Publications related to Atomic physics

Room-Temperature Quantum Optomechanics and Free-Electron Quantum Optics

Quantum optics studies how photons interact with other forms of matter, the understanding of which was crucial for the development of quantum mechanics as a whole. Starting from the photoelectric effect, the quantum property of light has led to the develop ...

EPFL2024

Photoinduced Second-Order Nonlinearities in Centrosymmetric Media

Ozan Yakar

The interaction of light and matter enables nonlinear frequency conversion and the creation of coherent currents. The optical control of electric currents is of fundamental relevance and prominent research focus in the last decades. These photocurrents ena ...

EPFL2024

Hadronic nature of high-energy emission from the Galactic ridge

Andrii Neronov

We show that the IceCube observation of the Galactic neutrino-flux component confirms the hint of detection of neutrinos from the Galactic ridge (the inner part of the Milky Way disk within the Galactic longitude IlI < 30(degrees)), previously reported by ...

American Physical Society2023

Dilute neutron star matter from neural-network quantum states

Giuseppe Carleo

Low-density neutron matter is characterized by fascinating emergent quantum phenomena, such as the formation of Cooper pairs and the onset of superfluidity. We model this density regime by capitalizing on the expressivity of the hidden-nucleon neural-netwo ...

AMER PHYSICAL SOC2023

Search for Higgs boson pairs decaying to WWWW, WW*ττ, and ττττ in proton-proton collisions at √s=13 TeV

Matthias Finger, Konstantin Androsov, Qian Wang, Jan Steggemann, Anna Mascellani, Yiming Li, Varun Sharma, Xin Chen, Arvind Shah, Rakesh Chawla, Jian Wang, João Miguel das Neves Duarte, Tagir Aushev, Matthias Wolf, Yi Zhang, Lei Zhang, Tian Cheng, Yixing Chen, Werner Lustermann, Andromachi Tsirou, Alexis Kalogeropoulos, Andrea Rizzi, Ioannis Papadopoulos, Paolo Ronchese, Hua Zhang, Leonardo Cristella, Siyuan Wang, Jessica Prisciandaro, Tao Huang, David Vannerom, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Kun Shi, Wei Shi, Guido Andreassi, Abhisek Datta, Jian Zhao, Federica Legger, Gabriele Grosso, Ji Hyun Kim, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Exfoliated 2D Layered and Nonlayered Metal Phosphorous Trichalcogenides Nanosheets as Promising Electrocatalysts for CO2 Reduction

Michael Graetzel, Dan Ren, Hong Zhang, Yelin Hu, Yunfei Jiao, Bing Wu, Chen Shen, Fei Liang

Two-dimensional (2D) materials catalysts provide an atomic-scale view on a fascinating arena for understanding the mechanism of electrocatalytic carbon dioxide reduction (CO2 ECR). Here, we successfully exfoliated both layered and nonlayered ultra-thin met ...

Wiley-VCH Verlag GmbH2023

The role of Zn in C-S-H atomic structure, nucleation and growth

Anna Morales Melgares

The most promising solution towards cementitious materials with a lower carbon footprint is the partial substitution of the clinker by supplementary cementitious materials (SCMs) such as fly ash, blast furnace slag, limestone and calcined clays. The produc ...

EPFL2023

Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties

Michele Ceriotti, Jigyasa Nigam, Michael John Willatt

Symmetry considerations are at the core of the major frameworks used to provide an effective mathematical representation of atomic configurations that is then used in machine-learning models to predict the properties associated with each structure. In most ...

AIP Publishing2022

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

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

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

Beyond potentials: Integrated machine learning models for materials

Michele Ceriotti

Over the past decade, interatomic potentials based on machine learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure calculations, they inherit ...

SPRINGER HEIDELBERG2022

Nuclei with Up to A=6 Nucleons with Artificial Neural Network Wave Functions

Giuseppe Carleo

The ground-breaking works of Weinberg have opened the way to calculations of atomic nuclei that are based on systematically improvable Hamiltonians. Solving the associated many-body Schrodinger equation involves non-trivial difficulties, due to the non-per ...

SPRINGER WIEN2022

Spinor GW /Bethe-Salpeter calculations in BerkeleyGW: Implementation, symmetries, benchmarking, and performance

Oleg Yazyev, Manish Jain

Computing the GW quasiparticle band structure and Bethe-Salpeter equation (BSE) absorption spectra for materials with spin-orbit coupling have commonly been done by treating GW corrections and spin-orbit coupling (SOC) as separate perturbations to density- ...

AMER PHYSICAL SOC2022

Effect of Co-Substitution on Hydrogen Absorption and Desorption Reactions of YMgNi4-Based Alloys

Andreas Züttel, Loris Giovanni Lombardo, Wen Luo, Heena Yang

YMgNi4-based alloys exhibit reversible hydrogen absorption and desorption reactions at near room temperature. Here, we report that Co-substituted YMgNi4-based alloys exhibited higher hydrogen contents and lower hydrogen absorption and desorption reaction p ...

AMER CHEMICAL SOC2022

Nuclear Excitation by Free Muon Capture

Fabrizio Carbone, Ivan Madan, Simone Gargiulo

Efficient excitation of nuclei via exchange of a real or virtual photon has a fundamental importance for nuclear science and technology development. Here, we present a mechanism of nuclear excitation based on the capture of a free muon into the atomic orbi ...

AMER PHYSICAL SOC2022

Dynamical Control of Nuclear Isomer Depletion via Electron Vortex Beams

Fabrizio Carbone, Simone Gargiulo

Some nuclear isomers are known to store a large amount of energy over long periods of time, with a very high energy-to-mass ratio. Here, we describe a protocol to achieve the external control of the isomeric nuclear decay by using electron vortex beams who ...

AMER PHYSICAL SOC2022

Mapping Orbital-Resolved Magnetism in Single Lanthanide Atoms

Harald Brune, Stefano Rusponi, Marina Pivetta, Fabio Donati, Aparajita Singha

Single lanthanide atoms and molecules are promising candidates for atomic data storage and quantum logic due to the long lifetime of their magnetic quantum states. Accessing and controlling these states through electrical transport requires precise knowled ...

AMER CHEMICAL SOC2021

Multi-scale approach for the prediction of atomic scale properties

Michele Ceriotti, Jigyasa Nigam, Andrea Grisafi

Electronic nearsightedness is one of the fundamental principles that governs the behavior of condensed matter and supports its description in terms of local entities such as chemical bonds. Locality also underlies the tremendous success of machine-learning ...

2021

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Hydrodynamic dead zone in multiphase geophysical flows impacting a rigid obstacle

Xingyue Li

When a gravity-driven solid-fluid mixture, such as those in geophysical flows, hits a wall-like rigid obstacle, a metastable jammed zone called hydrodynamic dead zone (HDZ) may emerge. The unjammed-jammed transition of HDZ, controlled by the intricate inte ...

2021

A general and efficient framework for atomistic machine learning

Félix Benedito Clément Musil

Over the last two decades, many technological and scientific discoveries, ranging from the development of materials for energy conversion and storage through the design of new drugs, have been accelerated by the use of preliminary in silico experiments, to ...

EPFL2021