Overview of Terry’s 2019

Terry Wyatt. Manchester Christmas Meeting, 2019. Current PhD students

• Sam Dysch: search for τ-lepton universality violation in W decays – Target precision ~1.5% for Run 2 data set (c.f. LEP-combined: 6.5%)

• Diego Barón: τ-lepton identification at high pT • Lewis Higgins: Football (co-supervised with Tobias Galla) – EPSRC CASE – co-funded with Man.City)

• Plus MPhys students (fysics and phootball) • Plus 10 fb-1 of 13 TeV ATLAS data in the 3rd year UG teaching lab. – First evidence for Higgs to 4-leptons in the 3rd year lab.!

2 Football • Data available: every game in 2016, 2017, 2018 and current premier league seasons • Technical work on datasets (in close collaboration with City expert) • Store in a consistent fashion data from different sources: position of players and ball, ball possession, game events • Now in a position to repeat/combine/extend studies previously performed as part of MPhys/summer projects Figure 7.14: Premier League 2017 - Optimised tiles on a per match basis. Velocity distorted, nearest player. Spatial Control: Voronoi regions boosted by player Correlation between “expected velocity and including consideration goals” and ”spatial control” of contested space

3 Figure 7.11: Diagram of the pixels created by the distorted Voronoi definition combined with the contested pixels (nearest home, nearest away) model.

The distortedFigure Voronoi 7.15: model Premiercan be used League to modify 2018the standard - Optimised definition of tiles the Voronoi on a (nearest per match basis. Velocity distorted, nearest player. player by time, rather than distance) - figure 7.10 is an example of this. Since distorting the cells only requires redefining how me measure the nearest player, the idea can also be applied to the contested control idea. The quickest home and away player to a pixel split the control according to their time to arrive. This idea is illustrated in figure 7.11. The distorted Voronoi model requires two parameters which alters the e↵ect of the distortion. These are the maximum velocity of the players vmax, and player acceleration a. These values should be sensible for professional athletes. The values used for the moment are a = 250 cm s 2 and v = 1000 cm s 1. · max · Ideally, they would be measured individually for each player to improve the accuracy of the model. This would reward quicker players by acknowledging their ability to arrive faster than the average player. It would be great to refine the model to even account for fatigue as the match continues - a player that is substituted later into the match would likely outrun the more fatigued players.

35 33 Points vs. fraction of Angular control “aggressive” passes (MPhys students: Jeremy Worsfold and Elliot Stapley)

Points vs. pass completion in ”safe” region

4 Other stuff in 2018: • Member of Editorial Boards for European Physical Journal C and Progress of Theoretical and Experimental Physics • Member of UKRI-STFC Advisory Panel on Evaluation of Value to UK of Membership of CERN • still ….. Member of Royal Society contact group on Brexit ….. sigh!

Plans for 2019: • Continue analysis of ATLAS data …. discover new physics in Run 2 …. or at least expose the old physics to as much stress as possible! …. and continue striving not to become a Former Research Scientist

5 Looking a bit further backwards

Time Manner Place Personal

40 years ago TASSO experiment Oxford and DESY Started DPhil (1979)

35 years ago UA1 experiment CERN CERN fellowship (1984)

30 years ago LEP starts! CERN (Manchester PPARC Advanced (1989) OPAL experiment :-) fellowship

20 years ago IC/Manchester join , Readership (1999) DØ experiment

15 years ago Elected as DØ Still Tevatron Professorship (2004) spokesperson First son born

6 7