Kinematic Fitting for ParticleFlow Detectors at Future Higgs Factories

TL;DR

This paper demonstrates how particle flow techniques at future Higgs factories enhance kinematic fitting by providing detailed uncertainty estimates, improving mass reconstruction and particle separation in collider experiments.

Contribution

It introduces a method to derive detailed covariance matrices for particle-flow objects, improving kinematic fits and mass resolution at future Higgs factory detectors.

Findings

Enhanced invariant mass reconstruction of di-jet systems.

Improved separation of ZH and ZZ events.

Effective correction of neutrino missing momentum in heavy-flavor jets.

Abstract

In many analyses in Higgs, top and electroweak physics, the kinematic reconstruction of the final state is improved by constrained fits. This is a particularly powerful tool at $e^{+}e^{-}$ colliders, where the initial state four-momentum is known and can be employed to constrain the final state. A crucial ingredient to kinematic fitting is an accurate estimate of the measurement uncertainties, in particular for composed objects like jets. This contribution will show how the particle flow concept, which is a design-driver for most detectors proposed for future Higgs factories, can -- in addition to an excellent jet energy measurement -- provide detailed estimates of the covariance matrices for each individual particle-flow object (PFO) and each individual jet. Combined with information about leptons and secondary vertices in the jets, the kinematic fit enables to correct $b$- and $c$-jets for missing momentum from neutrinos from semi-leptonic heavy quark decays. The impact on the reconstruction of invariant di-jet masses and the resulting improvement in $ZH$ vs $ZZ$ separation will be presented, using the full simulation of the ILD detector, as an example of highly-granular ParticleFlow optimized detector concept.