École Normale Supérieure

About: École Normale Supérieure is a other organization based out in Paris, Île-de-France, France. It is known for research contribution in the topics: Population & Catalysis. The organization has 68439 authors who have published 99414 publications receiving 3092008 citations.

Underplating in the Himalaya-Tibet collision zone revealed by the Hi-CLIMB experiment.

Abstract: We studied the formation of the Himalayan mountain range and the Tibetan Plateau by investigating their lithospheric structure. Using an 800-kilometer-long, densely spaced seismic array, we have constructed an image of the crust and upper mantle beneath the Himalayas and the southern Tibetan Plateau. The image reveals in a continuous fashion the Main Himalayan thrust fault as it extends from a shallow depth under Nepal to the mid-crust under southern Tibet. Indian crust can be traced to 31°N. The crust/mantle interface beneath Tibet is anisotropic, indicating shearing during its formation. The dipping mantle fabric suggests that the Indian mantle is subducting in a diffuse fashion along several evolving subparallel structures.

Connected Histories: Notes towards a Reconfiguration of Early Modern Eurasia

Abstract: The majority of Japanese even today believe that the politico-cultural universe of the Edo period was fundamentally determined by the closure of the country. They also think that the opening of Japan can be reduced to the development of exchanges with the West, following the birth of the Meiji regime. It is hard for them to imagine that Japan developed in relation with other Asian countries, since they are hardly used to appreciating Asian cultures.

Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights

Abstract: Image denoising is an important problem in image processing since noise may interfere with visual or automatic interpretation. This paper presents a new approach for image denoising in the case of a known uncorrelated noise model. The proposed filter is an extension of the nonlocal means (NL means) algorithm introduced by Buades, which performs a weighted average of the values of similar pixels. Pixel similarity is defined in NL means as the Euclidean distance between patches (rectangular windows centered on each two pixels). In this paper, a more general and statistically grounded similarity criterion is proposed which depends on the noise distribution model. The denoising process is expressed as a weighted maximum likelihood estimation problem where the weights are derived in a data-driven way. These weights can be iteratively refined based on both the similarity between noisy patches and the similarity of patches extracted from the previous estimate. We show that this iterative process noticeably improves the denoising performance, especially in the case of low signal-to-noise ratio images such as synthetic aperture radar (SAR) images. Numerical experiments illustrate that the technique can be successfully applied to the classical case of additive Gaussian noise but also to cases such as multiplicative speckle noise. The proposed denoising technique seems to improve on the state of the art performance in that latter case.

Generation of Einstein-Podolsky-Rosen Pairs of Atoms

Abstract: Pairs of atoms have been prepared in an entangled state of the Einstein-Podolsky-Rosen (EPR) type. They were produced by the exchange of a single photon between the atoms in a high $Q$ cavity. The atoms, entangled in a superposition involving two different circular Rydberg states, were separated by a distance of the order of 1 cm. At variance with most previous EPR experiments, this one involves massive particles. It can be generalized to three or more atoms and opens the way to new tests of nonlocality in mesoscopic quantum systems.