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Concept

Microcanonical ensemble

Related publications (23)

Soliton gas: Theory, numerics, and experiments

Andrey Gelash

The concept of soliton gas was introduced in 1971 by Zakharov as an infinite collection of weakly interacting solitons in the framework of Korteweg-de Vries (KdV) equation. In this theoretical construction of a diluted (rarefied) soliton gas, solitons with ...

Amer Physical Soc2024

Sparse autoregressive neural networks for classical spin systems

Giuseppe Carleo, Dian Wu, Indaco Biazzo

Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Iop Publishing Ltd2024

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Silvestro Micera

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by ...

ELSEVIER SCI LTD2023

Solids that are also liquids: elastic tensors of superionic materials

Nicola Marzari, Tommaso Chiarotti, Giuliana Materzanini

Superionics are fascinating materials displaying both solid- and liquid-like characteristics: as solids, they respond elastically to shear stress; as liquids, they display fast-ion diffusion at normal conditions. In addition to such scientific interest, su ...

NATURE PORTFOLIO2023

Antenna-coupled infrared nanospectroscopy of intramolecular vibrational interaction

Hatice Altug, Aurélian Michel John-Herpin

Many photonic and electronic molecular properties, as well as chemical and biochemical reactivities are controlled by fast intramolecular vibrational energy redistribution (IVR). This fundamental ultrafast process limits coherence time in applications from ...

National Academy of Sciences2023

Comparison of Three Imputation Methods for Groundwater Level Timeseries

Andrea Rinaldo

This study compares three imputation methods applied to the field observations of hydraulic head in subsurface hydrology. Hydrogeological studies that analyze the timeseries of groundwater elevations often face issues with missing data that may mislead bot ...

MDPI2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Ntorina Thanou, Nicola Parolini, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Andrea Kraus, David Kraus

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

High-Throughput Sizing, Counting, and Elemental Analysis of Anisotropic Multimetallic Nanoparticles with Single-Particle Inductively Coupled Plasma Mass Spectrometry

Andreas Züttel, Natalia Gasilova, Wen Luo, Mo Li, Cedric David Koolen

Nanoparticles (NPs) have wide applications in physical and chemical processes, and their individual properties (e.g., shape, size, and composition) and ensemble properties (e.g., distribution and homogeneity) can significantly affect the performance. Howev ...

2022

Multilevel ensemble Kalman filtering for spatio-temporal processes

Fabio Nobile, Hakon Andreas Hoel

We design and analyse the performance of a multilevel ensemble Kalman filter method (MLEnKF) for filtering settings where the underlying state-space model is an infinite-dimensional spatio-temporal process. We consider underlying models that needs to be si ...

Springer2021

Masksembles for Uncertainty Estimation

Pascal Fua, Timur Bagautdinov, Pierre Bruno Baqué, Nikita Durasov

Deep neural networks have amply demonstrated their prowess but estimating the reliability of their predictions remains challenging. Deep Ensembles are widely considered as being one of the best methods for generating uncertainty estimates but are very expe ...

2021

Uncertainty estimation for molecular dynamics and sampling

Michele Ceriotti, Kevin Rossi, Venkat Kapil, Federico Grasselli, Giulio Imbalzano, Edgar Albert Engel, Yongbin Zhuang

Machine-learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale, and complexity. Given the interpolative nature of these models, the r ...

2021

Architecture, environnement et artefact total : la ville selon Reyner Banham et Oswald Mathias Ungers

Thibaut Jean Bernard Pierron

When looking at the city and the land, current architectural practices face a double limitation. On the one hand, the discipline is asked to react to its own specter: the body of authoritarian spatial devices based on a questionable tradition of which the ...

EPFL2021

New Methods for the Integrative Dynamic Modeling of Biomolecular Structures

Sylvain Träger

The true understanding of most cellular functions is only really achievable through the structural determination of their underlying macromolecular assemblies. However, their size, large number of individual components and metastable states make their eluc ...

EPFL2021

Charge fluctuations from molecular simulations in the constant-potential ensemble

Sara Bonella, Alessandro Coretti

We revisit the statistical mechanics of charge fluctuations in capacitors. In constant-potential classical molecular simulations, the atomic charges of electrode atoms are treated as additional degrees of freedom which evolve in time so as to satisfy the c ...

2020

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

Michele Ceriotti, Piero Gasparotto

A central paradigm of self-assembly is to create ordered structures starting from molecular monomers that spontaneously recognize and interact with each other via noncovalent interactions. In recent years, great efforts have been directed toward perfecting ...

AMER CHEMICAL SOC2020

Data assimilation of in situ and satellite remote sensing data to 3D hydrodynamic lake models: a case study using Delft3D-FLOW v4.03 and OpenDA v2.4

Alfred Johny Wüest, Damien Bouffard, Theo Baracchini

The understanding of physical dynamics is crucial to provide scientifically credible information on lake ecosystem management. We show how the combination of in situ observations, remote sensing data, and three-dimensional hydrodynamic (3D) numerical simul ...

2020

Physics of optically driven nanojunctions

Philippe Andreas Rölli

Recent years have seen spectacular developments in the domain of nano-optics. Alongside the well-known techniques of super-resolution microscopy progress in nanofabrication has enabled important improvements in the fields of optical imaging and spectros ...

EPFL2020

Local Vulnerabilities and Global Robustness of Coupled Dynamical Systems on Complex Networks

Melvyn Sandy Tyloo

Coupled dynamical systems are omnipresent in everyday life. In general, interactions between individual elements composing the system are captured by complex networks. The latter greatly impact the way coupled systems are functioning and evolving in time. ...

EPFL2020

Exploiting the chirality of intermetallic PdGa

Samuel Thomas Stolz

The intermetallic compound PdGa has recently attracted considerable interest for combining high catalytic activity with high reaction selectivity in symmetric heterogeneous catalysis, in particular semi-hydrogenation of acetylene and methanol steam reformi ...

EPFL2020

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Mahsa Shoaran, Bingzhao Zhu

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020