Nonlinear dynamic analysis of D-alpha signals for type I edge localized modes characterization on JET with a carbon wall

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Since the discovery of dissipative Kerr solitons in optical microresonators, significant progress has been made in the understanding of the underlying physical principles from the fundamental side and generation of broadband coherent optical Kerr frequency ...

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Dynamical flow networks serve as macroscopic models for, e.g., transportation networks, queuing networks, and distribution networks. While the flow dynamics in such networks follow the conservation of mass on the links, the outflow from each link is often ...

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 ...

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

The implementation of three-dimensional magnetic fields, such as the ones of stellarators, in the GBS code (Ricci et al 2012 Plasma Phys. Control. Fusion54 124047; Giacomin et al 2022 J. Comput. Phys.464 111294) is presented, and simulation results are dis ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

The Super-X Divertor (SXD) is an alternative divertor configuration leveraging total flux expansion at the Outer Strike Point (OSP). While the extended 2-Point Model (2PM) predicts facilitated detachment access and control in the SXD configuration, these a ...

Surface roughness is a key factor when it comes to friction and wear, as well as to other physical properties. These phenomena are controlled by mechanisms acting at small scales, in which the topography of apparently flat surfaces is revealed. Roughness i ...

The intrinsic random amplitude and phase modulation of 40 distinct lines of a microresonator frequency comb operated in the modulation instability regime are used to realize massively parallel random-modulation continuous-wave light detection and ranging, ...

Following the conceptual design, the engineering design of the dc magnet and cable-in-conduit conductor (CICC) for the Super-X test facility has been done in 2021. Totally three types of conductors with different structures were designed for the three pair ...

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

. High-resolution simulations of particle-based kinetic plasma models typically require a high number of particles and thus often become computationally intractable. This is exacerbated in multi-query simulations, where the problem depends on a set of para ...

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

We summarize what we consider to be the two main limitations of the "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event" (Schmidli et al. 2022). First, the authors did not give detailed guidance on how to choose an appropriate esti ...

Nonlinear dynamic analysis of D-alpha signals for type I edge localized modes characterization on JET with a carbon wall

Chattez avec Graph Search

Emergent nonlinear dynamics in photonic lattices

Optimizing Dynamic Aperture Studies with Active Learning

The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks

Spectral Estimators for High-Dimensional Matrix Inference

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Random matrix methods for high-dimensional machine learning models

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

Stability: a search for structure

Global fluid simulation of plasma turbulence in stellarators with the GBS code

Exploiting the Signal-Leak Bias in Diffusion Models

Stochastic pairwise preference convergence in Bayesian agents

Parallel flows as a key component to interpret Super-X divertor experiments

Roughness Evolution Induced by Third-Body Wear

Chaotic microcomb-based parallel ranging

Performance of the Cable-in-Conduit Conductors for Super-X Test Facility

Higher-order organization of multivariate time series

Partial Information Sharing Over Social Learning Networks

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

Machine Learning Security in Industry: A Quantitative Survey

We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"