Publications related to Geometry

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Lausanne2024

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Katie Sabrina Catherine Rosie Marsden

In this thesis we will present two results on global existence for nonlinear dispersive equations with data at or below the scaling regularity. In chapter 1 we take a probabilistic perspective to study the energy-critical nonlinear Schrödinger equation in ...

EPFL2024

Gyrokinetic simulations of turbulence in magnetic fusion plasmas using a delta-f PIC scheme with evolving background

Moahan Murugappan

Using the GKEngine code which simulates an electrostatic plasma with adiabatic electron response under a sheared-slab geometry, an attempt at developing a hybrid approach between the delta-f and full-f schemes to describe plasma profiles exhibiting high fl ...

EPFL2024

Next-Generation Modeling of Cancer Using Organoids

Wouter Richard Karthaus, Jillian Rose Love

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be ...

Cold Spring Harbor Lab Press, Publications Dept2024

Novel Alkynylation Methods through the Combination of Hypervalent Iodine Reagents and Alkynyl-trifluoroborate Salts

Julien Aymeric Borrel

The alkyne motif is a versatile functional group often encountered in organic chemistry. It can be involved in various transformations such as the alkyne-azide cycloaddition and has found widespread application in medicinal chemistry, chemical biology and ...

EPFL2024

Weyl metallic state induced by helical magnetic order

Henrik Moodysson Rønnow, Jan Hugo Dil, Ivica Zivkovic, Jian Rui Soh, Xupeng Yang

In the rapidly expanding field of topological materials there is growing interest in systems whose topological electronic band features can be induced or controlled by magnetism. Magnetic Weyl semimetals, which contain linear band crossings near the Fermi ...

Berlin2024

Inter-discharge optimization for fast, reliable access to ASDEX Upgrade advanced tokamak scenario

Olivier Sauter, Federico Alberto Alfredo Felici, Cassandre Ekta Contré, Simon Van Mulders, Hartmut Zohm

Rapid inter-discharge simulation and optimization using the RAPTOR code have allowed the development of a reliable and reproducible early heating strategy for an advanced tokamak (AT) scenario on ASDEX Upgrade. Solving for electron heat and current diffusi ...

Bristol2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Strain-based analysis on the influence of local undercut geometry on fatigue crack initiation life

Alain Nussbaumer, Heikki Tapani Remes, Abinab Niraula

The local undercut defects at the weld toe provide a potential initiation site for fatigue cracks and significantly impact the structure's fatigue strength. The influence of continuous undercut depth on fatigue performance is widely studied, but the resear ...

2024

Holography and localization of information in quantum gravity

Kyriakos Papadodimas, Alexandre Mathieu Frédéric Belin

Within the AdS/CFT correspondence, we identify a class of CFT operators which represent diff-invariant and approximately local observables in the gravitational dual. Provided that the bulk state breaks all asymptotic symmetries, we show that these operator ...

Springer2024

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Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Gyrokinetic simulations of turbulence in magnetic fusion plasmas using a delta-f PIC scheme with evolving background

Next-Generation Modeling of Cancer Using Organoids

Novel Alkynylation Methods through the Combination of Hypervalent Iodine Reagents and Alkynyl-trifluoroborate Salts

Weyl metallic state induced by helical magnetic order

Inter-discharge optimization for fast, reliable access to ASDEX Upgrade advanced tokamak scenario

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Strain-based analysis on the influence of local undercut geometry on fatigue crack initiation life

Holography and localization of information in quantum gravity

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Next-Generation Modeling of Cancer Using Organoids

Gyrokinetic simulations of turbulence in magnetic fusion plasmas using a delta-f PIC scheme with evolving background

Holography and localization of information in quantum gravity

Strain-based analysis on the influence of local undercut geometry on fatigue crack initiation life

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Novel Alkynylation Methods through the Combination of Hypervalent Iodine Reagents and Alkynyl-trifluoroborate Salts

Weyl metallic state induced by helical magnetic order

Inter-discharge optimization for fast, reliable access to ASDEX Upgrade advanced tokamak scenario