Towards a New Quantum Frontier in High Energy Density Science
Lead Research Organisation:
University of Oxford
Department Name: Oxford Physics
Abstract
Novel facility developments over the next few years are set to transform our ability to explore matter in extreme conditions of temperature, density and pressure. Advances in high-energy lasers, and their co-location at large-scale free-electron laser facilities, such as the European XFEL in Hamburg, will soon allow us routinely to drive matter to pressures exceeding 10 Mbar, and probe it with the brightest x-ray source on the planet. In the US, the construction of the LCLS- II facility will enable independent x-ray-pump, x-ray-probe experiments to take place for the very first time. These capabilities will support novel laboratory-based studies of matter in stellar interior and exoplanetary core conditions, at the nanoscopic scale, and on ultrashort timescales. Most intriguingly, these advances promise to provide access to exotic plasma regimes where quantum behaviour is transferred to the macroscale, constituting a new quantum frontier in high-energy- density science. Here we propose to develop an experimental program to investigate this frontier. By using time-resolved, resonant inelastic x-ray scattering, we will firstly develop efficient approaches to measuring temperatures and valence electronic structure in laboratory-based planetary astrophysics experiments. We then aim to time-resolve electron localization dynamics in systems at increasingly high densities, where core-electron interactions become important. In this context we will study how such electron interactions help mitigate or inhibit phase transitions, metallic ordering, and support mechanisms driving the creation of complex structures such as electrides at high compression. Finally, we aim to explore whether high-energy-density quantum plasmas are able to support core-chemistry, i.e., hybridization and bonding of inner-electrons, by searching for the presence of transient interatomic bonds in proto-molecular systems, and probing their nuclear dynamics on ultrafast time scales.
Organisations
People |
ORCID iD |
| Sam Vinko (Principal Investigator) | |
| Justin Wark (Co-Investigator) |
Publications
Alaa El-Din KK
(2024)
STEP: extraction of underlying physics with robust machine learning.
in Royal Society open science
Azadi S
(2024)
Nonthermal solid-solid phase transition in ferromagnetic iron
in Physical Review B
Azadi S
(2024)
Quantum Monte Carlo study of the phase diagram of the two-dimensional uniform electron liquid
in Physical Review B
Azadi S
(2023)
Correlation energy of the paramagnetic electron gas at the thermodynamic limit
in Physical Review B
Azadi S
(2023)
Correlation energy of the spin-polarized electron liquid studied using quantum Monte Carlo simulations
in Physical Review B
Crépisson C
(2025)
Shock-driven amorphization and melting in Fe 2 O 3
in Physical Review B
| Description | We have developed an advanced technique to investigate the electronic structures of iron compounds under extreme conditions. The method depends on fielding resonant inelastic x-ray scattering (RIXS) with a novel approach that correlates the measurements of the self-amplified spontaneous emission (SASE) spectrum of an x-ray free-electron laser (XFEL) with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate. This method allows for higher-resolution insights into the behavior of materials subjected to high pressures and temperatures, such as those found in planetary interiors. ? As part of this, we have introduced a machine learning framework designed to solve complex inverse problems in physics. By integrating known physical models into the learning process, this approach enhances the accuracy and robustness of predictions, even when data is noisy. The STEP framework was applied to analyze RIXS spectra, demonstrating its capability to extract meaningful physical information from experimental measurements. ? |
| Exploitation Route | Our tools are already being used with the wider high energy density physics community to access electronic structure information in matter in extreme conditions. |
| Sectors | Aerospace Defence and Marine Digital/Communication/Information Technologies (including Software) Energy |
| Description | Inertial Fusion Energy: Optimising High Energy Density Physics in Complex Geometries |
| Amount | £6,141,929 (GBP) |
| Funding ID | EP/X025373/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 06/2023 |
| End | 06/2028 |
| Title | Supplementary Materials from STEP: Extraction of underlying Physics with robust Machine Learning |
| Description | step_suppl.tex |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | A novel approach to performing deconvolution on data with poor signal-to-noise, of particular use for examining spectroscopic data in high energy density physics. |
| URL | https://rs.figshare.com/articles/dataset/Supplementary_Materials_from_STEP_Extraction_of_underlying_... |