ErrorFlow: Jet Error Estimation for Kinematic Fitting in Particle Flow Detectors at Future Higgs Factories

Constrained fits improve the kinematic reconstruction of the final state in many Higgs, top and electroweak physics studies. This is a powerful tool, particularly at $e^{+}e^{-}$ colliders where the initial state four-momentum is known and can be employed to constrain the final state. An accurate estimate of the measurement uncertainties, particularly for composed objects like jets, is a crucial ingredient to kinematic fitting. Detectors optimized for particle-flow reconstruction provide a detailed estimation of the covariance matrices for individual particle flow objects in addition to an excellent four-momentum measurement. These can be combined to derive an estimate of the individual covariance matrix of the four-momentum of each jet by an algorithm called ErrorFlow. This contribution will present the improvements by the application of ErrorFlow in the $ZH$ versus $ZZ$ separation at $\sqrt{s}=250$ GeV, using the full simulation of the International Large Detector as an example of a highly-granular ParticleFlow optimized detector concept