Neural simulation-based inference on unbinned top-quark pair data at 13 TeV yields improved gluon PDF precision over traditional binned analyses while incorporating experimental and theoretical uncertainties.
Measurement of off-shell Higgs boson production in theH ∗ →ZZ→4ℓ decay channel using a neural simulation-based inference technique in 13 TeV pp collisions with the ATLAS detector
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Factorizable Normalizing Flows represent parameter-dependent densities via a reference flow composed with a factorized polynomial transformation, enabling isolated per-parameter learning and linear scaling.
The Minimum Resolution Likelihood method defines a fiducial signal region to convert ML-induced systematic effects into statistical uncertainties for unbiased signal strength estimation in collider analyses.
A hybrid NSBI technique is presented for inferring the Higgs trilinear coupling via off-shell production in SMEFT, achieving near-theoretical-optimum sensitivity with expected HL-LHC constraints.
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Proton Structure from Neural Simulation-Based Inference at the LHC
Neural simulation-based inference on unbinned top-quark pair data at 13 TeV yields improved gluon PDF precision over traditional binned analyses while incorporating experimental and theoretical uncertainties.
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Defining a Minimum Resolution for Unbinned Analyses
The Minimum Resolution Likelihood method defines a fiducial signal region to convert ML-induced systematic effects into statistical uncertainties for unbiased signal strength estimation in collider analyses.
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Neural simulation-based inference of the Higgs trilinear self-coupling via off-shell Higgs production
A hybrid NSBI technique is presented for inferring the Higgs trilinear coupling via off-shell production in SMEFT, achieving near-theoretical-optimum sensitivity with expected HL-LHC constraints.