Dielectronic satellite emission from a solid-density Mg plasma: relationship to models of ionisation potential depression
Physical Review E American Physical Society 109:4 (2024) 045204
Abstract:
We report on experiments where solid-density Mg plasmas are created by heating with the focused output of the Linac Coherent Light Source x-ray free-electron laser. We study the K-shell emission from the helium- and lithium-like ions using Bragg crystal spectroscopy. Observation of the dielectronic satellites in lithium-like ions confirms that the M-shell electrons appear bound for these high charge states. An analysis of the intensity of these satellites indicates that when modeled with an atomic-kinetics code, the ionization potential depression model employed needs to produce depressions for these ions which lie between those predicted by the well known Stewart-Pyatt and Ecker-Kroll models. These results are largely consistent with recent density functional theory calculations.Cosmic-ray confinement in radio bubbles by micromirrors
(2024)
Resonant excitation of plasma waves in a plasma channel
Physical Review Research American Physical Society 6:2 (2024) L022001
Abstract:
We demonstrate resonant excitation of a plasma wave by a train of short laser pulses guided in a preformed plasma channel, for parameters relevant to a plasma-modulated plasma accelerator (P-MoPA). We show experimentally that a train of N≈10 short pulses, of total energy ∼1J, can be guided through 110mm long plasma channels with on-axis densities in the range 1017-1018cm-3. The spectrum of the transmitted train is found to be strongly red shifted when the plasma period is tuned to the intratrain pulse spacing. Numerical simulations are found to be in excellent agreement with the measurements and indicate that the resonantly excited plasma waves have an amplitude in the range 3-10GVm-1, corresponding to an accelerator stage energy gain of order 1GeV.Efficient prediction of attosecond two-colour pulses from an X-ray free-electron laser with machine learning
Scientific Reports Nature Research 14:1 (2024) 7267
Abstract:
X-ray free-electron lasers are sources of coherent, high-intensity X-rays with numerous applications in ultra-fast measurements and dynamic structural imaging. Due to the stochastic nature of the self-amplified spontaneous emission process and the difficulty in controlling injection of electrons, output pulses exhibit significant noise and limited temporal coherence. Standard measurement techniques used for characterizing two-coloured X-ray pulses are challenging, as they are either invasive or diagnostically expensive. In this work, we employ machine learning methods such as neural networks and decision trees to predict the central photon energies of pairs of attosecond fundamental and second harmonic pulses using parameters that are easily recorded at the high-repetition rate of a single shot. Using real experimental data, we apply a detailed feature analysis on the input parameters while optimizing the training time of the machine learning methods. Our predictive models are able to make predictions of central photon energy for one of the pulses without measuring the other pulse, thereby leveraging the use of the spectrometer without having to extend its detection window. We anticipate applications in X-ray spectroscopy using XFELs, such as in time-resolved X-ray absorption and photoemission spectroscopy, where improved measurement of input spectra will lead to better experimental outcomesGeneration of photoionized plasmas in the laboratory of relevance to accretion-powered x-ray sources using keV line radiation
High Energy Density Physics Elsevier 51 (2024) 101097