Laser-driven ramp-compression experiments on the national ignition facility.

This report details the analyses and related uncertainties in measuring longitudinal-stress-density paths in indirect laser-driven ramp equation-of-state (EOS) experiments [Smith et al., Nat. Astron. 2(6), 452-458 (2018); Smith et al., Nature 511(7509), 330-333 (2014); Fratanduono et al., Science 372(6546), 1063-1068 (2021); and Fratanduono et al., Phys. Rev. Lett. 124(1), 015701 (2020)]. Experiments were conducted at the National Ignition Facility (NIF) located at the Lawrence Livermore National Laboratory. The NIF can deliver up to 2 MJ of laser energy over 30 ns and provide the necessary laser power and control to ramp compress materials to TPa pressures (1 TPa = 10 × 106 atmospheres). These data provide low-temperature solid-state EOS data relevant to the extreme conditions found in the deep interiors of giant planets. In these experiments, multi-stepped samples with thicknesses in the range of 40-120 µm experience an initial shock compression followed by a time-dependent ramp compression to peak pressure. Interface velocity measurements from each thickness combine to place a constraint on the Lagrangian sound speed as a function of particle velocity, which in turn allows for the determination of a continuous stress-density path to high levels of compressibility. In this report, we present a detailed description of the experimental techniques and measurement uncertainties and describe how these uncertainties combine to place a final uncertainty in both stress and density. We address the effects of time-dependent deformation and the sensitivity of ramp EOS techniques to the onset of phase transformations.

Measuring the melting curve of iron at super-Earth core conditions.

The discovery of more than 4500 extrasolar planets has created a need for modeling their interior structure and dynamics. Given the prominence of iron in planetary interiors, we require accurate and precise physical properties at extreme pressure and temperature. A first-order property of iron is its melting point, which is still debated for the conditions of Earth's interior. We used high-energy lasers at the National Ignition Facility and in situ x-ray diffraction to determine the melting point of iron up to 1000 gigapascals, three times the pressure of Earth's inner core. We used this melting curve to determine the length of dynamo action during core solidification to the hexagonal close-packed (hcp) structure. We find that terrestrial exoplanets with four to six times Earth's mass have the longest dynamos, which provide important shielding against cosmic radiation.

Radiographic areal density measurements on the OMEGA EP laser system.

We describe two orthogonal radiography geometries at the OMEGA EP laser facility, which we refer to as side-on and face-on radiography. This setup can be used to determine quantitative information about the areal densities in solid, particulate, or liquid samples. We show sample images from these two different platforms that use the radiography diagnostic, one of material microjetting by the Richtmeyer-Meshkov instability and one of a deforming tin sample by the Rayleigh-Taylor instability, demonstrating the versatile applicability of such measurements in the field of high-energy density physics. The analytical methodology behind the quantitative Rayleigh-Taylor face-on radiography is also demonstrated and can be applied to other types of samples.

The data-driven future of high-energy-density physics.

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. 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.

Single-Shot Multi-Frame Imaging of Cylindrical Shock Waves in a Multi-Layered Assembly.

We demonstrate single-shot multi-frame imaging of quasi-2D cylindrically converging shock waves as they propagate through a multi-layer target sample assembly. We visualize the shock with sequences of up to 16 images, using a Fabry-Perot cavity to generate a pulse train that can be used in various imaging configurations. We employ multi-frame shadowgraph and dark-field imaging to measure the amplitude and phase of the light transmitted through the shocked target. Single-shot multi-frame imaging tracks geometric distortion and additional features in our images that were not previously resolvable in this experimental geometry. Analysis of our images, in combination with simulations, shows that the additional image features are formed by a coupled wave structure resulting from interface effects in our targets. This technique presents a new capability for tabletop imaging of shock waves that can be extended to experiments at large-scale facilities.

Effectiveness of commercial video gaming on fine motor control in chronic stroke within community-level rehabilitation.

PURPOSE: The purpose of this study was to investigate the effectiveness of commercial gaming as an intervention for fine motor recovery in chronic stroke. METHODS: Ten chronic phase post-stroke participants (mean time since CVA = 39 mos; mean age = 72 yrs) completed a 16-session program using the Nintendo Wii for 15 min two times per week with their more affected hand (10 right handed). Functional recovery (Jebsen Hand Function Test (JHFT), Box and Block Test (BBT), Nine Hole Peg Test (NHPT)), and quality of life (QOL; Stroke Impact Scale (SIS)) were measured at baseline (pre-testing), after 8 sessions (mid-testing) and after 16 sessions (post-testing). RESULTS: Significant improvements were found with the JHFT, BBT and NHPT from pre-testing to post-testing (p = 0.03, p = 0.03, p = 0.01, respectively). As well, there was an increase in perceived QOL from pre-testing to post-testing, as determined by the SIS (p = 0.009). CONCLUSION: Commercial gaming may be a viable resource for those with chronic stroke. Future research should examine the feasibility of this as a rehabilitation tool for this population. IMPLICATIONS FOR REHABILITATION: Stroke survivors often live with lasting effects from their injury, however, those with chronic stroke generally receive little to no rehabilitation due to a perceived motor recovery plateau. Virtual reality in the form of commercial gaming is a novel and motivating way for clients to complete rehabilitation. The Nintendo Wii may be a feasible device to improve both functional ability and perceived quality of life in chronic stroke survivors.