Publications related to Triangular matrix

Experiments and gyrokinetic simulations of TCV plasmas with negative triangularity in view of DTT operations

Olivier Sauter, Stefano Coda, Justin Richard Ball, Alberto Mariani, Matteo Vallar, Filippo Bagnato

Negative triangularity (NT) scenarios in TCV have been compared to positive triangularity (PT) scenarios using the same plasma shapes foreseen for divertor tokamak test tokamak operations. The experiments provided a NT/PT L-mode pair and a PT H-mode with d ...

Iop Publishing Ltd2024

Validation of short-pulse reflectometry turbulence measurements with a synthetic diagnostic

Stefano Coda, Stephan Brunner, Oleg Krutkin, Umesh Kumar, Mackenzie Peter-Fulford Van Rossem, Samuele Mazzi

Experimental measurements of the turbulence amplitude utilizing a short pulse reflectometry method are presented. Two discharges with shaped plasma possessing opposite signs of triangularity are considered and a higher turbulence amplitude is found in the ...

IOP Publishing Ltd2024

Physical insights from the aspect ratio dependence of turbulence in negative triangularity plasmas

Stefano Coda, Justin Richard Ball

In this work, we study the impact of aspect ratio A = R 0 / r (the ratio of major radius R 0 to minor radius r) on the confinement benefits of negative triangularity (NT) plasma shaping. We use high-fidelity flux tube gyrokinetic GENE simulations and consi ...

Iop Publishing Ltd2024

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Daniel Kressner, Alice Cortinovis

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

Siam Publications2024

First-principle based predictions of the effects of negative triangularity on DTT scenarios

Olivier Sauter, Gabriele Merlo, Alberto Mariani

Plasmas with negative triangularity (NT) shape have been recently shown to be able to achieve H-mode levels of confinement in L-mode, avoiding detrimental edge localised modes. Therefore, this plasma geometry is now studied as a possible viable option for ...

IOP Publishing Ltd2024

Study of impurity C transport and plasma rotation in negative triangularity on the TCV tokamak

Olivier Sauter, Basil Duval, Stefano Coda, Benoît Labit, Alessandro Pau, Laurie Porte, Alexander Karpushov, Antoine Pierre Emmanuel Alexis Merle, Justin Richard Ball, Dmytry Mykytchuk, Filippo Bagnato

Carbon impurity transport is studied in the TCV tokamak using a charge exchange recombination diagnostic. TCVs flexible shaping capabilities were exploited to extend previous impurity transport studies to negative triangularity (delta < 0). A practical way ...

Iop Publishing Ltd2024

NBI optimization on SMART and implications for scenario development

Mario Ludovico Podesta, Francesca Maria Poli

The SMall Aspect Ratio Tokamak (SMART) under commissioning at the University of Seville, Spain, aims to explore confinement properties and possible advantages in confinement for compact/spherical tokamaks operating at negative vs. positive triangularity. T ...

Iop Publishing Ltd2024

Effect of triangularity on plasma turbulence and the SOL-width scaling in L-mode diverted tokamak configurations

Paolo Ricci, Louis Nicolas Stenger, Davide Mancini, Maurizio Giacomin

The effect of triangularity on tokamak boundary plasma turbulence is investigated using global, flux-driven, three-dimensional, two-fluid simulations. The simulations show that negative triangularity (NT) stabilizes boundary plasma turbulence, and linear i ...

IOP Publishing Ltd2023

Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

Ali H. Sayed, Michele Cirillo

This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

3D Characterisation of Turbulent Plasma Filaments Using Gas Puff Imaging in the Tokamak à Configuration Variable

Nicola Offeddu

A key challenge for the development of fusion reactors based on magnetic confinement, such as tokamaks and stellarators, is the control of the turbulent processes. The most prominent feature of turbulence in the Scrape-Off Layer (SOL), the volume between t ...

EPFL2023

An experimental and computational study of tokamak plasma turbulence

Aylwin Iantchenko

Turbulence driven by small-scale instabilities results in strong heat and particle transport, which significantly shortens the confinement time and prevents the formation of a self-sustained plasma reaction in magnetic confinement devices. Control and poss ...

EPFL2023

Modelling of sawtooth-induced fast ion transport in positive and negative triangularity in TCV

Olivier Sauter, Basil Duval, Alexander Karpushov, Duccio Testa, Mario Ludovico Podesta, Antoine Pierre Emmanuel Alexis Merle, Marcelo Baquero Ruiz, Dmytry Mykytchuk, Matteo Vallar, Lorenzo Stipani

Internal kinks are a common magneto hydro-dynamic (MHD) instability observed in tokamak operation when the q profile in the plasma core is close to unity. This MHD instability impacts both the transport of the bulk plasma (current, particle and energy tran ...

IOP Publishing Ltd2022

Iterative refinement of Schur decompositions

Daniel Kressner, Zvonimir Bujanovic

The Schur decomposition of a square matrix A is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following task: Compute a (m ...

SPRINGER2023

Enhanced confinement in diverted negative-triangularity L-mode plasmas in TCV

Olivier Sauter, Stefano Coda, Benoît Labit, Laurie Porte, Alessandro Pau, Alessandro Marinoni, Antoine Pierre Emmanuel Alexis Merle, Umar Sheikh, Cedric Kar-Wai Tsui, Matteo Vallar, Filippo Bagnato, Leonardo Pigatto

The favorable confinement properties of negative-triangularity (NT) tokamak configurations were discovered in the TCV tokamak in the late 1990s and were documented over the two following decades, through investigations of predominantly electron-heated plas ...

2022

Matrix product states with backflow correlations

Giuseppe Carleo

By taking inspiration from the backflow transformation for correlated systems, we introduce a tensor network Ansatz which extends the well-established matrix product state representation of a quantum many-body wave function. This structure provides enough ...

AMER PHYSICAL SOC2022

IMPROVED VARIANTS OF THE HUTCH plus plus ALGORITHM FOR TRACE ESTIMATION

Daniel Kressner, Ulf David Persson, Alice Cortinovis

This paper is concerned with two improved variants of the Hutch++ algorithm for estimating the trace of a square matrix, implicitly given through matrix-vector products. Hutch++ combines randomized low-rank approximation in a first phase with stochastic tr ...

SIAM PUBLICATIONS2022

Study of impurity ion transport using charge exchange spectroscopy on TCV

Filippo Bagnato

The study of impurity transport in fusion plasmas has gained interest over the years due to its implication with tokamak performances. In TCV (Tokamak à Configuration Variable), as in many other facilities, impurity ions can be studied through the CXRS (Ch ...

EPFL2022

Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima’s Replica Formula)

Florent Gérard Krzakala, Alia Abbara

There has been a recent surge of interest in the study of asymptotic reconstruction performance in various cases of generalized linear estimation problems in the teacher-student setting, especially for the case of i.i.d standard normal matrices. Here, we g ...

2022

Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

Nicolas Macris, Jean François Emmanuel Barbier

We consider increasingly complex models of matrix denoising and dictionary learning in the Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank growing linearly with the system size. This is in contrast with most existin ...

AMER PHYSICAL SOC2022

Magnetic control of tokamak plasmas through deep reinforcement learning

Ambrogio Fasoli, Olivier Sauter, Basil Duval, Stefano Coda, Jean-Marc Moret, Federico Alberto Alfredo Felici, Cristian Sommariva, Antoine Pierre Emmanuel Alexis Merle, Cristian Galperti, Francesco Carpanese, Jonas Buchli, Federico Pesamosca, Brendan Tracey, Jonas Degrave

Nuclear fusion using magnetic confinement, in particular in the tokamak configuration, is a promising path towards sustainable energy. A core challenge is to shape and maintain a high-temperature plasma within the tokamak vessel. This requires high-dimensi ...

2022