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Concept

Ensemble (mathematical physics)

Related publications (29)

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

Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Achille Mauri

We study the statistical mechanics and the equilibrium dynamics of a system of classical Heisenberg spins with frustrated interactions on a d -dimensional simple hypercubic lattice, in the limit of infinite dimensionality d -> infinity . In the analysis we ...

Amer Physical Soc2024

Land Cover Mapping From Multiple Complementary Experts Under Heavy Class Imbalance

Devis Tuia, Valérie Zermatten, Javiera Francisca Castillo Navarro

Deep learning has emerged as a promising avenue for automatic mapping, demonstrating high efficacy in land cover categorization through various semantic segmentation models. Nonetheless, the practical deployment of these models encounters important challen ...

Ieee-Inst Electrical Electronics Engineers Inc2024

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

Landscapes of DNA Mechanics and Genomes

Thomas Antonin Zwahlen

The local physical properties - such as shape and flexibility - of the DNA double-helix is today widely believed to be influenced by nucleic acid sequence in a non-trivial way. Furthermore, there is strong evidence that these properties play a role in many ...

EPFL2023

2023 Roadmap on molecular modelling of electrochemical energy materials

Alfredo Pasquarello, Chunmin Zhang, Assil Bouzid

New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as em ...

Iop Publishing Ltd2023

Many-body physics with strongly interacting fermions coupled to light

Victor Youri Helson

This thesis reports on the realization of the first experiments conducted with superfluid, strongly interacting Fermi gases of 6Li coupled to the light field of an optical cavity. In the scope of existing ultracold atomic platforms, this is the first time ...

EPFL2023

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

cgNA plus web : A Visual Interface to the cgNA plus Sequence-dependent Statistical Mechanics Model of Double-stranded Nucleic Acids

John Maddocks, Rahul Sharma, Alessandro Samuele Patelli, Lennart de Bruin

The sequence-dependent statistical mechanics of double-stranded nucleic acid, or dsNA, is believed to be essential in its biological functions. In turn, the equilibrium statistical mechanics behaviour of dsNA depends strongly both on sequence-dependent per ...

Elsevier2023

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

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

Backtracking Dynamical Cavity Method

Lenka Zdeborová, Freya Behrens, Barbora Hudcová

The cavity method is one of the cornerstones of the statistical physics of disordered systems such as spin glasses and other complex systems. It is able to analytically and asymptotically exactly describe the equilibrium properties of a broad range of mode ...

American Physical Society2023

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

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

Cheng Zhao

We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operat ...

OXFORD UNIV PRESS2023

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

A complete description of thermodynamic stabilities of molecular crystals

Venkat Kapil, Edgar Albert Engel

Predictions of relative stabilities of (competing) molecular crystals are of great technological relevance, most notably for the pharmaceutical industry. However, they present a long-standing challenge for modeling, as often minuscule free energy differenc ...

National Academy of Sciences2022

Unlocking crowding by ensemble statistics

Michael Herzog, David Pascucci, Oh-Hyeon Choung, Yury Markov, Natalia Tiurina

In crowding,1-7 objects that can be easily recognized in isolation appear jumbled when surrounded by other elements.8 Traditionally, crowding is explained by local pooling mechanisms,3,6,9-15 but many findings have shown that the global configuration of th ...

2022

Failure mechanism of fine-grained soil-structure interface for energy piles

Lyesse Laloui, Elena Ravera

The response of the soil-structure interface can significantly affect the performance of any geotechnical structure. Thermal cycles are a new factor that influence the response to all structures that have an energy function in addition to the structural on ...

2022

Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

Nicolas Macris, Jean François Emmanuel Barbier

We consider increasingly complex models of matrix denoising and dictionary learning in the Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank growing linearly with the system size. This is in contrast with most existin ...

AMER PHYSICAL SOC2022

Structure-preserving approaches and data-driven closure modeling for model order reduction

Nicolò Ripamonti

In this thesis, we propose model order reduction techniques for high-dimensional PDEs that preserve structures of the original problems and develop a closure modeling framework leveraging the Mori-Zwanzig formalism and recurrent neural networks. Since high ...

EPFL2022