Gradient boosted decision trees suppress diphoton backgrounds while adaptive symbolic memetic regression corrects beam deflection biases, reaching luminosity uncertainties below 10^{-4} and 5x10^{-6}.
arXiv (2025)
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Performance study of the ILD silicon-tungsten calorimeter with timing for B and tau physics at the Z pole, highlighting pi0 reconstruction and genuine vs fake photon identification.
citing papers explorer
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Novel Machine Learning Methods to Improve Z Pole Integrated Luminosity at Future Colliders
Gradient boosted decision trees suppress diphoton backgrounds while adaptive symbolic memetic regression corrects beam deflection biases, reaching luminosity uncertainties below 10^{-4} and 5x10^{-6}.
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Ultra-Granular Calorimeter Performances for the Heavy Flavor Physics Program at the Z Peak
Performance study of the ILD silicon-tungsten calorimeter with timing for B and tau physics at the Z pole, highlighting pi0 reconstruction and genuine vs fake photon identification.