Engineering topics
Publications and source records attributed to Mariscal, Derek.
Complete, accurate, and reliable short-pulse laser characterization and monitoring is a necessary tool to ensure that we are delivering the laser pulse shape required to optimize the target physics for ion- or electron-driven fast ignition (FI).
Here, we report on the first indirect-drive implosions driven by a dual conical frustum-shaped hohlraum denoted “frustraum” and the experimental tuning campaigns leading up to two layered implosions. The campaign used 1.2 and 1.4 mm inner radius high density carbon (HDC) capsules and represented the largest HDC capsules to be imploded on the National Ignition Facility via indirect drive. Several techniques were successfully implemented to control the Legendre mode 2 capsule symmetry of the implosions, including changing the wall angle of the frustraum, which is not possible with cylindrical hohlraums. A mode 4 feature was observed and its implications for hotspot mix discussed. Two layered implosions were conducted with 1.2 mm inner radius capsules, the latter of which achieved the highest layered capsule absorbed energy on the National Ignition Facility using only 1.74 MJ of laser energy. The layered implosion results, along with generalized Lawson parameters, suggest that increasing the energy absorbed by the capsule at the expense of long coast times makes it more challenging to achieve ignition and that further reducing coast time (time between end of laser pulse and bang time) closer to the 1 ns level is warranted to improve the areal density and make it easier to achieve the hotspot temperature, alpha heating, and yield amplification required for ignition.
High-intensity, ultrashort laser sources are a foundational pillar for High-Energy-Density (HED) physics, and as the repetition-rates of these systems increase, diagnostics must be developed to match their data collection speed. Characterization of any spatiotemporal distortions in the laser pulse is necessary in order to standardize results across facilities. Here, we have previously developed a laser diagnostic called Spatially and Temporally Resolved Intensity and Phase Evaluation Device: Full Information from a Single Hologram, or STRIPED FISH, to measure the full spatiotemporal laser electric field on a single shot. In order to provide rapid feedback, we here adapt the STRIPED FISH retrieval algorithm, which typically has computation times of up to 30 minutes due to the high spatial resolution of the device and its retrieval of the complete four-dimensional pulse field, to distill the key electric field quantities into a handful of scalars for rapid assessment of the pulse's first order distortions. Here, our new, rapid non-iterative retrieval algorithm is validated with simulated and experimental data, and it provides, within seconds, the same first-order information as given by the full analysis. This algorithm is suitable for on-shot assessment of spatiotemporal distortions and can be adapted to assess high repetition-rate laser quality in HED experiments.
High-energy-density physics is the field of physics concerned with studying matter at extremely high temperatures and densities. Such conditions produce highly nonlinear plasmas, in which several phenomena that can normally be treated independently of one another become strongly coupled. The study of these plasmas is important for our understanding of astrophysics, nuclear fusion and fundamental physics—however, the nonlinearities and strong couplings present in these extreme physical systems makes them very difficult to understand theoretically or to optimize experimentally. Here we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proved far too nonlinear for human researchers. Furthermore, from a fundamental perspective, our understanding can be improved by the way in which machine learning models can rapidly discover complex interactions in large datasets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to approximately daily), thus moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we suggest proposals for the community in terms of research design, training, best practice and support for synthetic diagnostics and data analysis.