We design and characterize a platform to radiograph a hohlraum-driven shock simultaneously using two radiographic probes: x-rays and protons. The platform was characterized with the VISAR diagnostic and complementary simulations from the LANL code FLAG.

project, we are following three paths to determine if such an approach will succeed for cm-scale objects. The first is an experimental one to determine if the presence of multiple short-pulse probes cause interference with each other, especially while radiographing dynamic objects. The second leg of this project is to determine if having multiple types of probes really does give more information on composition. Finally, an overall assessment of the viability of this approach will be made. Examples from recent experiments at the Omega EP laser will be presented. The initial approach to evaluating radiographs with multiple probes using the Bayesian Inference Engine (BIE) also will be given.

A plastic scintillator has found extensive application in the realm of high-energy physics and national security science. Many applications in those fields often involve the simultaneous production of photons, neutrons, and charged particles, which makes the relative sensitivity information for these different radiation types important. In this study, we have adopted a multi-head detector comprised of a plastic scintillator and high gain phototubes, which provides a large dynamic range and linearity. A comparative study on the relative sensitivities of plastic scintillators was facilitated by adopting three distinct radiation calibration sources (i.e., 60Co γ rays, DD neutrons, and DT neutrons). Neutrons from a DD source generate a comparable level of scintillation to gamma rays emitted by 60Co (i.e., 60Co-γ/DD-n = 0.92 ± 16%). DT neutrons induce ∼3.5 times the scintillation observed with DD neutrons (i.e., DT-n/DD-n = 3.5 ± 28%). In addition, the Geant4 simulation granted us valuable insights into the relative sensitivity of the scintillator. This comparative study will provide a useful database for users in diverse applications.

The multi-decade neutron dosimeter and imaging diagnostic (MDND) is a passive diagnostic that utilizes the polyethylene (n, p) nuclear reaction to enhance the diagnostic's sensitivity for time and energy integrated neutron measurements in the range of 2.45-14.1 MeV. The MDND utilizes a combination of radiochromic film, phosphor image plates, and solid-state nuclear track detectors, with the goal of providing several orders of magnitude of dynamic range in terms of measured neutron fluence. The diagnostic design was guided by simulations in the Monte Carlo N-Particle (MCNP) transport code to determine the optimum thickness of the polyethylene convertor for maximum proton fluence incident on the detection medium as a function of incident neutron energy. In addition, the simulation results of complete diagnostic assemblies, or "stacks," were used to determine the total dynamic range of an MDND in terms of measured neutron source yield, which was found to be between around 10(7) and 10(15) emitted into 4 pi with the detector located 1 m away from the source. Complimentary to these simulations, individual detectors within a stack were simulated and analyzed to determine response as a function of neutron energy and yield. This work presents the diagnostic design, MCNP simulation results, and analysis of expected signals for varying neutron sources. (c) 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license

We present an inversion method capable of robustly unfolding MeV x-ray spectra from filter stack spectrometer (FSS) data without requiring an a priori specification of a spectral shape or arbitrary termination of the algorithm. Our inversion method is based upon the perturbative minimization (PM) algorithm, which has previously been shown to be capable of unfolding x-ray transmission data, albeit for a limited regime in which the x-ray mass attenuation coefficient of the filter material increases monotonically with x-ray energy. Our inversion method improves upon the PM algorithm through regular smoothing of the candidate spectrum and by adding stochasticity to the search. With these additions, the inversion method does not require a physics model for an initial guess, fitting, or user-selected termination of the search. Instead, the only assumption made by the inversion method is that the x-ray spectrum should be near a smooth curve. Testing with synthetic data shows that the inversion method can successfully recover the primary large-scale features of MeV x-ray spectra, including the number of x-rays in energy bins of several-MeV widths to within 10%. Fine-scale features, however, are more difficult to recover accurately. Examples of unfolding experimental FSS data obtained at the Texas Petawatt Laser Facility and the OMEGA EP laser facility are also presented.

On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.

We present a reduced-order model to calculate response matrices rapidly for filter stack spectrometers (FSSs). The reduced-order model allows response matrices to be built modularly from a set of pre-computed photon and electron transport and scattering calculations through various filter and detector materials. While these modular response matrices are not appropriate for high-fidelity analysis of experimental data, they encode sufficient physics to be used as a forward model in design optimization studies of FSSs, particularly for machine learning approaches that require sampling and testing a large number of FSS designs.

Well over 100 diagnostics can operate on the National Ignition Facility (NIF) as a result of several decades of development on NIF, and before that on Nova, OMEGA, and earlier LLNL lasers. A subset of these have guided the approach to achieving ignition on the NIF in 2022 [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129(7), 075001 (2022)]. Achieving ignition on NIF has required many types of experiments with this core set of diagnostics, some constraining known unknowns and some revealing surprises—arguably unknown unknowns. Early design work realized that the extreme precision required for ignition on NIF would require fine-tuning by experiment, that is, measuring and adjusting known unknowns. Many examples are given where the use of the core set of ignition diagnostics in experimental arrangements called platforms demonstrated control of the key theoretical parameters defined as shape, adiabat, velocity, and mix. The direction of the adjustments to input conditions is found either by trend analysis or, in many cases, by observing from the diagnostic data the direction to make an adjustment. In addition, diagnostics have revealed some unexpected or neglected known issues, which degrade performance, or unexpected issues, unknown unknowns. Some of these factors had been previously considered, but underestimated or difficult to calculate at the time. The overall methodology can be described as a variant of Popper's falsifiability philosophy [K. Popper, The Logic of Scientific Discovery (Hutchinson, 1974)]. This paper summarizes the role of ignition diagnostics in terms of falsification or validation of theory or experimental setup as well as uncovering unexpected issues. The journey to ignition started in the seventies with a 1-µm wavelength laser producing disastrous results. Diagnostics have guided us to the recent multi-decadal goal of demonstrating ignition and burn in the laboratory.

We demonstrate the application of neural networks to perform x-ray spectra unfolding from data collected by filter stack spectrometers. A filter stack spectrometer consists of a series of filter-detector pairs, where the detectors behind each filter measure the energy deposition through each layer as photo-stimulated luminescence (PSL). The network is trained on synthetic data, assuming x-rays of energies <1 MeV and of two different distribution functions (Maxwellian and Gaussian) and the corresponding measured PSL values obtained from five different filter stack spectrometer designs. Predicted unfolds of single distributions are near identical reproductions of the ground truth spectra, with differences in the values lower than 20% at the higher energy end in some cases. The neural network has also demonstrated robustness to experimental measurement errors of <5% and some capability of performing unfolds for linear combinations of the two distributions without previous training. The network can perform unfolds at rates >1 Hz, ideal for application to some high-repetition-rate systems.

Radiography with multiple probe species offers the potential to extract additional information about a given object as compared to radiography with a single probe species. The flexibility for high-power, short-pulse lasers to accelerate a variety of particle species makes laser-driven sources an attractive option to achieve multi-probe radiography. However, crosstalk produced by each of laser-driven source may be responsible for substantial backgrounds on detectors, becoming a significant barrier to achieving simultaneous radiography. In this work, we describe measurements of and mitigation strategies against crosstalk between laser-driven radiography sources in experiments at the OMEGA EP laser.

continues examining the origin and nature of the x-ray background found in our last two experiments. This background is not well understood or characterized by the community. The first day will measure the electrons emanating from the proton and x-ray targets while also optimizing the background shielding first used in FY23. The second day will test a geometry that enables simultaneous radiographs using both short-pulse beams.

The National Diagnostic Working Group (NDWG) has led the effort to fully exploit the major inertial confinement fusion/high-energy density facilities in the US with the best available diagnostics. These diagnostics provide key data used to falsify early theories for ignition and suggest new theories, recently leading to an experiment that exceeds the Lawson condition required for ignition. The factors contributing to the success of the NDWG, collaboration and scope evolution, and the methods of accomplishment of the NDWG are discussed in this Review. Examples of collaborations in neutron and gamma spectroscopy, x-ray and neutron imaging, x-ray spectroscopy, and deep-ultraviolet Thomson scattering are given. An abbreviated history of the multi-decade collaborations and the present semiformal management framework is given together with the latest National Diagnostic Plan.

Short-pulse laser driven x-ray radiography offers the potential to improve spatial and temporal resolution for the dynamic imaging of shockwaves within materials. Here x-rays in the tens to hundreds of keV are used to image a Cr foil with an internal shockwave of ~100 μm width and a factor of two increase in density. The experimental configuration was assessed with a set of static and dynamic x-ray radiography experiments at Omega EP with a compound parabolic concentrator (CPC) cone with a Ta wire target to physically limit x-ray source size and a magnetic field to deflect background signal from electrons.