Off-shell Higgs Couplings in $H^*\to ZZ\to \ell\ell\nu\nu$

TL;DR

This paper investigates the potential to detect new physics through off-shell Higgs boson measurements at the high-luminosity LHC, utilizing machine learning to enhance sensitivity to various new physics parameters.

Contribution

It introduces a novel analysis combining machine learning with off-shell Higgs measurements to improve sensitivity to new physics in the Higgs sector at the LHC.

Findings

Enhanced sensitivity to Higgs width and EFT parameters.

Effective discrimination of new physics scenarios.

Significant improvement over previous methods.

Abstract

We explore the new physics reach for the off-shell Higgs boson measurement in the ${pp \to H^* \rightarrow Z(\ell^{+}\ell^{-})Z(\nu\bar{\nu})}$ channel at the high-luminosity LHC. The new physics sensitivity is parametrized in terms of the Higgs boson width, effective field theory framework, and a non-local Higgs-top coupling form factor. Adopting Machine-learning techniques, we demonstrate that the combination of a large signal rate and a precise phenomenological probe for the process energy scale, due to the transverse $ZZ$ mass, leads to significant sensitivities beyond the existing results in the literature for the new physics scenarios considered.