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Ab initio thermodynamics of liquid and solid water

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Cavity Quantum Electrodynamics with strongly correlated fermions

Kevin Etienne Robert Roux

This thesis presents the first cavity quantum electrodynamics experiments performed with a degenerate gas of

^6

Li with strong atom-atom interactions. The first part of this manuscript describes the design and the building of the apparatus that has been e ...

EPFL2022

Ab initio thermodynamics of liquid and solid water

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Chat with Graph Search

Spectral and thermodynamic properties of interacting electrons with dynamical functionals

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

Experimental and theoretical thermodynamic studies in Ba2MgReO6-the ground state in the context of Jahn-Teller effect

Temperature Dependent Properties of the Aqueous Electron

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Cavity Quantum Electrodynamics with strongly correlated fermions

Toward High-level Machine Learning Potential for Water Based on Quantum Fragmentation and Neural Networks

Uncertainty estimation for molecular dynamics and sampling

On the Application of Small-Scale Turbines in Industrial Steam Networks

Simulating the ghost: quantum dynamics of the solvated electron

Spectral and thermodynamic properties of interacting electrons with dynamical functionals

Experimental and theoretical thermodynamic studies in Ba2MgReO6-the ground state in the context of Jahn-Teller effect

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

Temperature Dependent Properties of the Aqueous Electron

Cavity Quantum Electrodynamics with strongly correlated fermions

On the Application of Small-Scale Turbines in Industrial Steam Networks

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Simulating the ghost: quantum dynamics of the solvated electron

Uncertainty estimation for molecular dynamics and sampling

Toward High-level Machine Learning Potential for Water Based on Quantum Fragmentation and Neural Networks