Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Canonical ensemble

Related publications (30)

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

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

Evaluation of Photocatalysts for Water Splitting through Combined Analysis of Surface Coverage and Energy-Level Alignment

Alfredo Pasquarello, Francesco Ambrosio, Zhendong Guo

To examine whether suitable conditions occur for the water splitting reaction at their interfaces with liquid water, we determine the pH-dependent surface coverage for a series of semiconductors, including GaAs, GaP, GaN, CdS, ZnO, SnO2, and rutile and ana ...

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

Corrections to “Experimental Details of a Steep-Slope Ferroelectric InGaAs Tunnel-FET With High-Quality PZT and Modeling Insights in the Transient Polarization”

Mihai Adrian Ionescu, Igor Stolichnov, Ali Saeidi

This correspondence highlights that the Gibbs free energy description of a ferroelectric capacitor in series with a paraelectric capacitor, depends on the initial charge on the plates of the ferroelectric capacitor. An incomplete Gibbs free energy descript ...

2020

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

Volumetric Transformer Networks

Sabine Süsstrunk, Mathieu Salzmann, Seungryong Kim

Existing techniques to encode spatial invariance within deep convolutional neural networks (CNNs) apply the same warping field to all the feature channels. This does not account for the fact that the individual feature channels can represent different sema ...

2020

Automatic 12-lead ECG Classification Using a Convolutional Network Ensemble

Manoel Horta Ribeiro

The 12-lead electrocardiogram (ECG) is a major diagnostic test for cardiovascular diseases and enhanced automated analysis tools might lead to more reliable diagnosis and improved clinical practice. Deep neural networks are models composed of stacked trans ...

IEEE2020