Publications associées à Impact of dispersion forces on the atomic structure of a prototypical network-forming disordered system: The case of liquid GeSe2

A Cavity-Microscope for Quantum Simulations with Locally-Controllable All-to-All Interactions

This thesis presents the development, construction, and benchmark of an experimental platform that combines cold fermionic 6Li atoms with locally controllable light-matter interactions. To enable local control, a new device, the cavity-microscope, was crea ...

EPFL2024

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

Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

IEEE2023

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Kynthia Chamilothori, Bahar Aydemir, Caroline Karmann, Seungryong Kim

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

Atomic-level structure determination of amorphous molecular solids by NMR

Manuel Cordova, Arthur César Pinon, David Lyndon Emsley, Pinelopi Moutzouri

Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder ...

Nature Portfolio2023

Deep excavation of the impact from endogenous and exogenous uncertainties on long-term energy planning

François Maréchal, Xiang Li

Endogenous and exogenous uncertainties exert significant influences on energy planning. In this study, we propose a systematic methodology to excavate the uncertainty space, by combining mix-integer linear programming (MILP), Monte Carlo simulation, and ma ...

ELSEVIER2023

A New Analytical Approximation of the Fluid Antenna System Channel

Malek Khammassi

Fluid antenna systems (FAS) are an emerging technology that promises a significant diversity gain even in the smallest spaces. It consists of a freely moving antenna in a small linear space to pick up the strongest received signal. Previous works in the li ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Energy geotechnology: A new era for geotechnical engineering practice

Lyesse Laloui, Melis Sütman

Energy geotechnology provides low carbon, cost-effective and local energy solu-tions to structures and infrastructures, which opens a new era for the geotechnical engineering practice, by extending the conventional role of structural design to the ...

CRC Press2023

Metal-Free Molecular Catalysts for the Oxygen Reduction Reaction: Electron Affinity as an Activity Descriptor

Ganna Gryn'ova, Juliette Veronique Schleicher

Heteroatom-doped polyaromatic hydrocarbons (or nanographenes) are promising molecular electrocatalysts for the oxygen reduction reaction (ORR). Here, we use density functional theory to investigate the first step of the ORR pathway (chemisorption) for a se ...

AMER CHEMICAL SOC2023

Unified theory of atom-centered representations and message-passing machine-learning schemes

Michele Ceriotti, Jigyasa Nigam, Guillaume André Jean Fraux, Sergey Pozdnyakov

Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents. Many types of models rely on descriptions of atom-cen ...

AIP Publishing2022

Two-dimensional Hubbard model at finite temperature: Weak, strong, and long correlation regimes

Riccardo Rossi

We investigate the momentum-resolved spin and charge susceptibilities, as well as the chemical potential and double occupancy in the two-dimensional Hubbard model as functions of doping, temperature, and interaction strength. Through these quantities, we i ...

AMER PHYSICAL SOC2022

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

Patrick Karl Alois Neff

BackgroundTinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a be ...

FRONTIERS MEDIA SA2022

Analysis of barrette foundations subjected to mechanical and thermal loads

Lyesse Laloui, Alessandro Francesco Rotta Loria

In recent years, there has been increasing interest in the use of rectangular barrette foundations for the structural support and energy supply of tall buildings when circular piles become inefficient or uneconomical. In such applications, so-called energy ...

2022

A Correlation-Based Electromagnetic Time Reversal Technique to Locate Indoor Transient Radiation Sources

Farhad Rachidi-Haeri, Marcos Rubinstein, Zhaoyang Wang, Qi Li

To overcome the multipath interference in locating transient electromagnetic (EM) radiation sources in an indoor environment, we propose a criterion that calculates the correlation between back-propagated signals from observation points, to be used in EM t ...

Institute of Electrical and Electronics Engineers2021

Source noise suppression in attosecond transient absorption spectroscopy by edge-pixel referencing

Hugo Jean Baptiste Marroux

Attosecond transient absorption spectroscopy (ATAS) is used to observe photoexcited dynamics with outstanding time resolution. The main experimental challenge of this technique is that high-harmonic generation sources show significant instabilities, result ...

2021

Towards Quantum 3D Imaging Devices

Claudio Bruschini, Edoardo Charbon, Samuel Burri, Arin Can Ülkü, Paul Mos, Michael Alan Wayne

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum–position entanglement and photon–number correlations to provide the typical refocusin ...

2021

Luminescent, porous, metal-organic crystals: Design, synthesis, and applications

Fatmah Ebrahim

The work presented in this thesis is focused on the design and discovery of new luminescent, porous, crystalline materials for targeted applications. In particular, we focus on luminescent Metal-Organic Frameworks (MOFs) and Organic Molecules of Intrinsic ...

EPFL2020

Towards the Validation of Noise Experiments in the CROCUS Reactor Using the TRIPOLI-4 Monte Carlo Code in Analog Mode

Andreas Pautz, Oskari Ville Pakari, Vincent Pierre Lamirand

Intrinsic neutron noise experiments offer a non-invasive manner to measure the prompt decay constant or reactivity of fissile systems. Using the fluctuations in the density of fission chains, one can infer the kinetics parameters via correlation analysis s ...

2021

Incompleteness of Atomic Structure Representations

Michele Ceriotti, Michael John Willatt, Sergey Pozdnyakov

Many-body descriptors are widely used to represent atomic environments in the construction of machine-learned interatomic potentials and more broadly for fitting, classification, and embedding tasks on atomic structures. There is a widespread belief in the ...

AMER PHYSICAL SOC2020

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Michele Ceriotti, Michael John Willatt

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear fun ...

Springer International Publishing2020