Publications associées à Température négative

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

EPFL2024

Molecular intercalation in the van der Waals antiferromagnets FePS3 and NiPS3

Bruce Normand, Ying Chen, Sheng Xu, Shuo Li, Xiaoyu Xu, Zeyu Wang, Weiqiang Yu

We have performed electrochemical treatment of the van der Waals antiferromagnetic materials FePS3 and NiPS3 with the ionic liquid EMIM-BF4, achieving significant molecular intercalation. Mass analysis of the intercalated compounds, EMIMx-FePS3 and EMIMx-N ...

Amer Physical Soc2024

Local vs. cooperative: Unraveling glass transition mechanisms with SEER

Matthieu Wyart, Wencheng Ji

Which phenomenon slows down the dynamics in supercooled liquids and turns them into glasses is a long-standing question of condensed matter. Most popular theories posit that as the temperature decreases, many events must occur in a coordinated fashion on a ...

National Academy of Sciences2024

Magneto-Thermoelectric Transport in Graphene Quantum Dot with Strong Correlations

Oleksandr Kriuchkov

Disorder at etched edges of graphene quantum dots (GQD) enables random all-to-all interactions between localized charges in partially filled Landau levels, providing a potential platform to realize the Sachdev-Ye-Kitaev (SYK) model. We use quantum Hall edg ...

2024

Field-controlled multicritical behavior and emergent universality in fully frustrated quantum magnets

Bruce Normand

Phase transitions in condensed matter are a source of exotic emergent properties. We study the fully frustrated bilayer Heisenberg antiferromagnet to demonstrate that an applied magnetic field creates a previously unknown emergent criticality. The quantum ...

Nature Portfolio2024

Tracking deep-level defects in degrading perovskite solar cells with a multifactorial approach

Vivek Subramanian

In this work, we provide a mechanistic understanding of the degradation of perovskite solar cells in operation by focusing on methylammonium lead triiodide (CH3NH3PbI3 or MAPbI3) and tracking the evolution of electronic defects via photo-induced current tr ...

Elsevier2024

Experiments and gyrokinetic simulations of TCV plasmas with negative triangularity in view of DTT operations

Olivier Sauter, Stefano Coda, Justin Richard Ball, Alberto Mariani, Matteo Vallar, Filippo Bagnato

Negative triangularity (NT) scenarios in TCV have been compared to positive triangularity (PT) scenarios using the same plasma shapes foreseen for divertor tokamak test tokamak operations. The experiments provided a NT/PT L-mode pair and a PT H-mode with d ...

Iop Publishing Ltd2024

Correlation properties of a one-dimensional repulsive Bose gas at finite temperature

Riccardo Rota

We present a comprehensive study shedding light on how thermal fluctuations affect correlations in a Bose gas with contact repulsive interactions in one spatial dimension. The pair correlation function, the static structure factor, and the one-body density ...

IOP Publishing Ltd2023

Modelling of metal alloys in realistic conditions with machine learning

Nataliya Lopanitsyna

Computer simulations based on statistical methods have emerged as a powerful tool for studying structure-property relationships at the atomistic level. However, to provide reliable insights into materials in realistic conditions, it is essential to accurat ...

EPFL2023

Thermal conductivity of glasses: first-principles theory and applications

Nicola Marzari, Michele Simoncelli

Predicting the thermal conductivity of glasses from first principles has hitherto been a very complex problem. The established Allen-Feldman and Green-Kubo approaches employ approximations with limited validity-the former neglects anharmonicity, the latter ...

NATURE PORTFOLIO2023

Experimental study of stability, quench propagation and detection methods on 15 kA sub-scale HTS fusion conductors in SULTAN

Pierluigi Bruzzone, Kamil Sedlák, Nikolay Bykovskiy, Ortensia Dicuonzo

High-temperature superconductors (HTSs) enable exclusive operating conditions for fusion magnets, boosting their performance up to 20 T generated magnetic fields in the temperature range from 4 K to 20 K. One of the main technological issues of HTS conduct ...

2023

On double-descent in uncertainty quantification in overparametrized models

Florent Gérard Krzakala, Lenka Zdeborová, Lucas Andry Clarte, Bruno Loureiro, Bruno Loureiro

Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ra ...

PMLR Proceedings of Machine Learning Research2023

Scaling Description of Dynamical Heterogeneity and Avalanches of Relaxation in Glass-Forming Liquids

Matthieu Wyart, Ali Tahaei

We provide a theoretical description of dynamical heterogeneities in glass-forming liquids, based on the premise that relaxation occurs via local rearrangements coupled by elasticity. In our framework, the growth of the dynamical correlation length e and o ...

American Physical Society2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

REMOTE: Re-thinking Task Mapping on Wireless 2.5D Systems-on-Package for Hotspot Removal

David Atienza Alonso, Marina Zapater Sancho, Giovanni Ansaloni, Darong Huang, Rafael Medina Morillas

2.5D Systems-on-Package (SoPs) are composed by several chiplets placed on an interposer. They are becoming increasingly popular as they enable easy integration of electronic components in the same package and high fabrication yields. Nevertheless, they int ...

2023

Low-temperature processing of screen-printed piezoelectric KNbO3 with integration onto biodegradable paper substrates

Danick Briand, Luis Guillermo Villanueva Torrijo, Morgan Mc Kay Monroe

The development of fully solution-processed, biodegradable piezoelectrics is a critical step in the development of green electronics towards the worldwide reduction of harmful electronic waste. However, recent printing processes for piezoelectrics are hind ...

2023

Motor-Unit Ordering of Blindly-Separated Surface-EMG Signals for Gesture Recognition

Pasquale Davide Schiavone, Elisa Donati

Hand gestures are one of the most natural and expressive way for humans to convey information, and thus hand gesture recognition has become a research hotspot in the human-machine interface (HMI) field. In particular, biological signals such as surface ele ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Uncertainty analysis of polymer-based capacitive relative humidity sensor at negative temperatures and low humidity levels

Sandro Carrara, Andromachi Tsirou, Amar Kapic

Capacitive relative humidity sensors, widely used in industrial and environmental applications, should be interchangeable and ideally have parametrizable response to relative humidity changes. While the effects of temperatures in the range between 0 degree ...

ELSEVIER SCI LTD2023

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

Silvestro Micera, Michael Lassi

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

Expectation consistency for calibration of neural networks

Florent Gérard Krzakala, Lenka Zdeborová, Lucas Andry Clarte, Bruno Loureiro, Bruno Loureiro

Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient calibration methods for neural networks is therefore an important endeavour tow ...

2023