Publications associées à Machine de Turing probabiliste

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Andreas Pautz, Vincent Pierre Lamirand, Thomas Jean-François Ligonnet, Axel Guy Marie Laureau

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

2024

Spatial Isolation Implies Zero Knowledge Even in a Quantum World

Alessandro Chiesa

Zero knowledge plays a central role in cryptography and complexity. The seminal work of Ben-Or et al. (STOC 1988) shows that zero knowledge can be achieved unconditionally for any language in NEXP, as long as one is willing to make a suitable physical assu ...

ASSOC COMPUTING MACHINERY2022

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

Edoardo Charbon, Claudio Bruschini, Ivan Michel Antolovic, Mario Stipcevic

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

SPIE2021

Tropical Ehrhart Theory and Tropical Volume

Matthias Schymura, Georg Peter Loho

We introduce a novel intrinsic volume concept in tropical geometry. This is achieved by developing the foundations of a tropical analog of lattice point counting in polytopes. We exhibit the basic properties and compare it to existing measures. Our exposit ...

2019

Efficient Quantum Algorithms for GHZ and W States, and Implementation on the IBM Quantum Computer

Nicolas Macris, Clément Christian Javerzac-Galy, Marc-André Dupertuis, Kenichi Komagata, Chun Lam Chan, Fabien Gremion, Jarla Thiesbrummel, Romain Fournier

Efficient deterministic algorithms are proposed with logarithmic step complexities for the generation of entangled GHZ(N) and W-N states useful for quantum networks, and an implementation on the IBM quantum computer up to N = 16 is demonstrated. Improved q ...

WILEY2019

Real-time implementation with FPGA-based DAQ system of a probabilistic disruption predictor from scratch

Olivier Sauter, Ambrogio Fasoli, Basil Duval, Stefano Coda, Martinus Gijs, Jonathan Graves, Yves Martin, Duccio Testa, Patrick Blanchard, Bruno Emanuel Ferreira De Sousa Correia

Real-time (RT) disruption prediction (DP) is essential to trigger mitigation actions that avoid irreversible damage to the devices. This paper deals with disruption mitigation alarms and performs the RT implementation of a probabilistic predictor. The RT i ...

2018

Applications of Real-Time Simulation Technologies in Power and Energy Systems

Mario Paolone

Real-time (RT) simulation is a highly reliable simulation method that is mostly based on electromagnetic transient simulation of complex systems comprising many domains. It is increasingly used in power and energy systems for both academic research and ind ...

2015

Tight Bounds for Asynchronous Renaming

Rachid Guerraoui, Seth Gilbert, Dan Alistarh

This article presents the first tight bounds on the time complexity of shared-memory renaming, a fundamental problem in distributed computing in which a set of processes need to pick distinct identifiers from a small namespace. We first prove an individual ...

Association for Computing Machinery2014

Optimal-Time Adaptive Strong Renaming, with Applications to Counting

Seth Gilbert, Dan Alistarh, Morteza Zadimoghaddam

We give two new randomized algorithms for tight renaming, both of which work against an adaptive adversary. The first uses repeated sampling over a sequence of arrays of decreasing size to assign unique names to each of

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processes with step complexity $ ...

Acm Order Department, P O Box 64145, Baltimore, Md 21264 Usa2011

Context models on sequences of covers

Christos Dimitrakakis

We present a class of models that, via a simple construction, enables exact, incremental, non-parametric, polynomial-time, Bayesian inference of conditional measures. The approach relies upon creating a sequence of covers on the conditioning variable and m ...

2011