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The Entropy of a Jet

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arxiv 1811.01021 v2 pith:Q3HNWUFD submitted 2018-11-02 hep-ph hep-thnucl-th

classification hep-phhep-thnucl-th
keywords entropyhardstatesinfraredscatteringdensitymatrixapproximation
verification ladder T0 review T1 audit T2 compute T3 formal

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Scattering processes often inevitably include the production of infrared states, which are highly correlated with the hard scattering event, and decohere the hard states. This can be described using the entropy of the hard reduced density matrix, which is obtained from tracing over infrared states. We determine this entropy for an asymptotically-free gauge theory by separating the Hilbert space into hard and infrared states, and calculate it in a leading-logarithmic approximation for jets. We find that the entropy increases when the resolution scales defining the hard radiation are lowered, that this entropy is related to the subjet multiplicity, and explore connections to using jet images for machine learning, and the forward-scattering density matrix of partons in a nucleon probed in deep-inelastic scattering.

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Exploring the Space of Jets with CMS Open Data

    hep-ph 2019-08 accept novelty 6.0 of 10

    The authors apply the energy mover's distance to 1.69 million jets from CMS open data and show that track-based jet studies, including visualizations and anomaly scoring, work on real collider data.

  2. How much joint resummation do we need?

    hep-ph 2019-08 conditional novelty 6.0 of 10

    Joint resummation of two angularities, rather than one or many, yields the largest gain in predicting other angularities in e+ e- dijet events.

  3. Particle production in the toy world: multiplicity distribution and entropy

    hep-ph 2024-12 conditional novelty 5.0 of 10

    In the Unitary Toy Model, final-state dipole multiplicity is computed via AGK cutting rules; its entropy matches the BFKL result S_E = ln(xG), while the UTM initial-state distribution differs.

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