Yasuhiro Kuramitsu

Generating 100-MeV protons is pivotal to developing laser-driven ion sources for many applications that range from medicine to laboratory astrophysics. An ultra-thin target is a way to increase the ion energy; however, such a target is easily destroyed by the interaction with laser prepulses. We have developed a large-area suspended graphene (LSG) target and demonstrated its durability by generating energetic protons and carbons by irradiating the thinnest target ever (2 nm) with an ultra-intense laser without a plasma mirror. Here, we show the experimental results of proton energies reaching 132 MeV by optimizing the laser conditions for the ultra-thin LSG targets. Ion diagnostics were primarily performed using a CR-39 stack detector combined with machine-learning-assisted analysis. Numerical simulations support the experimental results, where the radiation pressure of a relatively long-duration, low-intensity laser pulse slowly pushes the plasma, leading to the formation of a propagating electrostatic wave that efficiently accelerates protons, as in surfing acceleration.

Reconstructing multidimensional vector fields from path-integrated projection data is a fundamental challenge in high-energy-density physics, particularly when experimental sources exhibit spectral broadening and shot-to-shot jitter. We present a physics-guided deep-learning framework that addresses this ill-posed inverse problem by formulating global reconstruction as an aggregation of local inference tasks. By training a neural network on single-particle trajectories in randomized uniform magnetic fields, we develop a “local solver” that demonstrates strong zero-shot transfer to previously unseen magnetohydrodynamic topologies. Central to addressing non-ideal laser-driven proton sources, we introduce a spectral out-of-distribution filter that rejects inputs outside the training energy envelope. By preventing extrapolation, the filter enables accurate reconstruction within the represented training domain while maintaining stable populated-cell reconstruction metrics across diverse spectral conditions. Furthermore, we introduce an a priori reconstruction-reliability indicator based on the in-distribution fraction of the source spectrum, which provides a practical estimate of reconstruction coverage before inference. This approach can be integrated with energy-resolved detector systems, such as stacked nuclear track detectors, establishing a practical and highly parallelizable framework for quantitative plasma diagnostics.

Wakefield acceleration has been considered a possible mechanism for producing cosmic rays, including extremely high-energy ions, especially in astrophysical environments. In the laboratory, however, laser-driven wakefield acceleration of ions remains challenging because ions are much heavier than electrons. A central issue is how ions enter the accelerating field. One possible route with present laser facilities is to use dense plasma, in which the wake moves more slowly and ions can be trapped by the bow wake formed at the laser front. Here we experimentally demonstrate bow-wake acceleration of protons using resorcinol-formaldehyde foam targets. We obtain protons with energies up to 60 MeV. Three-dimensional particle-in-cell simulations support the interpretation that the protons are accelerated by the bow wake. These results show that dense plasma can enable ion injection into laser-driven wakes and provide a laboratory route toward bow-wake acceleration of high-energy ions.

Recent advances in laser-driven ion acceleration have brought GeV-class carbon acceleration closer to realization. For high-energy ion measurements, we have used a stack detector, which consists of plastic nuclear track detectors, such as CR-39 and aluminum energy absorbers. In such experiments, etch pit analysis from a large number of microscope images is required. To handle these massive datasets efficiently, the etch pit analysis was automated with the aid of machine learning. However, as the ion energy increases, secondary fragments generated within the CR-39 stack detector make a non-negligible contribution, and their impact on the measured energy spectra remains unclear. In this study, secondary fragments produced by GeV-class carbon ions incident on a CR-39 stack detector were examined at a conventional accelerator. The results show that the ratio of secondary fragments to incident carbon increases with depth, reaching more than 20%. In addition, comparison of linear energy transfer distributions with a Monte Carlo nuclear particle transport simulation revealed the production of Li, Be, and B. These findings highlight the importance of accounting for secondary fragments in precise high-energy heavy-ion measurements using CR-39 stack detectors.

Diagnosing turbulent electromagnetic fields in laser-driven plasmas is challenging because ion radiography cannot easily resolve the electric and magnetic field components. To address this limitation, we propose and numerically investigate a reconstruction method based on encoder–decoder convolutional neural networks. We construct a simulation dataset for training and testing the neural networks by pairing electric fields generated in hydrodynamic simulations with corresponding synthetic ion radiographs obtained from test particle simulations. Using the resulting dataset, we systematically investigate the influence of several key factors on the reconstruction, including the addition of synthetic noise, variations in the probing ion flux, and the use of different input data types.

In relativistic plasma expansion, a relative motion of plasma components causes absorption of spectral lines to be Doppler-shifted with respect to the emission line centers. The shift of spectral line can be of an order or exceeding the natural linewidth, leading to a significant reduction in self-absorption and optical thickness of the plasma. In this paper we experimentally examine the effect of femtosecond relativistic laser plasma expanding from both sides of the solid foil target. In an experiment, a hot plasma x-ray source in a 1–2 μm thin 4-chlorostyrene foil was created by high-contrast ∼ 1 × 1021 W/cm2 pulses delivered by the J-KAREN-P facility. In addition, the rear side of the target was heated by 1/100 of the main pulse power with a controlled few-nanosecond time delay. It is demonstrated that the high velocity of the downstream and upstream (from the rear side) plasma expansion essentially induces plasma transparency for K-shell emission from He-like chlorine ions dominating the ion charge distribution.

Induced Compton scattering (CS) is a quantum nonlinear interaction between an intense electromagnetic field and a rarefied plasma. Although the induced CS is expected to occur in radiation fields with high brightness temperatures such as pulsars in nature, the principle of induced CS has not been proven experimentally. Therefore, we conducted a proof‐of‐principle experiment of induced CS using an ultra‐intense laser. We measured the scattered spectra due to the interaction between the ultra‐intense laser and plasma. The observed spectrum shows a nonlinear redshift, which can be explained by induced CS. We also performed particle‐in‐cell simulations, in which induced CS is not included, and found that the experimental results are not explained by classical plasma physics.

Velocity vector measurement of laser-driven ions is essential to reconstructing electromagnetic fields in plasmas with ion radiography. A stack of solid-state nuclear track detectors can be used to diagnose the energy and incident angle of protons, which corresponds to the velocity vector measurement. However, the measured incident angle deviates from the normal when the ions are irradiated from a normal direction to the detector. In order to calibrate this, we irradiate an accelerator-generated proton beam on the CR-39 stack by changing incident angles. We analyze ion etch pits on scanned microscope images of the CR-39 with a convolutional neural network. While the measured angle agrees well with the incident angle when the incident angle ≲75 degrees, it tends to deviate from the incident angle as the incident angle approaches the normal direction. By numerically evaluating the proton incident angles using Monte Carlo simulations, we show qualitatively consistent results with our experimental results. We discuss the theoretical limitation of the standard formulation of etch pit analyses. We also show that the angle measurements are significantly affected by the resolution of etch pit images.

Short‐pulse intense lasers have the potential to model extreme astrophysical environments in laboratories. Although there are diagnostics for energetic electrons and ions resulting from laser‐plasma interactions, the diagnostics to measure velocity distribution functions at the interaction region of the laser and plasma are limited. We have been developing the diagnostics of the interaction between the intense laser and plasma using scattered intense laser. We performed experiments to measure electron density by observing the spatial distributions and the ratio of horizontal to vertical polarization components of the scattered laser beam using optical imaging. The observed ratio of polarization components is consistent with the drive laser beam, indicating the observed light originates from the drive laser. Imaging of the scattered light shows the structure of electron density, the zero moment of the electron velocity distribution function, interacting with the intense laser. We observed the change of structure due to the laser pre‐pulse that destroys the target before the arrival of the main pulse.