Concept

Machine de Turing probabiliste

Publications associées (32)

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

High-throughput screening of Weyl semimetals

Nicola Marzari, Davide Campi, Davide Grassano

Topological Weyl semimetals represent a novel class of nontrivial materials, where band crossings with linear dispersions take place at generic momenta across reciprocal space. These crossings give rise to low -energy properties akin to those of Weyl fermi ...

College Pk2024

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

Cirque /Machine.Circus as a space Machine

Au début des années 90, la ville industrielle de Bilbao ayant subi une crise économique, mise sur l’impact de l'édification du Guggenheim pour relancer la capitale basque. Ce projet envisage la possibilité inverse. L’architecture est mouvante, le spectateu ...

2019

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, Kenichi Komagata, Marc-André Dupertuis, 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, Jonathan Graves, Yves Martin, Duccio Testa, Patrick Blanchard, Alessandro Pau, Cristian Sommariva, Henri Weisen, Richard Pitts, Yann Camenen, Jan Horacek, Javier García Hernández, Marco Wischmeier, Nicola Vianello, Mikhail Maslov, Federico Nespoli, Yao Zhou, David Pfefferlé, Davide Galassi, Antonio José Pereira de Figueiredo, Jonathan Marc Philippe Faustin, Liang Yao, Dalziel Joseph Wilson, Hamish William Patten, Samuel Lanthaler, Bernhard Sieglin, Otto Asunta

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

Uncertainty Quantification of geochemical and mechanical compaction in layered sedimentary basins

Fabio Nobile, Lorenzo Tamellini, Anna Scotti

In this work we propose an Uncertainty Quantification methodology for sedimentary basins evolution under mechanical and geochemical compaction processes, which we model as a coupled, time-dependent, non-linear, monodimensional (depth-only) system of PDEs w ...

Elsevier2018

Robust Discriminative Clustering with Sparse Regularizers

Nicolas Henri Bernard Flammarion

Clustering high-dimensional data often requires some form of dimensionality reduction, where clustered variables are separated from "noise-looking" variables. We cast this problem as finding a low-dimensional projection of the data which is well-clustered. ...

2017

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