Search NASA⌕ Search

DOE OSTI · 1116870

Laser-Wakefield driven compact Compton scattering gamma-ray source

Abstract

We propose to demonstrate a novel x-ray and gamma-ray light source based on laser-plasma electron acceleration and Compton scattering at the Jupiter Laser Facility at LLNL. This will provide a new versatile and compact light source capability at the laboratory with very broad scientific applications that are of interest to many disciplines. The source’s synchronization with the seed laser system at a femtosecond time scale (i-e, at which chemical reactions occur) will allow scientists to perform pump-probe experiments with x-ray and gamma-ray beams. Across the laboratory, this will be a new tool for nuclear science, high energy density physics, chemistry, biology, or weapons studies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Albert, F., Froula, D. H., Hartemann, F. V., Joshi, C.. 2010-04-13. Laser-Wakefield driven compact Compton scattering gamma-ray source. https://doi.org/10.2172/1116870

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗