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Functional inequalities involving special functions are very useful in mathematical analysis, and several interesting results have been obtained in this topic. Several methods have been used by many authors in order to derive upper or lower bounds of certain special functions. In this paper, we establish some general integral inequalities involving strictly monotone functions. Next, some special cases are discussed. In particular, several estimates of trigonometric and hyperbolic functions are deduced. For instance, we show that Mitrinović-Adamović inequality, Lazarevic inequality, and Cusa-Huygens inequality are special cases of our obtained results. Moreover, an application to integral equations is provided.

A study of random walks over simplicial complexes with a particular emphasis on matroids. A framework is developed that yields results on the entropy contraction and modified log-Sobolev constant of the exchange walks over the levels of a simplicial complex, on the basis of entropy contraction properties of some local walks. This provides a general method for analyzing a variety of Markov chains by analyzing some of their lower-dimensional instances.

This thesis is part of a series of works carried out by Aldéric Joulin, Michel Bonnefont et alius, which aims at using intertwining relations to infer properties of some Markov generators. The present work deals specifically with three properties : Poincaré inequalities, logarithmic Sobolev inequalities and spectral estimates. Both above inequalities are widely use tools in infinite-dimensional analysis, that relate to the latter generators and underlying Boltzmann-Gibbs invariant distribution.In the first chapter, a method based on Feynman-Kac semigroups is proposed to infer new estimates, in relation to the logarithmic Sobolev inequality. The connexion between generators and stochastic processes is explored via a representation theorem for Feynman-Kac semigroups.In the second chapter, an algebraic approach to the estimation of eigenvalues of the aforementioned generators is discussed. This work echoes a related recent article by Emanuel Milman, in which he used optimal transport results in this very purpose. Multiplicities are addressed as well, in relation to the recent work of Franck Barthe and Boaz Klartag.In the last chapter, the relation between Poincaré inequalities and sensitivity analysis is investigated, particularly in order to compare two types of sensitivity indices. An estimation method related to this inequality is developed in dimension two, using finite elements methods.; Cette thèse s'inscrit dans une série de travaux menés par Aldéric Joulin, Michel Bonnefont et leurs collaborateurs, dont le but est d'appliquer des relations d'entrelacement pour obtenir des informations sur certains générateurs de Markov. Le présent travail traite de trois propriétés plus spécifiquement : les inégalités de Poincaré, de Sobolev logarithmiques et les estimations spectrales. Les deux inégalités ci-dessus sont des outils classiques d'analyse infini-dimensionnelle, qui présentent des liens intéressants avec les générateurs sus-mentionnés et les propriétés de la mesure de Boltzmann-Gibbs associée.Le premier chapitre propose une approche basée sur les semi-groupes de Feynman-Kac pour déduire de nouvelles estimations en relation avec l'inégalité de Sobolev logarithmique. Les résultats sont obtenus en utilisant le lien entre générateurs et processus stochastiques, via les semi-groupes de Feynman-Kac.Le deuxième chapitre pousse la réflexion amorcée par l'inégalité de Poincaré sur l'estimation des valeurs propres desdits générateurs en proposant une vision algébrique pour l'estimation de ces dernières. Ce travail fait écho à un article récent d'Emanuel Milman sur le sujet, où une approche par transport optimal était privilégiée. Les multiplicités associées sont également discutées, en lien notamment avec de récents travaux de Franck Barthe et Boaz Klartag.Enfin, le dernier chapitre traite d'une application des inégalités de Poincaré à l'analyse de sensibilité, où ces dernières sont utilisées pour faire un lien entre deux familles d'indices de sensibilité. Une méthode d'estimation en lien avec cette inégalité en dimension deux est proposée, basée sur des techniques d'éléments finis.

This thesis is part of a series of works carried out by Aldéric Joulin, Michel Bonnefont et alius, which aims at using intertwining relations to infer properties of some Markov generators. The present work deals specifically with three properties : Poincaré inequalities, logarithmic Sobolev inequalities and spectral estimates. Both above inequalities are widely use tools in infinite-dimensional analysis, that relate to the latter generators and underlying Boltzmann-Gibbs invariant distribution. In the first chapter, a method based on Feynman-Kac semigroups is proposed to infer new estimates, in relation to the logarithmic Sobolev inequality. The connexion between generators and stochastic processes is explored via a representation theorem for Feynman-Kac semigroups. The method is illustrated on two examples. In the second chapter, an algebraic approach to the estimation of eigenvalues of the aforementioned generators is discussed. This work echoes a related recent article by Emanuel Milman, in which he used optimal transport results in this very purpose. Multiplicities are addressed as well, in relation to the recent work of Franck Barthe and Boaz Klartag. In the last chapter, the relation between Poincaré inequalities and sensitivity analysis is investigated, particularly in order to compare two types of sensitivity indices. An estimation method related to this inequality is developed in dimension two, using finite elements methods. This approach is explained in much details and implemented on a simplified flood model., Cette thèse s'inscrit dans une série de travaux menés par Aldéric Joulin, Michel Bonnefont et collaborateurs, dont le but est d'appliquer des relations d'entrelacement pour obtenir des informations sur certains générateurs de Markov. Le présent travail traite de trois propriétés plus spécifiquement : les inégalités de Poincaré, de Sobolev logarithmiques et les estimations spectrales, pour les générateurs de Markov auto-adjoints. Les deux inégalités ci-dessus sont des outils classiques d'analyse infini-dimensionnelle, qui présentent des liens intéressants avec les générateurs sus-mentionnés et les propriétés de la mesure de Boltzmann-Gibbs associée. Le premier chapitre propose une approche basée sur les semi-groupes de Feynman-Kac pour déduire de nouvelles estimations en relation avec l'inégalité de Sobolev logarithmique. Les résultats sont obtenu en utilisant le lien entre générateurs et processus stochastiques, plus particulièrement via un théorème de représentation des semi-groupes de Feynman-Kac. Deux exemples illustrent la méthode. Le deuxième chapitre pousse la réflexion amorcée par l'inégalité de Poincaré sur l'estimation des valeurs propres desdits générateurs en proposant une vision algébrique pour l'estimation de ces dernières. Ce travail fait écho à un article récent d'Emanuel Milman sur le sujet, où une approche par transport optimal était privilégiée. Les multiplicités associées sont également discutées, en lien notamment avec de récents travaux de Franck Barthe et Boaz Klartag. Enfin, le dernier chapitre traite d'une application des inégalités de Poincaré à l'analyse de sensibilité, où ces dernières sont utilisées pour faire un lien entre deux familles d'indices de sensibilité. Une méthode d'estimation en lien avec cette inégalité en dimension deux est proposée, basée sur des techniques d'éléments finis. Cette approche est amplement détaillée et implémenté sur l'exemple classique d'un modèle de crue simplifié.

We study a $1$-dimensional chain of $N$ weakly anharmonic classical oscillators coupled at its ends to heat baths at different temperatures. Each oscillator is subject to pinning potential and it also interacts with its nearest neighbors. In our set up both potentials are homogeneous and bounded (with $N$ dependent bounds) perturbations of the harmonic ones. We show how a generalized version of Bakry-Emery theory can be adapted to this case of a hypoelliptic generator which is inspired by F. Baudoin (2017). By that we prove exponential convergence to non-equilibrium steady state (NESS) in Wasserstein-Kantorovich distance and in relative entropy with quantitative rates. We estimate the constants in the rate by solving a Lyapunov-type matrix equation and we obtain that the exponential rate, for the homogeneous chain, has order bigger than $N^{-3}$. For the purely harmonic chain the order of the rate is in $ [N^{-3},N^{-1}]$. This shows that, in this set up, the spectral gap decays at most polynomially with $N$., Comment: 54 pages, 1 figure, comments are welcome

We study dynamical optimal transport metrics between density matrices associated to symmetric Dirichlet forms on finite-dimensional $C^*$-algebras. Our setting covers arbitrary skew-derivations and it provides a unified framework that simultaneously generalizes recently constructed transport metrics for Markov chains, Lindblad equations, and the Fermi Ornstein--Uhlenbeck semigroup. We develop a non-nommutative differential calculus that allows us to obtain non-commutative Ricci curvature bounds, logarithmic Sobolev inequalities, transport-entropy inequalities, and spectral gap estimates., An error in Theorem 10.6 has been corrected

Report from the conference.

The purpose of this paper is to introduce the logarithmic mean of two convex functionals that extends the logarithmic mean of two positive operators. Some inequalities involving this functional mean are discussed as well. The operator versions of the functional theoretical results obtained here are immediately deduced without referring to the theory of operator means., 21 pages, Some typo's were modified

We establish a Shearer-type inequality for the Poincaré constant, showing that the Poincaré constant corresponding to the convolution of a collection of measures can be nontrivially controlled by the Poincaré constants corresponding to convolutions of subsets of measures. This implies, for example, that the sequence of Poincaré constants corresponding to successive convolutions in the central limit theorem is non-increasing. We also establish a dimension-free stability estimate for subadditivity of the Poincaré constant on convolutions which uniformly improves an earlier one-dimensional estimate of a similar nature by Johnson (Teor. Veroyatn. Primen. 48 (2003) 615–620). As a byproduct of our arguments, we find that the various monotone properties of entropy, Fisher information and the Poincaré constant on convolutions have a common, simple root in Shearer’s inequality.

Functional version for the so-called Furuta parametric relative operator entropy is here investigated. Some related functional inequalities are also discussed. The theoretical results obtained by our functional approach immediately imply those of operator versions in a simple, fast, and nice way.

In this work we present several quantitative results of convergence to equilibrium for the linear Boltzmann operator with soft potentials under Grad's angular cut-off assumption. This is done by an adaptation of the famous entropy method and its variants, resulting in explicit algebraic, or even stretched exponential, rates of convergence to equilibrium under appropriate assumptions. The novelty in our approach is that it involves functional inequalities relating the entropy to its production rate, which have independent applications to equations with mixed linear and non-linear terms. We also briefly discuss some properties of the equation in the non-cut-off case and conjecture what we believe to be the right rate of convergence in that case.

A functional inequality, called supermigrativity, was recently introduced for bivariate semi-copulas and applied in various problems arising in the study of aging properties of stochastic systems. Here, we revisit this notion and extend it to the case of aggregation functions in higher dimensions. In particular, we show how supermigrativity can be expressed via monotonicity of a function with respect to logarithmic majorization ordering of real vectors. Various alternative characterizations of supermigrativity are illustrated, together with some of its weaker versions. Several examples show similarities and differences between the bivariate and the general case.

In this paper we prove the functional inequality $f(x)^{f(x)}\leq g(x)^{g(x)}$ for positive real functions $f$ and $g$ satisfying natural conditions and apply it to derive inequalities between some of the elementary functions and to prove monotonocity of certain sequences of real numbers.

International audience; We use the formalism of the Rényi entropies to establish the symmetry range of extremal functions in a family of subcriti-cal Caffarelli-Kohn-Nirenberg inequalities. By extremal functions we mean functions which realize the equality case in the inequalities, written with optimal constants. The method extends recent results on critical Caffarelli-Kohn-Nirenberg inequalities. Using heuristics given by a nonlinear diffusion equation, we give a variational proof of a symmetry result, by establishing a rigidity theorem: in the symmetry region, all positive critical points have radial symmetry and are therefore equal to the unique positive, radial critical point, up to scalings and multiplications. This result is sharp. The condition on the parameters is indeed complementary of the condition which determines the region in which symmetry breaking holds as a consequence of the linear instability of radial optimal functions. Compared to the critical case, the subcritical range requires new tools. The Fisher information has to be replaced by Rényi entropy powers, and since some invariances are lost, the estimates based on the Emden-Fowler transformation have to be modified.

In this paper, we prove multilevel concentration inequalities for bounded functionals $$f = f(X_1, \ldots , X_n)$$f=f(X1,…,Xn) of random variables $$X_1, \ldots , X_n$$X1,…,Xn that are either independent or satisfy certain logarithmic Sobolev inequalities. The constants in the tail estimates depend on the operator norms of k-tensors of higher order differences of f. We provide applications for both dependent and independent random variables. This includes deviation inequalities for empirical processes $$f(X) = \sup _{g \in {\mathcal {F}}} {|g(X)|}$$f(X)=supg∈F|g(X)| and suprema of homogeneous chaos in bounded random variables in the Banach space case $$f(X) = \sup _{t} {\Vert \sum _{i_1 \ne \ldots \ne i_d} t_{i_1 \ldots i_d} X_{i_1} \cdots X_{i_d}\Vert }_{{\mathcal {B}}}$$f(X)=supt‖∑i1≠…≠idti1…idXi1⋯Xid‖B. The latter application is comparable to earlier results of Boucheron, Bousquet, Lugosi, and Massart and provides the upper tail bounds of Talagrand. In the case of Rademacher random variables, we give an interpretation of the results in terms of quantities familiar in Boolean analysis. Further applications are concentration inequalities for U-statistics with bounded kernels h and for the number of triangles in an exponential random graph model.

Some differentiability results from the paper of D.Ş. Marinescu & M. Monea [7] on delta-convex mappings, obtained for real functions, are extended for mappings with values in a normed linear space. In this way, we are nearing the completion of studies established in papers [2], [5] and [7].

The notion of strictly outward minimising hull is investigated for open sets of finite perimeter sitting inside a complete noncompact Riemannian manifold. Under natural geometric assumptions on the ambient manifold, the strictly outward minimising hull $\Omega^*$ of a set $\Omega$ is characterised as a maximal volume solution of the least area problem with obstacle, where the obstacle is the set itself. In the case where $\Omega$ has $\mathscr{C}^{1, \alpha}$-boundary, the area of $\partial \Omega^*$ is recovered as the limit of the $p$-capacities of $\Omega$, as $p \to 1^+$. Finally, building on the existence of strictly outward minimising exhaustions, a sharp isoperimetric inequality is deduced on complete noncompact manifolds with nonnegative Ricci curvature, provided $3 \leq n \leq 7$.

Consider tossing a collection of coins, each fair or biased towards heads, and take the distribution of the total number of heads that result. It is natural to conjecture that this distribution should be 'more random' when each coin is fairer. Indeed, Shepp and Olkin conjectured that the Shannon entropy of this distribution is monotonically increasing in this case. We resolve this conjecture, by proving that this intuition is correct. Our proof uses a construction which was previously developed by the authors to prove a related conjecture of Shepp and Olkin concerning concavity of entropy. We discuss whether this result can be generalized to $q$-R\'{e}nyi and $q$-Tsallis entropies, for a range of values of $q$., Comment: 16 pages

Functional inequalities constitute a very powerful toolkit in studying various problems arising in classical information theory, statistics and many-body systems. Extensions of these tools to the noncommutative setting have been introduced in the beginning of the 90's in order to study the asymptotic properties of certain quantum Markovian evolutions. In this thesis, we study various extensions and problems arising from the specific noncommutative nature of such processes. The first logarithmic Sobolev inequality to be proved, due to Gross, was for the Ornstein Uhlenbeck semigroup, that is the Brownian motion with friction on the real line. The generalization of this result to the quantum Ornstein Uhlenbeck semigroup was found very recently by Carlen and Maas, and de Palma and Huber by means of different techniques. The latter proof consists of a quantum generalization of the so-called entropy power inequality. Here, we consider another possible version of the entropy power inequality and use it to derive asymptotic properties of the frictionless quantum Brownian motion. The proof of Carlen and Maas discussed in the previous paragraph relies on their new quantum extension of the classical notion of displacement convexity. This is classically known to imply most of the usual functional inequalities such as the modified logarithmic Sobolev inequality and Poincaré's inequality. Here, we further study the framework introduced by Carlen and Maas. In particular, we show how displacement convexity implies quantum functional and transportation cost inequalities. The latter are then used to derive certain concentration inequalities of quantum states in the spirit of Bobkov and Goetze. These concentration inequalities are used in order to derive finite sample size bounds for the task of quantum parameter estimation. The main advantage of classical logarithmic Sobolev inequalities over other methods resides in their tensorization property: the strong log-Sobolev constant of the product of independent Markovian evolutions is equal to the maximum over the set of strong log-Sobolev constants of the individual evolutions. However, this property is strongly believed to fail in the non-commutative case, due to the non-multiplicativity of noncommutative Lp to Lq norms. In this thesis, we show tensorization of the logarithmic Sobolev constants for the simplest quantum Markov semigroup, namely the generalized depolarizing semigroup. Moreover, we consider a new general method to overcome the issue of tensorization for general primitive quantum Markov semigroups by looking at their contractivity properties under the completely bounded Lp to Lq norms. This method was first investigated in the restricted case of unital semigroups by Beigi and King. Noncommutative functional inequalities considered in the present literature only deal with primitive quantum Markovian semigroups which model memoryless irreversible dynamics converging to a specific faithful state. However, quantum Markov semigroups can in general display a much richer behavior referred to as decoherence: In particular, under some mild conditions, any such semigroup is known to converge to an algebra of observables which effectively evolve unitarily. Here, we introduce the concept of a decoherence-free logarithmic Sobolev inequality, and the related notion of hypercontractivity of the associated evolution, to study the decoherence rate of non-primitive quantum Markov semigroups. Moreover, we utilize the transference method recently introduced by Gao, Junge and LaRacuente, in order to find decoherence times associated to a class of decoherent Markovian evolutions of great importance in the field of quantum error protection, namely collective decoherence semigroups. Finally, we develop the notion of quantum reverse hypercontractivity, first introduced by Cubitt, Kastoryano, Montanaro and Temme in the unital case, and apply it in conjunction with the tensorization of the modified logarithmic Sobolev inequality for the generalized depolarizing semigroup in order to find strong converse rates in quantum hypothesis testing and for the classical capacity of classical-quantum channels. Moreover, the transference method also allows us to find strong converse bounds on the various capacities of quantum Markovian evolutions.

The purpose of this note is to show how simple Optimal Transport arguments, on the real line, can be used in Superconcentration theory. This methodology is efficient to produce sharp non-asymptotic variance bounds for various functionals (maximum, median, $l^p$ norms) of standard Gaussian random vectors in $\mathbb{R} ^n$. The flexibility of this approach can also provide exponential deviation inequalities reflecting preceding variance bounds. As a further illustration, usual laws from Extreme theory and Coulomb gases are studied.

In this thesis, I am studying the convergence rate to equilibrium of the stochastic Allen-Cahn equation, in the limit of vanishing noise. This convergence rate can be quantified by the spectral gap of the associated diffusion operator. It will be our primary goal, to compute the asymptotic behaviour of the spectral gap for the discretized version of the Allen-Cahn equation, with error terms uniformly controlled in the parameter N of the discrete model.

This work is related to inequalities in the approximation theory. Mainly, we study numerical solutions of delay Volterra integral equations by using a collocation method based on sigmoidal function approximation. Error estimation and convergence analysis are provided. At the end of the paper we display numerical simulations verifying our results.

The current work deals with the granular media equation whose probabilistic interpretation is the McKean–Vlasov diffusion. It is well known that the Laplacian provides a regularization of the solution. Indeed, for any t > 0, the solution is absolutely continuous with respect to the Lebesgue measure. It has also been proved that all the moments are bounded for positive t. However, the finiteness of the entropy of the solution is a new result which will be presented here.

We present functional inequalities and limit theorems for point processes. We prove a modified logarithmic Sobolev inequalities, a Stein inequality and a exact fourth moment theorem for a large class of point processes including mixed binomial processes and Poisson point processes. The proofs of these inequalities are inspired by the Malliavin-Stein approach and the $Gamma$-calculus of Bakry-Emery. The implementation of these techniques requires a development of a stochastic analysis for point processes. As point processes are essentially discrete, we design a theory to study non-diffusive random objects. For Poisson point processes, we extend the Stein inequality to study stable convergence with respect to limits that are conditionally Gaussian. Applications to Poisson approximations of Gaussian processes and random geometry are given. We discuss transport inequalities for mixed binomial processes and their consequences in terms of concentration of measure. On a generic metric measured space, we present a refinement of the notion of concentration of measure that takes into account the parallel enlargement of distinct sets. We link this notion of improved concentration with the eigenvalues of the metric Laplacian and with a version of the Ricci curvature based on multi-marginal optimal transport; Nous présentons des inégalités fonctionnelles pour les processus ponctuels. Nous prouvons une inégalité de Sobolev logarithmique modifiée, une inégalité de Stein et un théorème du moment quatrième sans terme de reste pour une classe de processus ponctuels qui contient les processus binomiaux et les processus de Poisson. Les preuves reposent sur des techniques inspirées de l'approche de Malliavin-Stein et du calcul avec l'opérateur $Gamma$ de Bakry-Émery. Pour mettre en œuvre ces techniques nous développons une analyse stochastique pour les processus ponctuels. Plus généralement, nous mettons au point une théorie d'analyse stochastique sans hypothèse de diffusion. Dans le cadre des processus de Poisson ponctuels, l'inégalité de Stein est généralisée pour étudier la convergence stable vers des limites conditionnellement gaussiennes. Nous appliquons ces résultats pour approcher des processus Gaussiens par des processus de Poisson composés et pour étudier des graphes aléatoires. Nous discutons d'inégalités de transport et de leur conséquence en termes de concentration de la mesure pour les processus binomiaux dont la taille de l'échantillon est aléatoire. Sur un espace métrique mesuré quelconque, nous présentons un développement de la concentration de la mesure qui prend en compte l'agrandissement parallèle d'ensembles disjoints. Cette concentration améliorée donne un contrôle de toutes les valeurs propres du Laplacien métrique. Nous discutons des liens de cette nouvelle notion avec une version de la courbure de Ricci qui fait intervenir le transport à plusieurs marginales

We study the convergence to equilibrium of a class of nonlinear recombination models. In analogy with Boltzmann's H theorem from kinetic theory, and in contrast with previous analysis of these models, convergence is measured in terms of relative entropy. The problem is formulated within a general framework that we refer to as Reversible Quadratic Systems. Our main result is a tight quantitative estimate for the entropy production functional. Along the way we establish some new entropy inequalities generalizing Shearer's and related inequalities., 27 pages

In molecular dynamics and sampling of high dimensional Gibb s measures coarse-graining is an important technique to reduce the dimensionality of the pro blem. We will study and quantify the coarse-graining error between the coarse-grained dynamic s and an effective dynamics. The effective dynamics is a Markov process on the coarse-grained state spa ce obtained by a closure procedure from the coarse-grained coefficients. We obtain error estimates b oth in relative entropy and Wasserstein distance, for both Langevin and overdamped Langevin dynami cs. The approach allows for vecto- rial coarse-graining maps. Hereby, the quality of the chose n coarse-graining is measured by certain functional inequalities encoding the scale separation of t he Gibbs measure. The method is based on error estimates between solutions of (kinetic) Fokker-Pla nck equations in terms of large-deviation rate functionals

In this article, we study generalization of the classical Talagrand transport-entropy inequality in which the Wasserstein distance is replaced by the entropic transportation cost. This class of inequalities has been introduced in the recent work (Probab. Theory Related Fields 174 (2019) 1–47), in connection with the study of Schrödinger bridges. We provide several equivalent characterizations in terms of reverse hypercontractivity for the heat semigroup, contractivity of the Hamilton–Jacobi–Bellman semigroup and dimension-free concentration of measure. Properties such as tensorization and relations to other functional inequalities are also investigated. In particular, we show that the inequalities studied in this article are implied by a Logarithmic Sobolev inequality and imply Talagrand inequality.

We study various transport-information inequalities under three different notions of Ricci curvature in the discrete setting: the curvature-dimension condition of Bakry and \'Emery, the exponential curvature-dimension condition of Bauer \textit{et al.} and the coarse Ricci curvature of Ollivier. We prove that under a curvature-dimension condition or coarse Ricci curvature condition, an $L_1$ transport-information inequality holds; while under an exponential curvature-dimension condition, some weak-transport information inequalities hold. As an application, we establish a Bonnet-Meyer's theorem under the curvature-dimension condition CD$(\kappa,\infty)$ of Bakry and \'Emery., Comment: 26 pages. Comments are welcome

In this work we present several quantitative results of convergence to equilibrium for the linear Boltzmann operator with soft potentials under Grad’s angular cut-off assumption. This is done by an adaptation of the famous entropy method and its variants, resulting in explicit algebraic, or even stretched exponential, rates of convergence to equilibrium under appropriate assumptions. The novelty in our approach is that it involves functional inequalities relating the entropy to its production rate, which have independent applications to equations with mixed linear and non-linear terms. We also briefly discuss some properties of the equation in the non-cut-off case and conjecture what we believe to be the right rate of convergence in that case., JAC was supported by project MTM2014-52056-P, funded by the Spanish government and the European Regional Development Fund. AE was partially supported by EPSRC grant EP/L002302/1 and partially supported by the Austrian Science Fund (FWF) grant M 2104-N32.

We present functional inequalities and limit theorems for point processes. We prove a modified logarithmic Sobolev inequalities, a Stein inequality and a exact fourth moment theorem for a large class of point processes including mixed binomial processes and Poisson point processes. The proofs of these inequalities are inspired by the Malliavin-Stein approach and the Γ-calculus of Bakry-Emery. The implementation of these techniques requires a development of a stochastic analysis for point processes. As point processes are essentially discrete, we design a theory to study non-diffusive random objects. For Poisson point processes, we extend the Stein inequality to study stable convergence with respect to limits that are conditionally Gaussian. Applications to Poisson approximations of Gaussian processes and random geometry are given. We discuss transport inequalities for mixed binomial processes and their consequences in terms of concentration of measure. On a generic metric measured space, we present a refinement of the notion of concentration of measure that takes into account the parallel enlargement of distinct sets. We link this notion of improved concentration with the eigenvalues of the metric Laplacian and with a version of the Ricci curvature based on multi-marginal optimal transport, Nous présentons des inégalités fonctionnelles pour les processus ponctuels. Nous prouvons une inégalité de Sobolev logarithmique modifiée, une inégalité de Stein et un théorème du moment quatrième sans terme de reste pour une classe de processus ponctuels qui contient les processus binomiaux et les processus de Poisson. Les preuves reposent sur des techniques inspirées de l'approche de Malliavin-Stein et du calcul avec l'opérateur Γ de Bakry-Émery. Pour mettre en œuvre ces techniques nous développons une analyse stochastique pour les processus ponctuels. Plus généralement, nous mettons au point une théorie d'analyse stochastique sans hypothèse de diffusion. Dans le cadre des processus de Poisson ponctuels, l'inégalité de Stein est généralisée pour étudier la convergence stable vers des limites conditionnellement gaussiennes. Nous appliquons ces résultats pour approcher des processus Gaussiens par des processus de Poisson composés et pour étudier des graphes aléatoires. Nous discutons d'inégalités de transport et de leur conséquence en termes de concentration de la mesure pour les processus binomiaux dont la taille de l'échantillon est aléatoire. Sur un espace métrique mesuré quelconque, nous présentons un développement de la concentration de la mesure qui prend en compte l'agrandissement parallèle d'ensembles disjoints. Cette concentration améliorée donne un contrôle de toutes les valeurs propres du Laplacien métrique. Nous discutons des liens de cette nouvelle notion avec une version de la courbure de Ricci qui fait intervenir le transport à plusieurs marginales

This thesis consists of three parts: The first and second parts focus on long-time asymptotics of macroscopic and kinetic models respectively, while in the third part we connect these regimes using different scaling approaches. (1) Keller–Segel-type aggregation-diffusion equations: We study a Keller–Segel-type model with non-linear power-law diffusion and non-local particle interaction: Does the system admit equilibria? If yes, are they unique? Which solutions converge to them? Can we determine an explicit rate of convergence? To answer these questions, we make use of the special gradient flow structure of the equation and its associated free energy functional for which the overall convexity properties are not known. Special cases of this family of models have been investigated in previous works, and this part of the thesis represents a contribution towards a complete characterisation of the asymptotic behaviour of solutions. (2) Hypocoercivity techniques for a fibre lay-down model: We show existence and uniqueness of a stationary state for a kinetic Fokker-Planck equation modelling the fibre lay-down process in non-woven textile production. Further, we prove convergence to equilibrium with an explicit rate. This part of the thesis is an extension of previous work which considered the case of a stationary conveyor belt. Adding the movement of the belt, the global equilibrium state is not known explicitly and a more general hypocoercivity estimate is needed. Although we focus here on a particular application, this approach can be used for any equation with a similar structure as long as it can be understood as a certain perturbation of a system for which the global Gibbs state is known. (3) Scaling approaches for collective animal behaviour models: We study the multi-scale aspects of self-organised biological aggregations using various scaling techniques. Not many previous studies investigate how the dynamics of the initial models are preserved via these scalings. Firstly, we consider two scaling approaches (parabolic and grazing collision limits) that can be used to reduce a class of non-local kinetic 1D and 2D models to simpler models existing in the literature. Secondly, we investigate how some of the kinetic spatio-temporal patterns are preserved via these scalings using asymptotic preserving numerical methods.

In a companion article we have introduced a notion of multiscale functional inequalities for functions X(A) of an ergodic stationary random field A on the ambient space Rd. These inequalities are multiscale weighted versions of standard Poincare, covariance, and logarithmic Sobolev inequalities. They hold for all the examples of fields A arising in the modelling of heterogeneous materials in the applied sciences whereas their standard versions are much more restrictive. In this contribution we first investigate the link between multiscale functional inequalities and more standard decorrelation or mixing properties of random fields. Next, we show that multiscale functional inequalities imply fine concentration properties for nonlinear functions X(A). This constitutes the main stochastic ingredient to the quenched large-scale regularity theory for random elliptic operators by the second author, Neukamm, and Otto, and to the corresponding quantitative stochastic homogenization results., SCOPUS: ar.j, info:eu-repo/semantics/published

The thesis focuses on the superconcentration phenomenon which appears in the study of the fluctuations of various moelds from current research (random matrices, spin glasses, discrete Gaussien free field, percolation,...). More precisely, the thesis mainly deals with superconcentration inequalities at an exponentiel level ; in particular for supremum of familu of Gaussian random variables. The principal tools used during this study are the hypercontractive property satisfied by some Markov semi-groups ; this approach leads to an extension of higher order of an inequality due to M. Talagrand. The first part of the thesis exposes the fundamental notions of concentration of measure, interpolation methods with Markovians semi-groups, functional inequalities, optimal transport and isoperimetry. Then, a survey of the literature concerning superconcentration phenomenon is done. The second part of the manuscript bring together, in different chapters, the results obtained during the thesis. Most of them are based on the dynamical representation of the variance along the semi-group of Ornstein-Uhlenbeck and its hypercontractive property. New ineqaulities are obtained at an exponential level and are illustrated on examples coming from extreme theory. This hypercontractive framework also gave birth to a new inequality on the discrete cube which leads to an application on the influence of second order of boolean functions. Finally, the last chapter is about the superconcentration phenomenon with an optimal transport approach. Some non asymptotic bounds on the variance and deviations inequalities are obtained for the maximum of an i.i.d. sample. Again, illustrations for usual laws of probability, belonging to different domain of attraction from extreme theory, are given.; Cette thèse porte sur le phénomène de superconcentration qui apparaît dans l'étude des fluctuations de divers modèles de la recherche actuelle (matrices aléatoires, verres de spins, champ libre gaussien discret, percolation,...). Plus particulièrement, la thèse est consacrée à l'examen d'inégalités de superconcentration à l'échelle exponentielle ; notamment pour des supremum de familles gaussiennes. Les outils mis en œuvre comprennent la propriété d'hypercontractivité de semi-groupes de Markov. Par ailleurs, celle-ci a conduit à une version d'ordre supérieur d'une inégalité sur la variance de M. Talagrand. La première partie de la thèse présente brièvement les notions essentielles de la théorie classique de la concentration de la mesure ainsi que les principaux outils, à savoir : méthodes d'interpolations à l'aide de semi-groupes markoviens, inégalités fonctionnelles, transport optimal et isopérimétrie. Un survol de la littérature existante est ensuite proposé. La deuxième partie du manuscrit rassemble, dans différents chapitres, les travaux que nous avons effectués durant cette thèse. Une grande partie de ceux-ci repose sur la représentation dynamique de la variance le long du semi-groupe d'Ornstein-Uhlenbeck et sa propriété d'hypercontractivité. De nouvelles inégalités de superconcentration sont obtenues au niveau exponentiel et illustrées sur des exemples provenant de la théorie des extrêmes. Le cadre de l'hypercontractivité a également conduit à une nouvelle inégalité sur le cube discret, celle-ci permettant une application sur l'influence d'ordre deux de fonctions booléennes. Enfin, le dernier chapitre aborde la phénomène de superconcentration par le transport optimal. Des majorations de la variance et des inégalités de déviations non asymptotiques pour le maximum de variables aléatoires indépendantes et de même loi sont obtenues. A nouveau, des illustrations pour des lois usuelles, appartenant aux différents domaines d'attraction de la théorie des extrêmes, sont proposées

The thesis focuses on the superconcentration phenomenon which appears in the study of the fluctuations of various moelds from current research (random matrices, spin glasses, discrete Gaussien free field, percolation,...). More precisely, the thesis mainly deals with superconcentration inequalities at an exponentiel level ; in particular for supremum of familu of Gaussian random variables. The principal tools used during this study are the hypercontractive property satisfied by some Markov semi-groups ; this approach leads to an extension of higher order of an inequality due to M. Talagrand. The first part of the thesis exposes the fundamental notions of concentration of measure, interpolation methods with Markovians semi-groups, functional inequalities, optimal transport and isoperimetry. Then, a survey of the literature concerning superconcentration phenomenon is done. The second part of the manuscript bring together, in different chapters, the results obtained during the thesis. Most of them are based on the dynamical representation of the variance along the semi-group of Ornstein-Uhlenbeck and its hypercontractive property. New ineqaulities are obtained at an exponential level and are illustrated on examples coming from extreme theory. This hypercontractive framework also gave birth to a new inequality on the discrete cube which leads to an application on the influence of second order of boolean functions. Finally, the last chapter is about the superconcentration phenomenon with an optimal transport approach. Some non asymptotic bounds on the variance and deviations inequalities are obtained for the maximum of an i.i.d. sample. Again, illustrations for usual laws of probability, belonging to different domain of attraction from extreme theory, are given.; Cette thèse porte sur le phénomène de superconcentration qui apparaît dans l'étude des fluctuations de divers modèles de la recherche actuelle (matrices aléatoires, verres de spins, champ libre gaussien discret, percolation,...). Plus particulièrement, la thèse est consacrée à l'examen d'inégalités de superconcentration à l'échelle exponentielle ; notamment pour des supremum de familles gaussiennes. Les outils mis en œuvre comprennent la propriété d'hypercontractivité de semi-groupes de Markov. Par ailleurs, celle-ci a conduit à une version d'ordre supérieur d'une inégalité sur la variance de M. Talagrand. La première partie de la thèse présente brièvement les notions essentielles de la théorie classique de la concentration de la mesure ainsi que les principaux outils, à savoir : méthodes d'interpolations à l'aide de semi-groupes markoviens, inégalités fonctionnelles, transport optimal et isopérimétrie. Un survol de la littérature existante est ensuite proposé. La deuxième partie du manuscrit rassemble, dans différents chapitres, les travaux que nous avons effectués durant cette thèse. Une grande partie de ceux-ci repose sur la représentation dynamique de la variance le long du semi-groupe d'Ornstein-Uhlenbeck et sa propriété d'hypercontractivité. De nouvelles inégalités de superconcentration sont obtenues au niveau exponentiel et illustrées sur des exemples provenant de la théorie des extrêmes. Le cadre de l'hypercontractivité a également conduit à une nouvelle inégalité sur le cube discret, celle-ci permettant une application sur l'influence d'ordre deux de fonctions booléennes. Enfin, le dernier chapitre aborde la phénomène de superconcentration par le transport optimal. Des majorations de la variance et des inégalités de déviations non asymptotiques pour le maximum de variables aléatoires indépendantes et de même loi sont obtenues. A nouveau, des illustrations pour des lois usuelles, appartenant aux différents domaines d'attraction de la théorie des extrêmes, sont proposées

The object of this thesis is the study of some analytical and asymptotic properties of Markov processes, and their applications to Stein's method. The point of view consists in the development of functional inequalities in order to obtain upper-bounds on the distance between probability distributions. The first part is devoted to the asymptotic study of time-inhomogeneous Markov processes through Poincaré-like inequalities, established by precise estimates on the spectrum of the transition operator. The first investigation takes place within the framework of the Central Limit Theorem, which states the convergence of the renormalized sum of random variables towards the normal distribution. It results in the statement of a Berry-Esseen bound allowing to quantify this convergence with respect to the chi-2 distance, a natural quantity which had not been investigated in this setting. It therefore extends similar results relative to other distances (Kolmogorov, total variation, Wasserstein). Keeping with the non-homogeneous framework, we consider a weakly mixing process linked to a stochastic algorithm for median approximation. This process evolves by jumps of two sorts (to the right or to the left) with time-dependent size and intensity. An upper-bound on the Wasserstein distance of order 1 between the marginal distribution of the process and the normal distribution is provided when the latter is invariant under the dynamic, and extended to examples where only the asymptotic normality stands. The second part concerns intertwining relations between (homogeneous) Markov processes and gradients, which can be seen as refinment of the Bakry-Emery criterion, and their application to Stein's method, a collection of techniques to estimate the distance between two probability distributions. Second order intertwinings for birth-death processes are stated, going one step further than the existing first order relations. These relations are then exploited to construct an original and universal method of evaluation of discrete Stein's factors, a key component of Stein-Chen's method.; L'objet de cette thèse est l'étude de certaines propriétés analytiques et asymptotiques des processus de Markov, et de leurs applications à la méthode de Stein. Le point de vue considéré consiste à déployer des inégalités fonctionnelles pour majorer la distance entre lois de probabilité. La première partie porte sur l'étude asymptotique de processus de Markov inhomogènes en temps via des inégalités de type Poincaré, établies par l'analyse spectrale fine de l'opérateur de transition. On se place d'abord dans le cadre du théorème central limite, qui affirme que la somme renormalisée de variables aléatoires converge vers la mesure gaussienne, et l'étude est consacrée à l'obtention d'une borne à la Berry-Esseen permettant de quantifier cette convergence. La distance choisie est une quantité naturelle et encore non étudiée dans ce cadre, la distance du chi-2, complétant ainsi la littérature relative à d'autres distances (Kolmogorov, variation totale, Wasserstein). Toujours dans le contexte non-homogène, on s'intéresse ensuite à un processus peu mélangeant relié à un algorithme stochastique de recherche de médiane. Ce processus évolue par sauts de deux types (droite ou gauche), dont la taille et l'intensité dépendent du temps. Une majoration de la distance de Wasserstein d'ordre 1 entre la loi du processus et la mesure gaussienne est établie dans le cas où celle-ci est invariante sous la dynamique considérée, et étendue à des exemples où seule la normalité asymptotique est vérifiée. La seconde partie s'attache à l'étude des entrelacements entre processus de Markov (homogènes) et gradients, qu'on peut interpréter comme un raffinement du critère de Bakry-Emery, et leur application à la méthode de Stein, qui est un ensemble de techniques permettant de majorer la distance entre deux mesures de probabilité. On prouve l'existence de relations d'entrelacement du second ordre pour les processus de naissance-mort, allant ainsi plus loin que les relations du premier ordre connues. Ces relations sont mises à profit pour construire une méthode originale et universelle d'évaluation des facteurs de Stein relatifs aux mesures de probabilité discrètes, qui forment une composante essentielle de la méthode de Stein-Chen.

The object of this thesis is the study of some analytical and asymptotic properties of Markov processes, and their applications to Stein's method. The point of view consists in the development of functional inequalities in order to obtain upper-bounds on the distance between probability distributions. The first part is devoted to the asymptotic study of time-inhomogeneous Markov processes through Poincaré-like inequalities, established by precise estimates on the spectrum of the transition operator. The first investigation takes place within the framework of the Central Limit Theorem, which states the convergence of the renormalized sum of random variables towards the normal distribution. It results in the statement of a Berry-Esseen bound allowing to quantify this convergence with respect to the chi-2 distance, a natural quantity which had not been investigated in this setting. It therefore extends similar results relative to other distances (Kolmogorov, total variation, Wasserstein). Keeping with the non-homogeneous framework, we consider a weakly mixing process linked to a stochastic algorithm for median approximation. This process evolves by jumps of two sorts (to the right or to the left) with time-dependent size and intensity. An upper-bound on the Wasserstein distance of order 1 between the marginal distribution of the process and the normal distribution is provided when the latter is invariant under the dynamic, and extended to examples where only the asymptotic normality stands. The second part concerns intertwining relations between (homogeneous) Markov processes and gradients, which can be seen as refinment of the Bakry-Emery criterion, and their application to Stein's method, a collection of techniques to estimate the distance between two probability distributions. Second order intertwinings for birth-death processes are stated, going one step further than the existing first order relations. These relations are then exploited to construct an original and universal method of evaluation of discrete Stein's factors, a key component of Stein-Chen's method.; L'objet de cette thèse est l'étude de certaines propriétés analytiques et asymptotiques des processus de Markov, et de leurs applications à la méthode de Stein. Le point de vue considéré consiste à déployer des inégalités fonctionnelles pour majorer la distance entre lois de probabilité. La première partie porte sur l'étude asymptotique de processus de Markov inhomogènes en temps via des inégalités de type Poincaré, établies par l'analyse spectrale fine de l'opérateur de transition. On se place d'abord dans le cadre du théorème central limite, qui affirme que la somme renormalisée de variables aléatoires converge vers la mesure gaussienne, et l'étude est consacrée à l'obtention d'une borne à la Berry-Esseen permettant de quantifier cette convergence. La distance choisie est une quantité naturelle et encore non étudiée dans ce cadre, la distance du chi-2, complétant ainsi la littérature relative à d'autres distances (Kolmogorov, variation totale, Wasserstein). Toujours dans le contexte non-homogène, on s'intéresse ensuite à un processus peu mélangeant relié à un algorithme stochastique de recherche de médiane. Ce processus évolue par sauts de deux types (droite ou gauche), dont la taille et l'intensité dépendent du temps. Une majoration de la distance de Wasserstein d'ordre 1 entre la loi du processus et la mesure gaussienne est établie dans le cas où celle-ci est invariante sous la dynamique considérée, et étendue à des exemples où seule la normalité asymptotique est vérifiée. La seconde partie s'attache à l'étude des entrelacements entre processus de Markov (homogènes) et gradients, qu'on peut interpréter comme un raffinement du critère de Bakry-Emery, et leur application à la méthode de Stein, qui est un ensemble de techniques permettant de majorer la distance entre deux mesures de probabilité. On prouve l'existence de relations d'entrelacement du second ordre pour les processus de naissance-mort, allant ainsi plus loin que les relations du premier ordre connues. Ces relations sont mises à profit pour construire une méthode originale et universelle d'évaluation des facteurs de Stein relatifs aux mesures de probabilité discrètes, qui forment une composante essentielle de la méthode de Stein-Chen.

In this paper, we prove a semigroup version of the Ahlswede–Daykin four functions theorem on the discrete hypercube, and of its generalization to 2n functions.

We consider macroscopic descriptions of particles where repulsion is modelled by non-linear power-law diffusion and attraction by a homogeneous singular kernel leading to variants of the Keller–Segel model of chemotaxis. We analyse the regime in which diffusive forces are stronger than attraction between particles, known as the diffusion-dominated regime, and show that all stationary states of the system are radially symmetric non-increasing and compactly supported. The model can be formulated as a gradient flow of a free energy functional for which the overall convexity properties are not known. We show that global minimisers of the free energy always exist. Further, they are radially symmetric, compactly supported, uniformly bounded and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C^\infty $$\end{document}C∞ inside their support. Global minimisers enjoy certain regularity properties if the diffusion is not too slow, and in this case, provide stationary states of the system. In one dimension, stationary states are characterised as optimisers of a functional inequality which establishes equivalence between global minimisers and stationary states, and allows to deduce uniqueness.

We consider $d\times d$ tensors $A(x)$ that are symmetric, positive semi-definite, and whose row-divergence vanishes identically. We establish sharp inequalities for the integral of $(\det A)^{\frac1{d-1}}$. We apply them to models of compressible inviscid fluids: Euler equations, Euler--Fourier, relativistic Euler, Boltzman, BGK, etc... We deduce an {\em a priori} estimate for a new quantity, namely the space-time integral of $\rho^{\frac1n}p$, where $\rho$ is the mass density, $p$ the pressure and $n$ the space dimension. For kinetic models, the corresponding quantity generalizes Bony's functional.

In this paper we consider a sum of modified Bessel functions of the first kind of which particular case is used in the study of Kanter's sharp modified Bessel function bound for concentrations of some sums of independent symmetric random vectors. We present some monotonicity and convexity properties for that sum of modified Bessel functions of the first kind, as well as some Tur\'an type inequalities, lower and upper bounds. Moreover, we point out an error in Kanter's paper [Ka] and at the end of the paper we pose an open problem, which may be of interest for further research., Comment: 8 pages

International audience; This paper is devoted to sharp interpolation inequalities on the sphere and their proof using flows. The method explains some rigidity results and proves uniqueness in related semilinear elliptic equations. Nonlinear flows allow to cover the interval of exponents ranging from Poincaré to Sobolev inequality, while an intriguing limitation (an upper bound on the exponent) appears in the carré du champ method based on the heat flow. We investigate this limitation, describe a counter-example for exponents which are above the bound, and obtain improvements below.

In the past 20 years the optimal transport theory revealed to be an efficient tool to study the asymptotic behavior for diffusion equations, to prove functional inequalities, to extend geometrical properties in extremely general spaces like metric measure spaces, etc. The curvature-dimension of the Bakry-Émery theory appears as the cornerstone of those applications. Just think to the easier and most important case of the quadratic Wasserstein distance W2: contraction of the heat flow in W2 characterizes uniform lower bounds for the Ricci curvature; the transport Talagrand inequality, comparing W2 to the relative entropy is implied and implies via the HWI inequality the log-Sobolev inequality; McCann geodesics in the Wasserstein space (P2(Rn),W2) allow to prove important functional properties like convexity, and standard functional inequalities, such as isoperimetry, measure concentration properties, the Prékopa Leindler inequality and so on. However the lack of regularity of optimal maps, requires non-smooth analysis arguments. The Schrödinger problem is an entropy minimization problem with marginal constraints and a fixed reference process. From the Large deviation theory, when the reference process is driven by the Brownian motion, its minimal value A converges to W2 when the temperature goes to zero. The entropic interpolations, solutions of the Schrödinger problem, are characterized in terms of Markov semigroups, hence computation along them naturally involves Γ2 computations and the curvature-dimension condition. Dating back to the 1930s, and neglected for decades, the Schrödinger problem recently enjoys an increasing popularity in different fields, thanks to this relation to optimal transport, smoothness of solutions and other well performing properties in numerical computations. The aim of this work is twofold. First we study some analogy between the Schrödinger problem and optimal transport providing new proofs of the dual Kantorovich and the dynamic Benamou-Brenier formulations for the entropic cost A. Secondly, as an application of these connections we derive some functional properties and inequalities under curvature-dimensions conditions. In particular, we prove the concavity of the exponential entropy along entropic interpolations under the curvature-dimension condition CD(0, n) and regularity of the entropic cost along the heat flow. We also give different proofs the Evolutionary Variational Inequality for A and contraction of the heat flow in A, recovering as a limit case the classical results in W2, under CD(κ,∞) and also in the flat dimensional case. Finally we propose an easy proof of the Gaussian concentration property via the Schrödinger problem as an alternative to classical arguments as the Marton argument which is based on optimal transport, Au cours des 20 dernières années, la théorie du transport optimal s’est revelée être un outil efficace pour étudier le comportement asymptotique dans le cas des équations de diffusion, pour prouver des inégalités fonctionnelles et pour étendre des propriétés géométriques dans des espaces extrêmement généraux comme des espaces métriques mesurés, etc. La condition de courbure-dimension de la théorie Bakry-Emery apparaît comme la pierre angulaire de ces applications. Il suffit de penser au cas le plus simple et le plus important de la distance quadratique de Wasserstein W2 : la contraction du flux de chaleur en W2 caractérise les bornes inférieures uniformes pour la courbure de Ricci ; l’inégalité de Talagrand du transport, comparant W2 à l’entropie relative est impliquée et implique, par l’inégalité HWI, l’inégalité log-Sobolev ; les géodésiques de McCann dans l’espace de Wasserstein (P2(Rn),W2) permettent de prouver des propriétés fonctionnelles importantes comme la convexité, et des inégalités fonctionnelles standards telles que l’isopérymétrie, des propriétés de concentration de mesure, l’inégalité de Prékopa-Leindler et ainsi de suite. Néanmoins, le manque de régularité des plans minimisation nécessite des arguments d’analyse non lisse. Le problème de Schrödinger est un problème de minimisation de l’entropie avec des contraintes marginales et un processus de référence fixes. À partir de la théorie des grandes déviations, lorsque le processus de référence est le mouvement Brownien, sa valeur minimale A converge vers W2 lorsque la température est nulle. Les interpolations entropiques, solutions du problème de Schrödinger, sont caractérisées en termes de semigroupes de Markov, ce qui implique naturellement les calculs Γ2 et la condition de courbure-dimension. Datant des années 1930 et négligé pendant des décennies, le problème de Schrodinger connaît depuis ces dernières années une popularité croissante dans différents domaines, grâce à sa relation avec le transport optimal, à la regularité de ses solutions, et à d’autres propriétés performantes dans des calculs numériques. Le but de ce travail est double. D’abord, nous étudions certaines analogies entre le problème de Schrödinger et le transport optimal fournissant de nouvelles preuves de la formulation duale de Kantorovich et de celle, dynamique, de Benamou-Brenier pour le coût entropique A. Puis, en tant qu’application de ces connexions, nous dérivons certaines propriétés et inégalités fonctionnelles sous des conditions de courbure-dimension. En particulier, nous prouvons la concavité de l’entropie exponentielle le long des interpolations entropiques sous la condition de courbure-dimension CD(0, n) et la régularité du coût entropique le long du flot de la chaleur. Nous donnons également différentes preuves de l’inégalité variationnelle évolutionnaire pour A et de la contraction du flux de la chaleur en A, en retrouvant comme cas limite, les résultats classiques en W2, sous CD(κ,∞) et CD(0, n). Enfin, nous proposons une preuve simple de la propriété de concentration gaussienne via le problème de Schrödinger comme alternative aux arguments classiques tel que l’argument de Marton basé sur le transport optimal

International audience; In this paper we consider a family of Caffarelli-Kohn-Nirenberg interpolation inequalities (CKN), with two radial power law weights and exponents in a subcritical range. We address the question of symmetry breaking: are the optimal functions radially symmetric, or not ? Our intuition comes from a weighted fast diffusion (WFD) flow: if symmetry holds, then an explicit entropy - entropy production inequality which governs the intermediate asymptotics is indeed equivalent to (CKN), and the self-similar profiles are optimal for (CKN). We establish an explicit symmetry breaking condition by proving the linear instability of the radial optimal functions for (CKN). Symmetry breaking in (CKN) also has consequences on entropy - entropy production inequalities and on the intermediate asymptotics for (WFD). Even when no symmetry holds in (CKN), asymptotic rates of convergence of the solutions to (WFD) are determined by a weighted Hardy-Poincaré inequality which is interpreted as a linearized entropy - entropy production inequality. All our results rely on the study of the bottom of the spectrum of the linearized diffusion operator around the self-similar profiles, which is equivalent to the linearization of (CKN) around the radial optimal functions, and on variational methods. Consequences for the (WFD) flow will be studied in Part II of this work.

We prove the following theorem. Let α and β be real numbers. The inequality Γ ( x α + y β ) ≤ Γ ( Γ ( x ) + Γ ( y ) ) holds for all positive real numbers x and y if and only if α = β = − γ . Here, Γ and γ = 0.57721 … denote Euler’s gamma function and Euler’s constant, respectively.

We develop a new and systematic method for proving entropic Ricci curvature lower bounds for Markov chains on discrete sets. Using different methods, such bounds have recently been obtained in several examples (e.g., 1-dimensional birth and death chains, product chains, Bernoulli-Laplace models, and random transposition models). However, a general method to obtain discrete Ricci bounds had been lacking. Our method covers all of the examples above. In addition, we obtain new Ricci curvature bounds for zero-range processes on the complete graph. The method is inspired by recent work of Caputo, Dai Pra and Posta on discrete functional inequalities., Comment: Published at http://dx.doi.org/10.1214/15-AAP1133 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)

We present several inequalities for f a ( x ) = Γ ( a , x ) Γ ( a , 0 ) ( a > 0 , x ⩾ 0 ) , where Γ ( a , x ) is the incomplete gamma function. One of our theorems states that the inequalities f a ( S p ( x 1 , … , x n ) ) ⩽ f a ( x 1 ) ⋯ f a ( x n ) ⩽ f a ( S q ( x 1 , … , x n ) ) ( p , q > 0 ) hold for all nonnegative real numbers x 1 , … , x n ( n ⩾ 2 ) if and only if p ⩽ m i n ( a , 1 ) and q ⩾ m a x ( a , 1 ) . Here, S t ( x 1 , … , x n ) denotes the power sum of order t. This extends and complements a result published by Ismail and Laforgia in 2006.