LLNL researchers have developed a high average power Faraday rotator that is gas-cooled and uniquely designed to dissipate heat uniformly so that it does not build up in the optical component and affect its performance.  The Faraday rotator material is sliced into smaller disks like a loaf of bread so that high speed helium gas can flow between the slices.  With this highly efficient cooling…

This invention discloses a method to minimize transient variations in the wavelength- and/or pointing-behavior of an optic, without requiring a reduction in its thermal resistance, optical absorption, or operating irradiance. The invention employs a combination of a time-varying heat source and time-varying thermal resistance and/or heat sink temperature to achieve temperature stability of the…

This invention concerns a new type of optic: a transient gas or plasma volume grating produced indirectly by small secondary lasers or directly by nonlinear processes using the primary beams themselves. When used in conjunction with advantageously placed shielding it offers a means of protecting the final optical components of a high-repetition-rate IFE facility. These transmission optics are…

Lawrence Livermore National Laboratory (LLNL) is offering the opportunity to collaborate in accelerating artificial intelligence (AI) for applied science, including research in key areas such as advanced material design, 3D printing, predictive biology, energy systems, “self-driving” lasers and fusion energy research.

Clinical images have a wealth of data that are currently untapped by physicians and machine learning (ML) methods alike. Most ML methods require more data than is available to sufficiently train them. In order to obtain all data contained in a clinical image, it is imperative to be able to utilize multimodal, or various types of, data such as tags or identifications, especially where spatial…

Some COVID-19 diagnoses are utilizing computed tomography (CT)-scans for triage. CT-scans produce immediate results with high sensitivity. The digital images produced by a CT-scan require physicians to identify objects within the image to determine the presence of disease. Object identification can be done using machine learning (ML) techniques such as deep learning (DL) to improve speed and…

MimicGAN represents a new generation of methods that can “self-correct” for unseen corruptions in the data out in the field. This is particularly useful for systems that need to be deployed autonomously without needing constant intervention such as Automated Driver Assistance Systems. MimicGAN achieves this by treating every test sample as “corrupt” by default. The goal is to determine (a) the…

LLNL has developed a new system, called the Segmentation Ensembles System, that provides a simple and general way to fuse high-level and low-level information and leads to a substantial increase in overall performance of digital image analysis. LLNL researchers have demonstrated the effectiveness of the approach on applications ranging from automatic threat detection for airport security, to…