NET4EXA EuroHPC JU Project Seeks to Advance European Interconnect for HPC and AI

The US government recently stood up a consortium of six Washington D.C.-based federal agencies to explore a range of quantum technologies necessary to create, demonstrate, and operate DC-QNet, a regional, multi-kilometer quantum network testbed. The six participating agencies span a range of US government mission agencies including the National Security Agency, the US Naval Research Laboratory, the National Institute of Standards and Technology, and the National Aeronautics and Space Administration. The program targets key underlying technologies needed to implement a metro[1]area quantum network that includes high-fidelity quantum memory, single photon devices, and related network metrology as well as mechanisms to support quantum entanglement between network nodes in a quantum computer. Details about project schedule and budget have not yet been made available, but each participating agency will be responsible for funding its research activities.

At the conclusion of 2021, researchers at UNC Charlotte and Duke University Medical Center published results of work done to use transfer learning methods to generate fluence maps for radiation therapy, aimed at providing medical professionals with more capability and information in fighting adrenal cancers. The technique uses a deep transfer learning model trained on a much larger dataset that can be applied to a smaller data set for a specific application.

• The initial model was trained on pancreas treatment plans, then retuned and applied to a smaller set of data points on adrenal cancers. The output of the model generates a fluence map for specific IMRT beam-based treatments for adrenal cancers.
• According to the researchers, this approach is meant to supplement but not replace human expertise in the field and is reliant on human expertise to finetune and improve the AI model.