Les Houches

• Graph of fraction of negative weights for Higgs processes/background (slide 5/9 Jeppe talk)
• Discussion on good metrics (what to compare before considering events close)
• Measure the impact on reals vs virtuals, which events are most likely to be altered and by how much?
• Try it on proper experimental samples (what metric is good, what issues arise?)
• Applying this to NNLO (e.g. HighTea samples)
• Try e.g. jpsi→leptons something very narrow (technical issues regarding IR sensitivity, modifying distributions…)
• Plots of mean/median/width of the cell resampling bins, studying these distributions and their potential impact
• Can narrow weight distribution for more efficient event unweighting

• q: why is w+5 improving more than z+3?

1. initial event sample size? (no, both have 1e9)
2. dipole cut vs improvement? (check dipole cut used)

- q: calculating density of events to “pre-check” that this algorithm may work?

- q: metric needs to be compatible with how ps generator is populating ps, proof that this is not biasing anything? - q: should there be a bias towards positive values (since you iteratively add nearest event until wi>=0)?

• ps generator dependent because this alters which events are clustered, can this have an impact on the physics?

- q: plotting statistical uncertainties on the original sample

• more easily allows verifying that differences are within statistical uncertainty

- q: on which type of event does this have the biggest impact?

• imagine reals are more impacted than virtual
• we were completely agnostic

- q: can we really prove that this does not alter distributions? (prove that you preserve distributional structure of the observables you compute)

• we do not alter any of the event kinematics
• there is no cross talk of events separated by more than the maximum allowed distance
• IRC safe measure important, but this is not a sufficient condition, can you reproduce infrared sensitive observables (e.g. Sudakov shoulder, 0-bin of ptZ), can your smearing reproduce this feature in the limit that the smearing goes to 0?

- q: mean/median/width of the cell resampling bins

• we have plots which we can examine

• Apply cell resampling (paper 1 paper 2 source binaries) to Higgs signal/background (closure tests, measure of simplification e.g. #event reduction)

• di-photon NLO sample (m_gamgam centred around Higgs mass window)