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Engineering random spin models with atoms in a high-finesse cavity

Jean-Philippe Brantut, Nick Jacob Sauerwein, Tigrane Arthur Cantat Moltrecht

Random spin models play a key role in our understanding of disorder and complex many-body systems. Two all-to-all interacting, disordered models have now been realized using a cavity quantum electrodynamics platform. ...

NATURE PORTFOLIO2023

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

Jan Sickmann Hesthaven, Nicolò Ripamonti, Cecilia Pagliantini

. High-resolution simulations of particle-based kinetic plasma models typically require a high number of particles and thus often become computationally intractable. This is exacerbated in multi-query simulations, where the problem depends on a set of para ...

AMER MATHEMATICAL SOC2023

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

SPRINGER2023

Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins

Anne-Florence Raphaëlle Bitbol

Author summaryWhen two protein families interact, their sequences feature statistical dependencies. First, interacting proteins tend to share a common evolutionary history. Second, maintaining structure and interactions through the course of evolution yiel ...

PUBLIC LIBRARY SCIENCE2023

Dual-function engineering to construct ultra-stable anodes for potassium-ion hybrid capacitors: N, O-doped porous carbon spheres

Kangning Zhao, Yanan Chen, Chao Yang, Jie Xu, Xin Peng, Wen Liu, Wei Zhou

Heteroatom doping engineering is deemed to be an adoptable strategy to boost the potassium (K) storage performance of carbonaceous materials. The inevitable issue for this strategy lies in the huge volume expansion originated from the large radius of K+. I ...

Elsevier2022

Micro-addition of Fe in highly alloyed Cu-Ti alloys to improve both formability and strength

Roland Logé, Cyril Cayron, Baptiste Thomas Jean Rouxel

Cu-Be alloys provide excellent electrical and mechanical properties, but present serious health hazards during manufacturing. Among alternative alloys, the Cu-Ti system has the highest yield strength; however, Ti cannot be easily solutionized at concentrat ...

ELSEVIER SCI LTD2022

Low-temperature and rapid photo-annealing process for metal-oxide thin-film transistors using combined excimer deep-ultraviolet and intensely pulsed light irradiation

Jaemin Kim

The fabrication of high-performance metal-oxide-based thin-film transistors (TFTs) on flexible and transparent polymer substrates by solution processes has garnered substantial interest, particularly for manufacturing flex-ible electronics. However, the an ...

ELSEVIER2022

HIERARCHICAL MARKOV CHAIN MONTE CARLO METHODS FOR BAYESIAN INVERSE PROBLEMS

Juan Pablo Madrigal Cianci

This thesis is devoted to the construction, analysis, and implementation of two types of hierarchical Markov Chain Monte Carlo (MCMC) methods for the solution of large-scale Bayesian Inverse Problems (BIP). The first hierarchical method we present is base ...

EPFL2022

Maintenance scheduling of manufacturing systems based on optimal price of the network

Olga Fink

Goods can exhibit positive externalities impacting decisions of customers in social networks. Suppliers can integrate these externalities in their pricing strategies to increase their revenue. Besides optimizing the prize, suppliers also have to consider t ...

2022

Optimization of multi-group energy structures for diffusion analyses of sodium-cooled fast reactors assisted by simulated annealing - Part I: Methodology demonstration

Konstantin Mikityuk, Vincenzo Anthony Di Nora

This study presents an approach to the selection of optimal energy group structures for multi-group nodal diffusion analyses of Sodium-cooled Fast Reactor cores. The goal is to speed up calculations, particularly in transient calculations, while maintainin ...

2021

Generalized parallel tempering on Bayesian inverse problems

Fabio Nobile, Juan Pablo Madrigal Cianci

In the current work we present two generalizations of the Parallel Tempering algorithm in the context of discrete-timeMarkov chainMonteCarlo methods for Bayesian inverse problems. These generalizations use state-dependent swapping rates, inspired by the so ...

2021

Turning PathFinder Upside -Down: 1-4,xploring FPGA Switch -Blocks by Negotiating Switch Presence

Paolo Ienne, Stefan Nikolic

Automated switch-block exploration gains in importance as technology scaling brings more emphasis on the physical constraints, making it insufficient to rely on abstract measures of routability alone. In this work, we take an approach that significantly di ...

IEEE COMPUTER SOC2021

Exploring ferroelectricity in HfO2-based thin films by tackling application-relevant challenges

Matteo Cavalieri

Ferroelectric materials offer a broad range of application-relevant properties, including spontaneous polarization switchable by electric field. Archetypical representatives of this class of materials are perovskites, currently used in applications ranging ...

EPFL2021

Active Subdivision Surfaces for the Semiautomatic Segmentation of Biomedical Volumes

Michaël Unser, Anaïs Laure Marie-Thérèse Badoual

We present a new family of active surfaces for the semiautomatic segmentation of volumetric objects in 3D biomedical images. We represent our deformable model by a subdivision surface encoded by a small set of control points and generated through a geometr ...

2021

Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information

Giuseppe Carleo, Julien Sebastian Gacon, Stefan Woerner

The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution. Computing the full QFIM for a model with d parameters, however, is computat ...

VEREIN FORDERUNG OPEN ACCESS PUBLIZIERENS QUANTENWISSENSCHAF2021

Evaluating a prediction system for snow management

Michael Lehning

The evaluation of snowpack models capable of accounting for snow management in ski resorts is a major step towards acceptance of such models in supporting the daily decision-making process of snow production managers. In the framework of the EU Horizon 202 ...

COPERNICUS GESELLSCHAFT MBH2021

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Anthony Christopher Davison, Hélène Ruffieux, Jörg Hager

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, ...

INST MATHEMATICAL STATISTICS2020

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Sylvain Calinon, Emmanuel Pignat, Hakan Girgin, Noémie Laure Gwendoline Jaquier

Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a great influence on the generalization performances of LfD approaches. In this pa ...

IEEE2020

Stabilization and Performance Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method

Alireza Karimi, Seyed Sohail Madani

Power-Hardware-in-the-Loop (PHIL) setups have gained high importance in validation of the performance of newly developed instruments and devices with low risk and implementation cost. However, the interconnection of a power hardware with a simulated model ...

2022

On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

Nicolas Henri Bernard Flammarion, Scott William Pesme, Aymeric Daphnis Kévin Dieuleveut

Constant step-size Stochastic Gradient Descent exhibits two phases: a transient phase during which iterates make fast progress towards the optimum, followed by a stationary phase during which iterates oscillate around the optimal point. In this paper, we s ...

2020