1 / 16

WW workshop towards further Spin measurements

WW workshop towards further Spin measurements. Rosemarie Aben, Pamela Ferrari, Nikos Karastathis, Peter Kluit, Tatjana Lenz, Christian Schmidt, Doug Schouten, Manuela Venturi, Tuan Vu Anh WW workshop Sesimbra 30 November 2012. Introduction Measurement of Spin properties:.

cai
Download Presentation

WW workshop towards further Spin measurements

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. WW workshoptowards further Spin measurements Rosemarie Aben, Pamela Ferrari, Nikos Karastathis, Peter Kluit, Tatjana Lenz, Christian Schmidt, Doug Schouten, Manuela Venturi, Tuan Vu Anh WW workshop Sesimbra 30 November 2012

  2. Introduction Measurement of Spin properties: • Here I will discuss a few topics that are related to current and • future H->WW spin measurements. • Some topics deal with the cut based analysis, others are more • general. Here I will not present an overview of the analysis but • discuss questions like: • What can we measure? Can we improve the results and how? • Things we learned, topics we should further investigate. • Simulations and the inclusion of the 1 jet channel • Event Selection and Combination of Variables • Optimization of combination of Variables • The 2D space and binning • The stats framework

  3. Simulations and the 1 jet channel Skip slide already discussed Current results have only used the spin 2+ simulations in the 0 jet channel. Time has come to extend this to the following spin topics, here ordered in importance: - spin 0+ and 0- - spin 2- Some inconsistencies in JHU; under investigation - spin 1+/- Note that although H->γγ excludes spin 1 it is perfectly possible to have a spin 1 particle in this final state Concerning the 1 jet final state. Here we have a 10% contamination from VBF. For the cut based the event selection was already optimized and ready (in September see slide 6).

  4. Simulations and the 1 jet channel Although I was/am of the opinion that this is a rather small component, we now can obtain MAD Graph/MC at NLO spin 2+/- simulations that include higher orders. This means that the 1 jet channel can be included. Note that this only applies to spin 2. For spin 0- this is already available. What does this bring? 2+ has expected sensitivity of say 2σ inclusion of the 1 jet will go to 2.4σ. My proposal for Moriond would be to extend the measurements to include the 1 jet channel; spin 0, 1 and 2.

  5. Event Selection and….. - The spin analysis is statistics limited. This means that we are interested in getting the largest possible opposite flavor sample that is understood. - To avoid biases in the event selection we run with lowered Mll, Ptll and MET cuts. A one jet selection has been developed in the context of the cut based analysis. See next slide for the precise cut values. • For this analysis it is not optimal e.g. to reduce for the backgrounds (say W jets and Z tau tau) at the cost of efficiencies. A further tuning of the lepton isolation cuts is also not needed. Inclusion of the tagged muons e.g. one would gain ~10% efficiency, keeping same pT cuts. Needs some further fake factor studies.

  6. Event selection emu mue for 0 and 1 jet Concerning the 1 jet final state. Here we have a 10% contamination from VBF. Can this be further reduced?

  7. Combination of Variables • What did we learn on this topic? • For the BDT it was found to be optimal make two BDTs one for spin 0 against background and one for spin 2 • This comes from the fact that we have to do two things optimally: 1) Suppress background 2) Separate spin 0 from spin 2 • One can understand both for cut based and for a BDT analysis that it is a VERY different thing to suppress background and to separate spin by shapes • That is why both analyses converge on a 2D analysis • For the cut based 2 variables were selected: the boosted angle between the leptons and the so called boosted Esum variable = P llead+ Eνsublead –P lsublead/2 • This can be further optimized….

  8. Optimization of Variables • For the 2+ hypothesis the BDT and cut based analysis have a similar expected sensitivity/exclusion of about 2σ • The challenge for the 2-is the following • Current sensitivity for the BDT and cutbased using the same variables is: • Sensitivity is about 0.6-1.2σ • This should be further optimized…. • For the cut based it means studying the sensitive variables: use the boosted angles and energies and combine these • Similarly the spin 1 and 0 analyses should be optimized • True they are harder, but still we should try. • See next slide 9 for spin 0 CP odd and even separation (August 2012) • Two other roads: • An analysis with boosted variables with a different Mvv value • Combine boosted and BDT variables

  9. Example: Boosted variables spin 0CP odd and even Here the (sub) leading lepton and neutrino energies separate CP odd/even

  10. Optimization: boosted Variables with Mvv = 40 GeV • The boosted analysis uses a fixed value for Mvv • It was observed that Mvv= 30 GeV is optimal for a SM Higgs • However for a spin 2+ Mvv = 50 GeV seems optimal • Here a quick 2D analysis was done with a value of 40 GeV (Nikos provided the ntuples) • Sensitivity goes from 2σ to 2.1σ • Small improvement Spin 0+ Spin 2+

  11. Combine BDT and boosted Variablesand… rebinning • For the 2+ hypothesis the BDT a combination with Esum has been tried • Here one variant was tried out – one can think of others: • Making a BDT vs Esum 2D analysis • Sensitivity goes from 2σ to 1.8-2σ • Not an improvement; close to the optimal point for both analyses(?) A topic where we have to be carefull is ‘rebinning’. Here the boosted analysis is compared for 100 and 50 bins. Sensitivity goes from 2σ to 1.8σ. Because a shape fit is done one can loose performance… Note that this is pretty big sensitivity loss!

  12. 2D space and the Binning of variables • There are some issues with binning that we learnt • First, one should have no empty bins; and certainly no bin with signal and NO background. • Secondly, one should have enough background events to get a reasonable estimate of its value. Here typically e.g. 25 real background events per bin can be used. • Thirdly, one should check that the signal to background ratio is not fluctuating up to e.g. 0.5 (average is 0.1) • This provides important constraints on a sensible binning • Automatic code is available that makes a remapping: • first building from the 2D observables the S/B (40 bins) and Spin 0/Spin 2 (20 bins) variables • Then a mapping to a 1D variable is made (e.g. 100 bins cut based) • An example for the cut based analysis is shown on the next slide

  13. Remapping example Plots show data and fit for fixed spin 0 and 2 fits for the 50 bin fit results Further rebinning ‘lesson’: use a more coarse binning at low remapped values and keep fine binning at high values.

  14. Binning of variables and uncertainties • What happens if one does not respect these three criteria: • The fit crashes and/or gives nan values • The fit and the likelihood curve is not well-behaved • Here on the right a toy example where the likelihood shows anomalous behavior (at epsilon<0) - The sensitivities given are too good (to be true…) • Some remarks on error estimates: • Currently epsilon (spin 2 fraction) is constraint to the range 0 to 1 • Minos error estimation suffers from this constraint and the error on epsilon is then not correctly estimated • If the epsilon value is unbounded one can obtain a better error estimate • One can further check the compatibility of unconstraint epsilon with spin 0 as was proposed by Bill Murray • Marumi is right that the probability can also be obtained by integration • Think of quoting our basic physics result as the probability to be compatible with spin 0 and the exclusion of spin 2

  15. The stats framework • CPU use is relevant from the toy generation: • 50 bins works but we submit jobs with only 25 events on the grid • 100 bins is (above?) the limit because of CPU • Fortunately, Wouter will have a look and will try to speed this up • We have in principle two very valuable cross checks of the framework: • A full X-check using Tuan his framework (see talk in the workshop) • A fast check (‘fit_properties’ code) without full shape systematics • For spin the shapes are important, need more diagnostics. Here our ‘wishlist’: • Need functionality to plot residuals after the full fit • Might need more functionality like full Likelihood plot (epsilon) to spot anomalous behaviour • How can we perform fits leaving out (e.g. bkg) bins and constraints (without remaking the workspace)?

  16. Conclusions • In the above I listed some opportunities and problems • Simulations and the inclusion of the 1 jet channel • Event Selection and Combination of Variables • Optimization of combination of Variables • The 2D space and binning • The stats framework • Most important is to discuss them, agree on them and address them for the Moriond/Summer publication • In particular, to make a common workplan to solve them • We have a solid basis: the approved analysis • Keeping in mind the synergy and complementarity of the cut based and BDT analyses • Question from Marumi: impact of gg/qq polarisation pdfs on the spin 0 shapes and final result. Might need work.

More Related