main webpage W Topic Classical Mechanics SciPost Physics • Vol 14 • No 3 Modeling hadronization using machine learning 2023 We present the first steps in the development of a new class of hadronization models utilizing machine learning techniques. We successfully implement, validate, and train a conditional sliced-Wasserstein autoencoder to replicate the Pythia generated kinematic… Article Open Classical Mechanics Open Article Page

Classical Mechanics

Description of large objects' physics Classical mechanics is a physical theory describing the motion of macroscopic objects, from projectiles to parts of machinery and astronomical objects, such as spacecraft, planets, stars, and galaxies. For objects governed by classical mechanics, if the present state is known, it is possible to predict how it will move in the future (determinism), and how it has moved in the past (reversibility). The "classical" in "classical mechanics" does not refer to classical antiquity, as it might in, say, classical architecture. On the contrary, the development of classical mechanics involved substantial change in the methods and philosophy of physics. Critical Symbolic Virtual Narrative Open Classical Mechanics Open Article Page

Exploring foci of: SciPost Physics • Vol 14 • No 3 Modeling hadronization using machine learning 2023 We present the first steps in the development of a new class of hadronization models utilizing machine learning techniques. We successfully implement, validate, and train a conditional sliced-Wasserstein autoencoder to replicate the Pythia generated kinematic distributions of first-hadron emissions, when the Lund string model of hadronization implemented in Pythia is restricted to the emissions of pions only. The trained models are then used to generate the full hadronization chains, with an IR cutoff energy impos… Open Article Page

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Explore Classical Mechanics W Topic Classical Mechanics SciPost Physics • Vol 14 • No 3 Modeling hadronization using machine learning 2023 We present the first steps in the development of a new class of hadronization models utilizing machine learning techniques. We successfully implement, validate, and train a conditional sliced-Wasserstein autoencoder to replicate the Pythia generated kinematic… Article Critical Symbolic Virtual Narrative Open Classical Mechanics Open Article Page