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Angular analysis and differential branching fraction of the decay B-s(0) -> phi mu(+)mu(-)

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Publications associées (37)

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Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

Nikolay Bykovskiy

Numerous conductor designs for pulsed magnets based on High Temperature Superconductors (HTS), featuring stacks of tapes are currently being proposed. A major contribution to the AC losses is expected to be given by hysteresis losses. Several numerical mod ...

IEEE Institute of Electrical and Electronics Engineers2024

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Ian Smith, Katrin Beyer, Bryan German Pantoja Rosero, Mathias Christian Haindl Carvallo

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Springer2024

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Michael Lehning, Dylan Stewart Reynolds, Michael Haugeneder

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, ...

Frontiers Media Sa2024

Chiral Anomaly and Dynamos from Inhomogeneous Chemical Potential Fluctuations

Salim Bennouna

In the standard model of particle physics, the chiral anomaly can occur in relativistic plasmas and plays a role in the early Universe, protoneutron stars, heavy-ion collisions, and quantum materials. It gives rise to a magnetic instability if the number d ...

Amer Physical Soc2024

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

Katrin Beyer, Igor Tomic

Masonry aggregates, which emerged as layouts of cities and villages became denser, make up historical centres all over the world. In these aggregates, neighbouring structures may share structural walls that are joined at the interfaces by mortar or interlo ...

Springer2024

Measurements of azimuthal anisotropy of nonprompt D0 mesons in PbPb collisions at √sNN=5.02 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

Measurements of the elliptic (v(2)) and triangular (v(3)) azimuthal anisotropy coefficients are presented for D-0 mesons produced in b hadron decays (nonprompt D-0 mesons) in lead-lead collisions at root s(NN) = 5.02 TeV. The results are compared with prev ...

Elsevier2024

Search for Scalar Leptoquarks Produced via τ-Lepton-Quark Scattering in pp Collisions at ffiffi s p=13 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Junqiu Liu, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

The first search for scalar leptoquarks produced in z-lepton-quark collisions is presented. It is based on a set of proton-proton collision data recorded with the CMS detector at the LHC at a center-of-mass energy of 13 TeV corresponding to an integrated l ...

Amer Physical Soc2024

Sterile neutrinos as dark matter

Mikhail Chapochnikov

I describe the sterile neutrino dark matter candidate and discuss how it may fit into the overall picture of physics beyond the Standard Model. ...

Elsevier2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Future Changes in Dynamics of Extreme Precipitation and Dry Periods in the Swiss Alps and Consequences for Hydropower Production

Tatjana Milojevic

Global climate warming is leading to more frequent and severe extreme weather events, with alpine regions like the European Alps being particularly vulnerable. This thesis explores future changes in extreme weather dynamics in the southeastern Swiss Alps a ...

EPFL2024

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Nathan Russell Powell, Mert Eyuboglu

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Paolo De Los Rios, Bruno Claude Daniel Fauvet, Adélaïde Alice Mohr, Mathieu Rebeaud, Satyam Tiwari

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Elsevier Science Inc2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

EPFL Infoscience2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Study of b-hadron decays to Λc+h−h′− final states

Olivier Schneider, Aurelio Bay, Guido Haefeli, Tatsuya Nakada, Frédéric Blanc, Lesya Shchutska, Elena Graverini, Sebastian Schulte, Donal Patrick Hill, Marie Theres Christin Bachmayer, Serhii Cholak, Ettore Zaffaroni, Aravindhan Venkateswaran, Luis Miguel Garcia Martin, Vitalii Lisovskyi, Elisabeth Maria Niel, Federico Ronchetti, Radoslav Marchevski, Anni Matilda Kauniskangas, Dimitrios Kaminaris, Raphaël van Laak, Pierre Paul Louis Mayencourt, Brianna Leililani Thielen, Arnaud Merlin Gauthey, Gianluca Zunica, Abdul-Kerim Guseinov, Esteban Curras Rivera, Yifei Song, Roberto Ribatti, Alexandre Brea Rodriguez, Rita De Sousa Ataíde Da Silva

Decays of Ξb− and Ωb− baryons to Λc+h−h′− final states, with h−h′− being π−π−, K−π− and K−K− meson pairs, are searched for using data collected with the LHCb detector. The data sample studied corresponds to an integrated luminosity of 8.7 fb−1 of pp collis ...

Springer Nature2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024