Lensing of 21-cm Fluctuations by Primordial Gravitational Waves

Weak-gravitational-lensing distortions to the intensity pattern of 21-cm radiation from the dark ages can be decomposed geometrically into curl and curl-free components. Lensing by primordial gravitational waves induces a curl component, while the contribution from lensing by density fluctuations is strongly suppressed. Angular fluctuations in the 21-cm background extend to very small angular scales, and measurements at different frequencies probe different shells in redshift space. There is thus a huge trove of information with which to reconstruct the curl component of the lensing field, allowing tensor-to-scalar ratios conceivably as small as r∼10^(-9)—far smaller than those currently accessible—to be probed

On adaptive posterior concentration rates

We investigate the problem of deriving posterior concentration rates under different loss functions in nonparametric Bayes. We first provide a lower bound on posterior coverages of shrinking neighbourhoods that relates the metric or loss under which the shrinking neighbourhood is considered, and an intrinsic pre-metric linked to frequentist separation rates. In the Gaussian white noise model, we construct feasible priors based on a spike and slab procedure reminiscent of wavelet thresholding that achieve adaptive rates of contraction under $L^2$ or $L^{\infty}$ metrics when the underlying parameter belongs to a collection of H\"{o}lder balls and that moreover achieve our lower bound. We analyse the consequences in terms of asymptotic behaviour of posterior credible balls as well as frequentist minimax adaptive estimation. Our results are appended with an upper bound for the contraction rate under an arbitrary loss in a generic regular experiment. The upper bound is attained for certain sieve priors and enables to extend our results to density estimation.Comment: Published at http://dx.doi.org/10.1214/15-AOS1341 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Nonparametric estimation of the volatility under microstructure noise: wavelet adaptation

We study nonparametric estimation of the volatility function of a diffusion process from discrete data, when the data are blurred by additional noise. This noise can be white or correlated, and serves as a model for microstructure effects in financial modeling, when the data are given on an intra-day scale. By developing pre-averaging techniques combined with wavelet thresholding, we construct adaptive estimators that achieve a nearly optimal rate within a large scale of smoothness constraints of Besov type. Since the underlying signal (the volatility) is genuinely random, we propose a new criterion to assess the quality of estimation; we retrieve the usual minimax theory when this approach is restricted to deterministic volatility.Adaptive estimation; diffusion processes; high-frequency data; microstructure noise; minimax estimation; semimartingales; wavelets.

Line planning with user-optimal route choice

We consider the problem of designing lines in a public transport system, where we include user-optimal route choice. The model we develop ensures that there is enough capacity present for every passenger to travel on a shortest route. We present two different integer programming formulations for this problem, and discuss exact solution approaches. To solve large-scale line planning instances, we also implemented a genetic solution algorithms. We test our algorithms in computational experiments using randomly generated instances along realistic data, as well as a realistic instance modeling the German long-distance network. We examine the advantages and disadvantages of using such user-optimal solutions, and show that our algorithms sufficiently scale with instance size to be used for practical purposes

Benchmarking de l’agritourisme en Autriche, Allemagne, France et Suisse

Ce travail se focalise sur l’agritourisme en Allemagne, Autriche, France et Suisse. Son objectif est d’analyser la situation de ce secteur puis, d’en extraire les bonnes pratiques, afin d’apporter des recommandations et des pistes d’améliorations pour développer l’agritourisme suisse de manière durable. Elles concernent autant les politiques que l’association nationale ou les exploitants. Pour la rédaction de ce travail, des recherches sur internet ont été nécessaires. Des études et des ouvrages ont été lus afin d’établir un état des lieux de l’agritourisme dans les différents pays. Un benchmarking a été effectué en suivant le processus de Camp afin de comparer la Suisse aux leader européens. De plus, un questionnaire a été rédigé et envoyé à des professionnels du terrain (dans les quatre pays) afin de compléter les informations. Les résultats du benchmarking ont montré qu’en Allemagne, en Autriche et en France le secteur est bien développé et se professionnalise. L’Autriche reste tout de même le leader grâce à l’ancrage de l’agriculture dans le tourisme. Aussi, ce pays compte le pourcentage le plus élevé d’agriculteurs qui pratiquent l’accueil. Les offres sont regroupées sous une même association et il en existe peu d’indépendantes. Malgré la création de la structure Agritourisme Suisse, la Suisse a un réel retard dans ce domaine. Cette association représente un grand pas vers le succès mais il reste encore beaucoup de de mesures et d’efforts à entreprendre. Les agriculteurs doivent encore faire face à de nombreuses contraintes administratives mais surtout législatives sans connaître le réel retour sur leur investissement