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PISCEES is a SciDAC Earth System Modeling project with the following goals: (1) To develop and apply robust, accurate, and scalable dynamical cores for ice sheet modeling on structured and unstructured meshes with adaptive refinement, (2) To evaluate ice sheet models using new tools and data sets for verification and validation (V&V) and uncertainty quantification (UQ), (3) to integrate these models and tools into DOE's Accelerated Climate Model for Energy (ACME). Using improved estimates of ice sheet initial conditions, we will simulate decade-to-century-scale evolution of the Greenland and Antarctic ice sheets, running PISCEES ice sheet models both in standalone mode and coupled to ACME. We aim to provide useful, credible predictions, including uncertainty ranges, of future ice-sheet mass loss and resulting changes in climate and sea level.
PISCEES is jointly funded by the Office of Biological and Environmental Research (BER) and the Office of Advanced Scientific Computing Research (ASCR) of the DOE Office of Science.
Principle Investigator: Steve Price - LANL and Esmond Ng – LBNL, Kate Evans - ORNL site PI
PISCEES is jointly funded by the Office of Biological and Environmental Research (BER) and the Office of Advanced Scientific Computing Research (ASCR) of the DOE Office of Science.
Principle Investigator: Steve Price - LANL and Esmond Ng – LBNL, Kate Evans - ORNL site PI
The Accelerated Climate Modeling for Energy (ACME) project is a newly launched project sponsored by the Earth System Modeling (ESM) program within U.S. Department of Energy's (DOE’s) Office of Biological and Environmental Research. ACME is an unprecedented collaboration among eight national laboratories and six partner institutions to develop and apply the most complete, leading-edge climate and Earth system models to challenging and demanding climate-change research imperatives. It is the only major national modeling project designed to address DOE mission needs to efficiently utilize DOE leadership computing resources now and in the future. While the project capabilities will address the critical science questions, its modeling system and related capabilities also can be flexibly applied by the DOE research community to address mission-specific climate change applications from U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather.
Situ combines anomaly detection and data visualization to provide a distributed, streaming platform for discovery and explanation of suspicious behavior to enhance situation awareness.
Security event data, such as intrusion detection system alerts, provide a starting point for analysis, but are information impoverished. To provide context, analysts must manually gather and synthesize relevant data from myriad sources within their enterprise and external to it. Analysts search system logs, network flows, and firewall data; they search IP blacklists and reputation lists, software vulnerability information, malware and threat data, OS and application vendor blogs, and news sites. All of these sources are manually searched for data relevant to the event being investigated. Relevant results must then be brought together and synthesized to put the event in context and make decisions about its importance and impact.
The goal of the proposed work is to bring powerful, flexible analytics to the analysts’ fingertips.
This project develops a multi-scale anomaly detection algorithm for time-varying graph data.
Entangled photons possess many strange properties which make them invaluable tools in physics. This project seeks to push their entanglement to fundamental limits for new applications in quantum information processing.
Nonlinear interferometers, which use parametric amplifiers in place of beam splitters, can improve the signal to noise ratio of interferometric sensors by a factor of twice the power gain. Recently ORNL has realized a novel, inherently stable, nonlinear interferometer using nonlinear rubidium (Rb) vapor. This approach reduces the complexity and the size, weight and power requirements (SWAP) of earlier demonstrations. However, it is still constructed using bulk, free-space optics on a lab table. This project seeks to realize a reduced SWAP further and perform measurements to quantify its performance relative to other approaches.
We propose an entirely new experimental photonic qubit interface which will enable quantum connections between common material qubits such as ions or atoms.