首页|Research in the Area of Machine Learning Reported from University of Cincinnati (Simulating Hadronization with Machine Learning)
Research in the Area of Machine Learning Reported from University of Cincinnati (Simulating Hadronization with Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting from the University of C incinnati by NewsRx journalists, research stated, "Hadronization is an important part of physics modeling in Monte Carlo event generators, where quarks and gluo ns are bound into physically observable hadrons." Our news journalists obtained a quote from the research from University of Cinci nnati: "Today's generators rely on finely-tuned phenomenological models, such as the Lund string model; while these models have been quite successful overall, t here remain phenomenological areas where they do not match data well. A machine- learning-based alternative called MLhad, intended ultimately to be data-trainabl e, can simulate hadronization by encoding latentspace vectors, trained to be dis tributed according to a user-defined distribution using the sliced-Wasserstein d istance in the loss function, then decoding them. The multiplicities and cumulat ive kinematic distributions of pions generated with MLhad in this way match thos e generated using Pythia 8. While this architecture has been successful, an alte rnative using normalizing flows is convenient for generating non-pion hadrons an d for taking advantage of reweighting techniques to reduce computing time."
University of CincinnatiCyborgsEmerg ing TechnologiesMachine Learning
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