Investigating mechanisms of state localization in highly ionized dense plasmas

Producción CientíficaWe present experimental observations of Kβ emission from highly charged Mg ions at solid density, driven by intense x rays from a free electron laser. The presence of Kβ emission indicates the n=3 atomic shell is relocalized for high charge states, providing an upper constraint on the depression of the ionization potential. We explore the process of state relocalization in dense plasmas from first principles using finite-temperature density functional theory alongside a wave-function localization metric, and find excellent agreement with experimental results.This work has been supported by the Spanish Ministry of Science and Innovation under Research Grant No. PID2019-108764RB-I0

Investigating Mechanisms of State Localization in Highly-Ionized Dense Plasmas

We present the first experimental observation of K$_{\beta}$ emission from highly charged Mg ions at solid density, driven by intense x-rays from a free electron laser. The presence of K$_{\beta}$ emission indicates the $n=3$ atomic shell is relocalized for high charge states, providing an upper constraint on the depression of the ionization potential. We explore the process of state relocalization in dense plasmas from first principles using finite-temperature density functional theory alongside a wavefunction localization metric, and find excellent agreement with experimental results.Comment: 22 pages, 13 figure

A quantum-inspired approach to exploit turbulence structures

Understanding turbulence is key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multiscale nature, describing the coupling between different-sized eddies in space and time. Here we analyze the structure of turbulent flows by quantifying correlations between different length scales using methods inspired from quantum many-body physics. We present the results for interscale correlations of two paradigmatic flow examples, and use these insights along with tensor network theory to design a structure-resolving algorithm for simulating turbulent flows. With this algorithm, we find that the incompressible Navier–Stokes equations can be accurately solved even when reducing the number of parameters required to represent the velocity field by more than one order of magnitude compared to direct numerical simulation. Our quantum-inspired approach provides a pathway towards conducting computational fluid dynamics on quantum computers.</p

Non-thermal evolution of dense plasmas driven by intense x-ray fields

The advent of x-ray free-electron lasers has enabled a range of new experimental investigations into the properties of matter driven to extreme conditions via intense x-ray-matter interactions. The femtosecond timescales of these interactions lead to the creation of transient high-energy-density plasmas, where both the electrons and the ions may be far from local thermodynamic equilibrium. Predictive modelling of such systems remains challenging because of the different timescales at which electrons and ions thermalize, and because of the vast number of atomic configurations required to describe highly-ionized plasmas. Here we present CCFLY, a code designed to model the time-dependent evolution of both electron distributions and ion states interacting with intense x-ray fields on ultra-short timescales, far from local thermodynamic equilibrium. We explore how the plasma relaxes to local thermodynamic equilibrium on femtosecond timescales in terms of the charge state distribution, electron density, and temperature

A quantum-inspired approach to exploit turbulence structures

Understanding turbulence is the key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multi-scale nature, describing the coupling between different-sized eddies in space and time. Here we introduce a new paradigm for analyzing the structure of turbulent flows by quantifying correlations between different length scales using methods inspired from quantum many-body physics. We present results for interscale correlations of two paradigmatic flow examples, and use these insights along with tensor network theory to design a structure-resolving algorithm for simulating turbulent flows. With this algorithm, we find that the incompressible Navier-Stokes equations can be accurately solved within a computational space reduced by over an order of magnitude compared to direct numerical simulation. Our quantum-inspired approach provides a pathway towards conducting computational fluid dynamics on quantum computers.Comment: Newest and final version of our articl