaningful information from an image, we investigate the significance of scale relative to our saliency measure, and attempt to determine optimal scales for image analysis. In addition to this, we extend a perceptual grouping framework by using our measure as an optimization criterion for determining the organizational strength of edge groupings. As a result, the use of ground truth images is circumvented.

In dieser Dissertation analysieren wir drei Aspekte von Konforme Feldtheorien (CFTs). Erstens betrachten wir Korrelationsfunktionen von sekundären Zuständen (SZ) in zweidimensionalen CFTs. Wir diskutieren eine rekursive Formel zu ihrer Berechnung und erstellen eine Computerimplementierung dieser Formel. Damit können wir jede Korrelationsfunktion von SZ des Vakuums erhalten und für Nicht-Vakuum-SZ den Korrelator als Differentialoperator, der auf den jeweiligen primären Korrelator wirkt, ausdrücken. Mit diesem Code untersuchen wir dann einige Verschränkungs- und Unterscheidbarkeitsmaße zwischen SZ, i.e. die Rényi-Entropie, den Spurquadratabstand und die Sandwich-Rényi-Divergenz. Mit unseren Ergebnissen können wir die Rényi Quanten-Null-Energie-Bedingung testen und stellen neue Werkzeuge zur Analyse der holographischen Beschreibung von SZ bereit. Zweitens untersuchen wir vierdimensionale Weyl-Fermionen auf verschiedenen Hintergründen. Unser Interesse gilt ihrer Spuranomalie, und der Frage, ob die Pontryagin-Dichte auftritt. Deshalb berechnen wir die Anomalien von Dirac-Fermionen, die an vektorielle und axiale Eichfelder gekoppelt sind, und dann auf einem metrisch-axialen Tensor Hintergrund. Geeignete Grenzwerte der Hintergründe erlauben es dann, die Anomalien von Weyl-Fermionen, die an Eichfelder gekoppelt sind, und in einer gekrümmten Raumzeit zu berechnen. Wir bestätigen das Fehlen der Pontryagin-Dichte in den Spuranomalien. Drittens liefern wir die holographische Beschreibung einer vierdimensionalen CFT mit einem irrelevanten Operator. Wenn der Operator eine ganzzahlige konforme Dimension hat, modifiziert sein Vorhandensein in der CFT die Weyl-Transformation der Metrik, was wiederum die Spuranomalie ändert. Unter Ausnutzung der Äquivalenz zwischen Diffeomorphismen im Inneren und Weyl-Transformationen auf dem Rand, berechnen wir diese Modifikationen mithilfe der dualen Gravitationstheorie. Unsere Ergebnisse repräsentieren einen weiteren Test der AdS/CFT-Korrespondenz. / Conformal field theories (CFTs) are amongst the most studied field theories and they offer a remarkable playground in modern theoretical physics. In this thesis we analyse three aspects of CFTs in different dimensions. First, we consider correlation functions of descendant states in two-dimensional CFTs. We discuss a recursive formula to calculate them and provide a computer implementation of it. This allows us to obtain any correlation function of vacuum descendants, and for non-vacuum descendants to express the correlator as a differential operator acting on the respective primary correlator. With this code, we study some entanglement and distinguishability measures between descendant states, i.e. the Rényi entropy, trace square distance and sandwiched Rényi divergence. With our results we can test the Rényi Quantum Null Energy Condition and provide new tools to analyse the holographic description of descendant states. Second, we study four-dimensional Weyl fermions on different backgrounds. Our interest is in their trace anomaly, where the Pontryagin density has been claimed to appear. To ascertain this possibility, we compute the anomalies of Dirac fermions coupled to vector and axial non-abelian gauge fields and then in a metric-axial-tensor background. Appropriate limits of the backgrounds allow to recover the anomalies of Weyl fermions coupled to non-abelian gauge fields and in a curved spacetime. In both cases we confirm the absence of the Pontryagin density in the trace anomalies. Third, we provide the holographic description of a four-dimensional CFT with an irrelevant operator. When the operator has integer conformal dimension, its presence in the CFT modifies the Weyl transformation of the metric, which in turns modifies the trace anomaly. Exploiting the equivalence between bulk diffeomorphisms and boundary Weyl transformations, we compute these modifications from the dual gravity theory. Our results represent an additional test of the AdS/CFT conjecture.

This thesis examines the utility of mathematical complexity measures for the analysis of stratospheric dynamics. Through theoretical considerations and tests with artificial data sets, e.g., the iteration of the logistic map, suitable parameters are determined for the application of the statistical entropy measures sample entropy (SE) and Rényi entropy (RE) to methane (a long-lived stratospheric tracer) data from simulations of the SOCOL chemistry-climate model. The SE is shown to be useful for quantifying the variability of recurring patterns in a time series and is able to identify tropical patterns similar to those reported by previous studies of the ``tropical pipe'' region. However, the SE is found to be unsuitable for use in polar regions, due to the non-stationarity of the methane data at extra-tropical latitudes. It is concluded that the SE cannot be used to analyse climate complexity on a global scale. The focus is turned to the RE, which is a complexity measure of probability distribution functions (PDFs). Using the second order RE and a normalisation factor, zonal PDFs of ten consecutive days of methane data are created with a Bayesian optimal binning technique. From these, the RE is calculated for every day (moving 10-day window). The results indicate that the RE is a promising tool for identifying stratospheric mixing barriers. In Southern Hemisphere winter and early spring, RE produces patterns similar to those found in other studies of stratospheric mixing. High values of RE are found to be indicative of the strong fluctuations in tracer distributions associated with relatively unmixed air in general, and with gradients in the vicinity of mixing barriers, in particular. Lower values suggest more thoroughly mixed air masses. The analysis is extended to eleven years of model data. Realistic inter-annual variability of some of the RE structures is observed, particularly in the Southern Hemisphere. By calculating a climatological mean of the RE for this period, additional mixing patterns are identified in the Northern Hemisphere. The validity of the RE analysis and its interpretation is underlined by showing that qualitatively similar patterns can be seen when using observational satellite data of a different tracer. Compared to previous techniques, the RE has the advantage that it requires significantly less computational effort, as it can be used to derive dynamical information from model or measurement tracer data without relying on any additional input such as wind fields. The results presented in this thesis strongly suggest that the RE is a useful new metric for analysing stratospheric mixing and its variability from climate model data. Furthermore, it is shown that the RE measure is very robust with respect to data gaps, which makes it ideal for application to observations. Hence, using the RE for comparing observations of tracer distributions with those from model simulations potentially presents a novel approach for analysing mixing in the stratosphere.

<p>Quantum key growing, often called quantum cryptography or quantum key distribution, is a method using some properties of quantum mechanics to create a secret shared cryptography key even if an eavesdropper has access to unlimited computational power. A vital but often neglected part of the method is unconditionally secure message authentication. This thesis examines the security aspects of authentication in quantum key growing. Important concepts are formalized as Python program source code, a comparison between quantum key growing and a classical system using trusted couriers is included, and the chain rule of entropy is generalized to any Rényi entropy. Finally and most importantly, a security flaw is identified which makes the probability to eavesdrop on the system undetected approach unity as the system is in use for a long time, and a solution to this problem is provided.</p>

Quantum key growing, often called quantum cryptography or quantum key distribution, is a method using some properties of quantum mechanics to create a secret shared cryptography key even if an eavesdropper has access to unlimited computational power. A vital but often neglected part of the method is unconditionally secure message authentication. This thesis examines the security aspects of authentication in quantum key growing. Important concepts are formalized as Python program source code, a comparison between quantum key growing and a classical system using trusted couriers is included, and the chain rule of entropy is generalized to any Rényi entropy. Finally and most importantly, a security flaw is identified which makes the probability to eavesdrop on the system undetected approach unity as the system is in use for a long time, and a solution to this problem is provided. / ICG QC

Ziel dieser Arbeit ist die Untersuchung der Sub- und Superdiffusion in fraktalen Strukturen. Der Fokus liegt auf zwei separaten Ansätzen, die entsprechend des Diffusionbereiches gewählt und variiert werden. Dadurch erhält man ein tieferes Verständnis und eine bessere Beschreibungsweise für beide Bereiche. Im ersten Teil betrachten wir subdiffusive Prozesse, die vor allem bei Transportvorgängen, z. B. in lebenden Geweben, eine grundlegende Rolle spielen. Hierbei modellieren wir den fraktalen Zustandsraum durch endliche Sierpinski Teppiche mit absorbierenden Randbedingungen und lösen dann die Mastergleichung zur Berechnung der Zeitentwicklung der Wahrscheinlichkeitsverteilung. Zur Charakterisierung der Diffusion auf regelmäßigen und zufälligen Teppichen bestimmen wir die Abfallzeit der Wahrscheinlichkeitsverteilung, die mittlere Austrittszeit und die Random Walk Dimension. Somit können wir den Einfluss zufälliger Strukturen auf die Diffusion aufzeigen. Superdiffusive Prozesse werden im zweiten Teil der Arbeit mit Hilfe der Diffusionsgleichung untersucht. Deren zweite Ableitung im Ort erweitern wir auf nichtganzzahlige Ordnungen, um die fraktalen Eigenschaften der Umgebung darzustellen. Die resultierende raum-fraktionale Diffusionsgleichung spannt ein Übergangsregime von der irreversiblen Diffusionsgleichung zur reversiblen Wellengleichung auf. Deren Lösungen untersuchen wir mittels verschiedener Entropien, wie Shannon, Tsallis oder Rényi Entropien, und deren Entropieproduktionsraten, welche natürliche Maße für die Irreversibilität sind. Das dabei gefundene Entropieproduktions-Paradoxon, d. h. ein unerwarteter Anstieg der Entropieproduktionsrate bei sinkender Irreversibilität des Prozesses, können wir nach geeigneter Reskalierung der Entropien auflösen. / The aim of this thesis is the examination of sub- and superdiffusive processes in fractal structures. The focus of the work concentrates on two separate approaches that are chosen and varied according to the corresponding regime. Thus, we obtain new insights about the underlying mechanisms and a more appropriate way of description for both regimes. In the first part subdiffusion is considered, which plays a crucial role for transport processes, as in living tissues. First, we model the fractal state space via finite Sierpinski carpets with absorbing boundary conditions and we solve the master equation to compute the time development of the probability distribution. To characterize the diffusion on regular as well as random carpets we determine the longest decay time of the probability distribution, the mean exit time and the Random walk dimension. Thus, we can verify the influence of random structures on the diffusive dynamics. In the second part of this thesis superdiffusive processes are studied by means of the diffusion equation. Its second order space derivative is extended to fractional order, which represents the fractal properties of the surrounding media. The resulting space-fractional diffusion equations span a linking regime from the irreversible diffusion equation to the reversible (half) wave equation. The corresponding solutions are analyzed by different entropies, as the Shannon, Tsallis or Rényi entropies and their entropy production rates, which are natural measures of irreversibility. We find an entropy production paradox, i. e. an unexpected increase of the entropy production rate by decreasing irreversibility of the processes. Due to an appropriate rescaling of the entropy we are able to resolve the paradox.

This thesis examines the utility of mathematical complexity measures for the analysis of stratospheric dynamics. Through theoretical considerations and tests with artificial data sets, e.g., the iteration of the logistic map, suitable parameters are determined for the application of the statistical entropy measures sample entropy (SE) and Rényi entropy (RE) to methane (a long-lived stratospheric tracer) data from simulations of the SOCOL chemistry-climate model. The SE is shown to be useful for quantifying the variability of recurring patterns in a time series and is able to identify tropical patterns similar to those reported by previous studies of the ``tropical pipe'' region. However, the SE is found to be unsuitable for use in polar regions, due to the non-stationarity of the methane data at extra-tropical latitudes. It is concluded that the SE cannot be used to analyse climate complexity on a global scale. The focus is turned to the RE, which is a complexity measure of probability distribution functions (PDFs). Using the second order RE and a normalisation factor, zonal PDFs of ten consecutive days of methane data are created with a Bayesian optimal binning technique. From these, the RE is calculated for every day (moving 10-day window). The results indicate that the RE is a promising tool for identifying stratospheric mixing barriers. In Southern Hemisphere winter and early spring, RE produces patterns similar to those found in other studies of stratospheric mixing. High values of RE are found to be indicative of the strong fluctuations in tracer distributions associated with relatively unmixed air in general, and with gradients in the vicinity of mixing barriers, in particular. Lower values suggest more thoroughly mixed air masses. The analysis is extended to eleven years of model data. Realistic inter-annual variability of some of the RE structures is observed, particularly in the Southern Hemisphere. By calculating a climatological mean of the RE for this period, additional mixing patterns are identified in the Northern Hemisphere. The validity of the RE analysis and its interpretation is underlined by showing that qualitatively similar patterns can be seen when using observational satellite data of a different tracer. Compared to previous techniques, the RE has the advantage that it requires significantly less computational effort, as it can be used to derive dynamical information from model or measurement tracer data without relying on any additional input such as wind fields. The results presented in this thesis strongly suggest that the RE is a useful new metric for analysing stratospheric mixing and its variability from climate model data. Furthermore, it is shown that the RE measure is very robust with respect to data gaps, which makes it ideal for application to observations. Hence, using the RE for comparing observations of tracer distributions with those from model simulations potentially presents a novel approach for analysing mixing in the stratosphere.

Ziel dieser Arbeit ist die Untersuchung der Sub- und Superdiffusion in fraktalen Strukturen. Der Fokus liegt auf zwei separaten Ansätzen, die entsprechend des Diffusionbereiches gewählt und variiert werden. Dadurch erhält man ein tieferes Verständnis und eine bessere Beschreibungsweise für beide Bereiche. Im ersten Teil betrachten wir subdiffusive Prozesse, die vor allem bei Transportvorgängen, z. B. in lebenden Geweben, eine grundlegende Rolle spielen. Hierbei modellieren wir den fraktalen Zustandsraum durch endliche Sierpinski Teppiche mit absorbierenden Randbedingungen und lösen dann die Mastergleichung zur Berechnung der Zeitentwicklung der Wahrscheinlichkeitsverteilung. Zur Charakterisierung der Diffusion auf regelmäßigen und zufälligen Teppichen bestimmen wir die Abfallzeit der Wahrscheinlichkeitsverteilung, die mittlere Austrittszeit und die Random Walk Dimension. Somit können wir den Einfluss zufälliger Strukturen auf die Diffusion aufzeigen. Superdiffusive Prozesse werden im zweiten Teil der Arbeit mit Hilfe der Diffusionsgleichung untersucht. Deren zweite Ableitung im Ort erweitern wir auf nichtganzzahlige Ordnungen, um die fraktalen Eigenschaften der Umgebung darzustellen. Die resultierende raum-fraktionale Diffusionsgleichung spannt ein Übergangsregime von der irreversiblen Diffusionsgleichung zur reversiblen Wellengleichung auf. Deren Lösungen untersuchen wir mittels verschiedener Entropien, wie Shannon, Tsallis oder Rényi Entropien, und deren Entropieproduktionsraten, welche natürliche Maße für die Irreversibilität sind. Das dabei gefundene Entropieproduktions-Paradoxon, d. h. ein unerwarteter Anstieg der Entropieproduktionsrate bei sinkender Irreversibilität des Prozesses, können wir nach geeigneter Reskalierung der Entropien auflösen. / The aim of this thesis is the examination of sub- and superdiffusive processes in fractal structures. The focus of the work concentrates on two separate approaches that are chosen and varied according to the corresponding regime. Thus, we obtain new insights about the underlying mechanisms and a more appropriate way of description for both regimes. In the first part subdiffusion is considered, which plays a crucial role for transport processes, as in living tissues. First, we model the fractal state space via finite Sierpinski carpets with absorbing boundary conditions and we solve the master equation to compute the time development of the probability distribution. To characterize the diffusion on regular as well as random carpets we determine the longest decay time of the probability distribution, the mean exit time and the Random walk dimension. Thus, we can verify the influence of random structures on the diffusive dynamics. In the second part of this thesis superdiffusive processes are studied by means of the diffusion equation. Its second order space derivative is extended to fractional order, which represents the fractal properties of the surrounding media. The resulting space-fractional diffusion equations span a linking regime from the irreversible diffusion equation to the reversible (half) wave equation. The corresponding solutions are analyzed by different entropies, as the Shannon, Tsallis or Rényi entropies and their entropy production rates, which are natural measures of irreversibility. We find an entropy production paradox, i. e. an unexpected increase of the entropy production rate by decreasing irreversibility of the processes. Due to an appropriate rescaling of the entropy we are able to resolve the paradox.

In this thesis, we study statistical inference for entropy, divergence, and related functionals of one or two probability distributions. Asymptotic properties of particular nonparametric estimators of such functionals are investigated. We consider estimation from both independent and dependent observations. The thesis consists of an introductory survey of the subject and some related theory and four papers (A-D). In Paper A, we consider a general class of entropy-type functionals which includes, for example, integer order Rényi entropy and certain Bregman divergences. We propose U-statistic estimators of these functionals based on the coincident or epsilon-close vector observations in the corresponding independent and identically distributed samples. We prove some asymptotic properties of the estimators such as consistency and asymptotic normality. Applications of the obtained results related to entropy maximizing distributions, stochastic databases, and image matching are discussed. In Paper B, we provide some important generalizations of the results for continuous distributions in Paper A. The consistency of the estimators is obtained under weaker density assumptions. Moreover, we introduce a class of functionals of quadratic order, including both entropy and divergence, and prove normal limit results for the corresponding estimators which are valid even for densities of low smoothness. The asymptotic properties of a divergence-based two-sample test are also derived. In Paper C, we consider estimation of the quadratic Rényi entropy and some related functionals for the marginal distribution of a stationary m-dependent sequence. We investigate asymptotic properties of the U-statistic estimators for these functionals introduced in Papers A and B when they are based on a sample from such a sequence. We prove consistency, asymptotic normality, and Poisson convergence under mild assumptions for the stationary m-dependent sequence. Applications of the results to time-series databases and entropy-based testing for dependent samples are discussed. In Paper D, we further develop the approach for estimation of quadratic functionals with m-dependent observations introduced in Paper C. We consider quadratic functionals for one or two distributions. The consistency and rate of convergence of the corresponding U-statistic estimators are obtained under weak conditions on the stationary m-dependent sequences. Additionally, we propose estimators based on incomplete U-statistics and show their consistency properties under more general assumptions.

Mon travail de thèse est consacré à l’étude de quelques aspects de la physique quantique des systèmes quantiques à N corps en interaction. Il est orienté vers l’étude des chaînes de spins quantiques. Je me suis intéressé à plusieurs questions relatives aux chaînes de spins quantiques, du point de vue numérique et analytique à la fois. J'aborde en particulier les questions relatives à la structure des fonctions d'onde, la forme de la densité d'états et les propriétés spectrales des Hamiltoniens de chaînes de spins. Dans un premier temps, je présenterais très rapidement les techniques numériques de base pour le calcul des vecteurs et valeurs propres des Hamiltonien de chaînes de spins. Les densités d’états des modèles quantiques constituent des quantités importantes et très simples qui permettent de caractériser les propriétés spectrales des systèmes avec un grand nombre de degrés de liberté. Alors que dans la limite thermodynamique, les densités d'états de la plupart des modèles intégrables sont bien décrites par une loi gaussienne, dans certaines limites de couplage de la chaîne de spins au champ magnétique et pour un nombre de spins N fini sur la chaîne, on observe l’apparition de pics dans la densité d’états. Je montrerais que la connaissance des deux premiers moments du Hamiltonien dans le sous-espace dégénéré associé à chaque pics donne une bonne approximation de la densité d’états. Dans un deuxième temps je m'intéresserais aux propriétés spectrales des Hamiltoniens de chaînes de spins quantiques. L’un des principal résultats sur la statistique spectrale des systèmes quantiques concerne le comportement universel des fluctuations des mesures telles que l’espacement entre valeurs propres consécutives. Ces fluctuations sont bien décrites par la théorie des matrices aléatoires mais la comparaison avec les prédictions de cette théorie nécessite généralement une opération sur le spectre du Hamiltonien appelée unfolding. Dans les problèmes quantiques de N corps, la taille de l’espace de Hilbert croît généralement exponentiellement avec le nombre de particules, entraînant un manque de données pour pouvoir faire une statistique. Ces limitations ont amené l’introduction d’une nouvelle mesure se passant de la procédure d’unfolding basée sur le rapport d’espacements successifs plutôt que les espacements. En suivant l’idée du “surmise” de Wigner pour le calcul de la distribution de l’espacement, je montre comment calculer une approximation de la distribution du rapport d’espacements dans les trois ensembles gaussiens invariants en faisant le calcul pour des matrices 3x3. Les résultats obtenus pour les différents ensembles de matrices aléatoires se sont révélés être en excellent accord avec les résultats numériques. Enfin je m’intéresserais à la structure des fonctions d’ondes fondamentales des modèles de chaînes de spins quantiques. Les fonctions d’onde constituent, avec le spectre en énergie, les objets fondamentaux des systèmes quantiques : leur structure est assez compliquée et n’est pas très bien comprise pour la plupart des systèmes à N corps. En raison de la croissance exponentielle de la taille de l’espace de Hilbert avec le nombre de particules, l’étude des vecteurs propres est une tâche très difficile, non seulement du point de vue analytique mais aussi du point de vue numérique. Je démontrerais en particulier que l’état fondamental de tous les modèles que nous avons étudiés est multifractal avec en général une dimension fractale non triviale. / My thesis is devoted to the study of some aspects of many body quantum interacting systems. In particular we focus on quantum spin chains. I have studied several aspects of quantum spin chains, from both numerical and analytical perspectives. I addressed especially questions related to the structure of eigenfunctions, the level densities and the spectral properties of spin chain Hamiltonians. In this thesis, I first present the basic numerical techniques used for the computation of eigenvalues and eigenvectors of spin chain Hamiltonians. Level densities of quantum models are important and simple quantities that allow to characterize spectral properties of systems with large number of degrees of freedom. It is well known that the level densities of most integrable models tend to the Gaussian in the thermodynamic limit. However, it appears that in certain limits of coupling of the spin chain to the magnetic field and for finite number of spins on the chain, one observes peaks in the level density. I will show that the knowledge of the first two moments of the Hamiltonian in the degenerate subspace associated with each peak give a good approximation to the level density. Next, I study the statistical properties of the eigenvalues of spin chain Hamiltonians. One of the main achievements in the study of the spectral statistics of quantum complex systems concerns the universal behaviour of the fluctuation of measure such as the distribution of spacing between two consecutive eigenvalues. These fluctuations are very well described by the theory of random matrices but the comparison with the theoretical prediction generally requires a transformation of the spectrum of the Hamiltonian called the unfolding procedure. For many-body quantum systems, the size of the Hilbert space generally grows exponentially with the number of particles leading to a lack of data to make a proper statistical study. These constraints have led to the introduction of a new measure free of the unfolding procedure and based on the ratio of consecutive level spacings rather than the spacings themselves. This measure is independant of the local level density. By following the Wigner surmise for the computation of the level spacing distribution, I obtained approximation for the distribution of the ratio of consecutive level spacings by analyzing random 3x3 matrices for the three canonical ensembles. The prediction are compared with numerical results showing excellent agreement. Finally, I investigate eigenfunction statistics of some canonical spin-chain Hamiltonians. Eigenfunctions together with the energy spectrum are the fundamental objects of quantum systems: their structure is quite complicated and not well understood. Due to the exponential growth of the size of the Hilbert space, the study of eigenfunctions is a very difficult task from both analytical and numerical points of view. I demonstrate that the groundstate eigenfunctions of all canonical models of spin chain are multifractal, by computing numerically the Rényi entropy and extrapolating it to obtain the multifractal dimensions.