Faisceaux pervers, homomorphisme de changement de base et lemme fondamental de Jacquet et Ye

We give a geometric interpretation of the base change homomorphism between the Hecke algebra of GL(n) for an unramified extension of local fields of positive characteristic. For this, we use some results of Ginzburg, Mirkovic and Vilonen related to the geometric Satake isomorphism. We give new proof for these results in the positive characteristic case. By using that geometric interpretation of the base change homomorphism, we prove the fundamental lemma of Jacquet and Ye for arbitrary Hecke function in the the equal characteristic case.Comment: 66 pages, Latex, frenc

Shibboleth as a Tool for Authorized Access Control to the Subversion Repository System

Shibboleth is an architecture and protocol for allowing users to authenticate and be authorized to use a remote resource by logging into the identity management system that is maintained at their home institution. With Shibboleth, a federation of institutions can share resources among users and yet allow the administration of both the user access control to resources and the user identity and attribute information to be performed at the hosting or home institution. Subversion is a version control repository system that allows the creation of fine-grained permissions to files and directories. In this project an infrastructure, Shibbolized Subversion, has been created that consists of a Subversion repository with an Apache web interface that is protected by a Shibboleth authentication system. The infrastructure can allow authorized and authenticated data sharing between institutions yet retains simplicity and protects privacy for users. In addition, it also relieves local administrators from the task of having to perform extra account management for users from other institutions. This paper describes the Shibboleth and Subversion systems, the implementation of the file sharing infrastructure, and issues of attribute maintenance, privacy and security

Bounded Expectations: Resource Analysis for Probabilistic Programs

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials of the inputs. The new technique combines manual state-of-the-art reasoning techniques for probabilistic programs with an effective method for automatic resource-bound analysis of deterministic programs. It can be seen as both, an extension of automatic amortized resource analysis (AARA) to probabilistic programs and an automation of manual reasoning for probabilistic programs that is based on weakest preconditions. As a result, bound inference can be reduced to off-the-shelf LP solving in many cases and automatically-derived bounds can be interactively extended with standard program logics if the automation fails. Building on existing work, the soundness of the analysis is proved with respect to an operational semantics that is based on Markov decision processes. The effectiveness of the technique is demonstrated with a prototype implementation that is used to automatically analyze 39 challenging probabilistic programs and randomized algorithms. Experimental results indicate that the derived constant factors in the bounds are very precise and even optimal for many programs