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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
Princeton-led team develops AI for fusion plasma monitoring
A new AI software tool for monitoring and controlling the plasma inside nuclear fuel systems has been developed by an international collaboration of scientists from Princeton University, Princeton Plasma Physics Laboratory (PPPL), Chung-Ang University, Columbia University, and Seoul National University. The software, which the researchers call Diag2Diag, is described in the paper, “Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas,” published in Nature Communications.
S. Pearlstein
Nuclear Science and Engineering | Volume 58 | Number 4 | December 1975 | Pages 354-360
Technical Paper | doi.org/10.13182/NSE75-A26791
Articles are hosted by Taylor and Francis Online.
A representation for structured data is described that does not make use of a resonance parameter formalism and is applicable in a region where resonance parameters cannot be resolved or in a resolved resonance region where the precise location of a resonance is unimportant. Following the Probability Table Method, a representation statistically equivalent to a pointwise description of data is given but extended to characterize energy correlations. In the case of data from which higher order derivatives can be taken, a method for temperature broadening and unbroadening data is presented.
