Measured inclusive B(Z → 4ℓ) = 4.67 ± 0.21 × 10^{-6} with individual modes, differential distributions, and triple-product asymmetry limits.
PyUnfold: A Python Package for Iterative Unfolding
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abstract
PyUnfold is a Python package for incorporating imperfections of the measurement process into a data analysis pipeline. In an ideal world, we would have access to the perfect detector: an apparatus that makes no error in measuring a desired quantity. However, in real life, detectors have finite resolutions, characteristic biases that cannot be eliminated, less than full detection efficiencies, and statistical and systematic uncertainties. By building a matrix that encodes a detector's smearing of the desired true quantity into the measured observable(s), a deconvolution can be performed that provides an estimate of the true variable. This deconvolution process is known as unfolding. The unfolding method implemented in PyUnfold accomplishes this deconvolution via an iterative procedure, providing results based on physical expectations of the desired quantity. Furthermore, tedious book-keeping for both statistical and systematic errors produces precise final uncertainty estimates.
fields
hep-ex 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Studies of Z $\to$ 4$\ell$ decays in proton-proton collisions at $\sqrt{s}$ = 8 and 13 TeV
Measured inclusive B(Z → 4ℓ) = 4.67 ± 0.21 × 10^{-6} with individual modes, differential distributions, and triple-product asymmetry limits.