Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–7 of 7 results
Advanced filters: Author: Brendan Kettle Clear advanced filters
  • Radiation reaction (RR) on particles in strong fields is the subject of intense experimental research, but previous efforts lacked statistical significance due to the extreme regimes required. Here, the authors report a 5σ observation of RR and obtain strong, quantitative evidence favouring quantum models over classical, using an all-optical setup where electrons are accelerated by a laser in a gas jet before colliding with a second, intense pulse.

    • Eva E. Los
    • Elias Gerstmayr
    • Stuart P. D. Mangles
    ResearchOpen Access
    Nature Communications
    P: 1-11
  • The authors demonstrate dual-probe multi-messenger imaging of high-energy-density plasmas based on laser-wakefield-accelerated electrons. This enables spatiotemporally resolved simultaneous probing of plasma hydrodynamics and electromagnetic field evolution with both x-ray and electron beams.

    • Mario D. Balcazar
    • Hai-En Tsai
    • Carolyn C. Kuranz
    ResearchOpen Access
    Nature Communications
    Volume: 17, P: 1-14
  • Laser-driven X-rays can provide ultrashort pulses of broadband light, well suited for femtosecond timescale absorption spectroscopy. Here the authors measure the extended X-ray absorption features of a copper sample using a laser wakefield accelerator, in a single shot; important for studying samples driven to extreme and non-equilibrium states.

    • Brendan Kettle
    • Cary Colgan
    • Stuart P. D. Mangles
    ResearchOpen Access
    Communications Physics
    Volume: 7, P: 1-7
  • This Perspective discusses how high-energy-density physics could tap the potential of AI-inspired algorithms for extracting relevant information and how data-driven automatic control routines may be used for optimizing high-repetition-rate experiments.

    • Peter W. Hatfield
    • Jim A. Gaffney
    • Ben Williams
    Reviews
    Nature
    Volume: 593, P: 351-361