Laser-Plasma Interactions

Long-Pulse LPI and Plasma Photonics

Laser–plasma interactions (LPIs) are a central focus of research regarding inertial confinement fusion (ICF) and HED science in general. LPI research deals with the nonlinear propagation of intense lasers through plasmas, their energy deposition, and all the possible instabilities that can arise due to the nonlinear coupling of light waves and plasma waves.

Significant progress has been made over the past decade due to experiments on the National Ignition Facility (NIF) at LLNL. Our efforts involve developing and implementing new mitigation strategies to keep LPI processes under control in ICF experiments. This research requires advancing our understanding of fundamental LPI processes via focused science experiments in collaboration with our partners in academia and at other national laboratories. Ultimately, these experiments inform and guide us in the development of new LPI models that can be directly incorporated into macroscopic radiative-hydrodynamics simulation codes, enabling us to describe the results from the complex mutual interactions between LPI and hydrodynamics in ICF and HED experiments.

A crucial aspect that emerged from our expanded understanding of LPI is the many ways in which plasmas can modify the fundamental properties of light, including its propagation direction, amplitude, pulse duration, or polarization. As a result, a growing effort in the past decade to explore potential opportunities in light manipulation using plasma has turned into a vibrant new area of research known as plasma photonics. Using plasma in lieu of solids (like glass or crystals) to manipulate light essentially alleviates the concerns of optics damage, which dictates the scale (and cost) of high-power laser facilities and limits the maximum achievable laser intensity with chirped-pulse amplification technology. Work that started with using plasma gratings in NIF experiments to redirect laser light inside ICF targets and fine-tune the implosion symmetry has now been extended to include new concepts of plasma waveplates and polarizers, and beam combiners, as well as the first demonstrations of slow and fast light in plasmas.

Learn More

• Research describes slow and fast light plasma
• Plasma optic combines NIF lasers into superbeam
• Controlling laser beam polarization in plasma

Relativistic Electron–Positron Pair Creation

Positrons are the antimatter particles of ordinary-matter electrons. Positrons and electrons have the same mass, but opposite charges, and they annihilate each other when they meet, converting their masses to energy. Particle accelerators are typically used to generate positrons for antimatter research.

At LLNL, we use high-power lasers to generate positrons by “zapping” a thick target made of a high-atomic-number (high-Z) material, such as gold or tantalum. This event produces very high-energy electrons, which are then deflected by the high-Z nucleus, emitting gamma rays that decay into electron-hole pairs.

In these experiments, billions of positrons are made in the laboratory in less than 100 picoseconds per laser shot—providing a new way to make antimatter accessible for exciting research avenues. For example, the interactions of laser-produced, relativistic, dense electron–positron pair plasmas could mimic the physics processes of some of the most energetic events in the universe, such as the gamma-ray bursts near black holes. We are actively working to achieve this capability. For example, we are exploring how to increase the efficiency by converting more laser energy to the electron–positron pairs, as well as by using new target and laser configurations.

Learn More

• Turbulent intensity islands give cone-shaped targets relativistic power
• Lasers shed light on the universe’s most luminous electromagnetic events—gamma-ray bursts
• Scientists produce billions of positrons using an ultra-intense, short-pulse laser

Laser–Particle Acceleration Experiments and Simulations

Short-pulse ion acceleration has been a topic of interest for decades. These energetic particles have a wide range of applications, including diagnosing extreme electromagnetic fields in laser-driven experiments; heating sample materials to extreme conditions of temperature and density; creating heavy ion or neutron sources; and providing cancerous tumor therapy. Compared to traditional particle accelerators, laser-driven acceleration takes place on the micro-meter scale with extremely large electric fields (~teraVolt/meter). The most studied ion acceleration mechanism is known as target-normal sheath acceleration. Over the last two decades, many experiments have studied this process with the aim of developing scaling laws that can be used to predict the beam characteristics from a given laser‒target interaction.

While many of these studies have been fruitful in describing scaling of the properties of these beams, experiments were typically driven by lasers with pulse widths <1 picosecond (or one trillionth of a second). At LLNL, scientists have demonstrated and explained the ability to generate tens of MeV ion beams with multi-picosecond laser interactions on the Advanced Radiographic Capability (ARC) laser at LLNL’s National Ignition Facility, which were counter to the well-established scalings. Continuing research seeks to push this capability and understanding by performing large-scale, particle-in-cell simulations of these laser experiments on LLNL’s supercomputing resources.

In addition to these expensive large-scale simulations, researchers also produce thousands of lower-dimensional (and computationally “cheaper”) simulations. By utilizing advanced machine-learning methods, scientists can now construct realistic maps of large, multi-dimensional parameter spaces to look for laser pulse and target combinations that can produce optimized ion sources. These new machine-learning-based models then serve as the basis for experimental investigations utilizing high-repetition-rate laser facilities, capable of delivering high-intensity laser pulses at multi-Hz rates.

Researchers at LLNL are developing diagnostics that can operate in extremely hostile experimental environments with integrated machine learning for rapid and accurate analysis of data “on the fly.” The simulations and experiments are being integrated through artificial intelligence in order to smartly navigate experimental investigation without human intervention—massively speeding up the process of scientific learning. The goals of this work include controlling and optimizing laser-driven particle sources, while also tailoring secondary-source delivery, including high- and low-energy x-ray sources.

Learn More

• Laser-driven ion acceleration research benefits from machine learning technique
• The data-driven future of extreme physics