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The development of high intensity petawatt lasers has created new possibilities for ion acceleration and nuclear fusion using solid targets. In such laser-matter interaction, multiple ion species are accelerated with broad spectra up to hundreds of MeV. To measure ion yields and for species identification, CR-39 solid-state nuclear track detectors are frequently used. However, these detectors are limited in their applicability for multi-ion spectra differentiation as standard image recognition algorithms can lead to a misinterpretation of data, there is no unique relation between track diameter and particle energy, and there are overlapping pit diameter relationships for multiple particle species. In this report, we address these issues by first developing an algorithm to overcome user bias during image processing. Second, we use calibration of the detector response for protons, carbon and helium ions (alpha particles) from 0.1 to above 10 MeV and measurements of statistical energy loss fluctuations in a forward-fitting procedure utilizing multiple, differently filtered CR-39, altogether enabling high-sensitivity, multi-species particle spectroscopy. To validate this capability, we show that inferred CR-39 spectra match Thomson parabola ion spectrometer data from the same experiment. Filtered CR-39 spectrometers were used to detect, within a background of ~ 2 × 1011 sr-1 J-1 protons and carbons, (1.3 ± 0.7) × 108 sr-1 J-1 alpha particles from laser-driven proton-boron fusion reactions.

An overview from the past and an outlook for the future of fundamentallaser-plasma interactions research enabled by emerging laser systems.

We present a method for generating intense vortex laser beams using spiral-phase plasma mirrors. These single-use micro-metric formations imprint a set amount of orbital angular momentum (OAM) to an arbitrary high power focusing beam. Using these beams, we irradiated ultrathin foils and measured the emission of ions from their back side. Utilizing a PW class laser, 5 J@45fs@2w resulting in an Intensity of 2×1020 W cm − 2 at spot focus, we observed an increase in the energy and numbers of these ions, compared to shots taken with reflection off flat plasma mirrors. A 45% increase in the proton numbers and a 35% increase in cutoff energy was observed. This is a major advance since the area of interaction and intensity are reduced due to the planar shape of the generated OAM laser. We review the available data-sets on laser ion acceleration using vortex beams, and conclude with a comparison to our findings. [ABSTRACT FROM AUTHOR]

High repetition rate laser systems enable new strategies for diagnosing plasma behavior with large datasets. Here, we define an ensemble technique that relies on randomized targeting of x-ray tracer micro-stripes. On each shot, a high-intensity laser pulse is focused on a solid target with Ti tracer stripes embedded in an Al foil, randomly targeting a micro-stripe, a portion of a stripe, or a gap between stripes. High-resolution, time-integrated x-ray spectrometers capture line emission from the portion of the micro-stripe that is heated to sufficiently high electron temperatures. Accumulation of many such cases is used to construct ensemble distributions of x-ray line intensities that encompass all relative offsets of the laser focus to the micro-stripe centers. Synthetic intensity distributions are likewise generated using collisional-radiative modeling. Bayesian fitting of modeled to measured intensity distributions establishes the most likely radial temperature profiles, enabling comparison to hydrodynamic models and calling into question the cylindrical symmetry of these micro-stripe-embedded systems. Ensemble techniques have significant potential for high-energy-density plasma diagnostics, especially with the advent of high repetition rate experiments. [ABSTRACT FROM AUTHOR]

X-ray line emission spectra can thoroughly characterize hot plasmas, especially when line shapes and ratios convey distinct aspects of plasma conditions. However, the high spectral resolution required for observing line shapes is often at odds with the large bandwidth required to observe many line ratios across a wide spectral range. One strategy to obtain high spectral resolution over a wide bandwidth is to use multiple crystals with calibrated reflectivity so that line intensities across different crystals can be compared. Here, we explore the use of a low-resolution, wide-bandwidth mica survey spectrometer to infer relative reflectivity of two high-resolution, narrow-bandwidth quartz crystals. A Monte Carlo error analysis determines comparable x-ray line ratios measured from both spectrometers, resulting in an in situ calibration factor and associated uncertainty for the relative reflectivity of the high-resolution crystals. [ABSTRACT FROM AUTHOR]

An ablation crater depth estimation model, founded on the concept of an ionizing bleaching wave, has been developed for metal targets irradiated by an extreme ultraviolet (EUV) laser. Two EUV capillary discharge lasers operating at a wavelength of 46.9 nm were focused onto targets of gold, aluminum, and copper using two different experimental setups to maximize the laser fluence range. The experimental ablation craters were measured using an atomic force microscope, and the depths were compared to the ionizing wave model. The model depends on the dominant ion charge of the ablated plasma, which was measured experimentally using the low fluence setup with a time-of-flight mass spectrometer. The measured ablation depths and ion charges at low fluences are in agreement with the model. The ablation crater depths in the higher fluence range confirmed the trends predicted by the model, showing potential to expand its use to other materials and fluence ranges. [ABSTRACT FROM AUTHOR]

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments. [ABSTRACT FROM AUTHOR]

Les patients atteints de maladies auto-immunes ont un risque plus élevé d'infections, en partie favorisé par les traitements reçus. La grossesse est également en soi un facteur de risque connu d'infections sévères. En raison du manque de données disponibles sur ce sujet, nous avons évalué ce risque dans l'étude prospective du GR2. Les grossesses de patientes suivies pour une connectivite et incluses dans l'étude GR2 ont été étudiées. Les infections sévères étaient définies comme ayant entraîné une hospitalisation ou un décès et étaient analysées chez les mères, les nouveau-nés et les enfants jusqu'à 1 an. Au total, 733 patientes enceintes atteintes de connectivite étaient incluses, dont 379 (51,7 %) avec un lupus systémique. 280 patientes (38,9 %, non disponible (ND) = 14) étaient sous corticoïdes, avec une dose médiane en début de la grossesse de 5,5 mg/j (IQR 5,0–10,0), 115 (15,8 %, ND = 4) sous immunosuppresseurs (principalement azathioprine et tacrolimus), 8 (1,1 %, ND = 6) sous biothérapie (principalement belimumab, infliximab, certolizumab et adalimumab) et 540 (74,0 %, ND = 3) sous hydroxychloroquine. Au 24/06/2024, les investigateurs ont déclaré 20 infections maternelles sévères (2,8 %, ND = 25), principalement des pyélonéphrites (n = 9) et des endométrites (n = 3), 7 infections néonatales sévères (1,0 %, ND = 28), principalement des infections maternofœtales (n = 5), et 5 infections sévères chez des enfants au cours de la première année de vie (1,2 %, ND = 100), principalement des infections urinaires (n = 2) et des pneumopathies (n = 2). Aucun décès en rapport avec une infection n'a été rapporté. La corticothérapie maternelle à une posologie ≥ à 10 mg/j était associée au risque de développer une infection maternelle sévère en analyse multivariée (OR 3,3 [IC95 % 1,1–9,6], p = 0,03). En analyse univariée, la prématurité était le seul facteur associé à la survenue d'une infection au cours de la première année de vie des enfants (OR 38,3 [IC95 % 1,6–432,0], p = 0,005). Le faible nombre d'infections chez les enfants n'a pas permis de réaliser d'analyses multivariées. La corticothérapie à une posologie ≥ 10 mg/j était associée à un sur-risque d'infections maternelles sévères au cours de la grossesse, mais non au risque infectieux des enfants. Seule la prématurité était associée à ce dernier. [ABSTRACT FROM AUTHOR]