1 / 21

Realistic MC Needs/Status

Realistic MC Needs/Status. Mike Hildreth Universit é de Notre Dame du Lac Representing the Full Simulation Group with Charles Plager UCLA/FNAL. Philosophic Overview. Full Simulation: should include all details relevant for physics analysis

varick
Download Presentation

Realistic MC Needs/Status

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. Realistic MC Needs/Status Mike Hildreth Université de Notre Dame du Lac Representing the Full Simulation Group with Charles Plager UCLA/FNAL Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  2. Philosophic Overview • Full Simulation: should include all details relevant for physics analysis • accurate representation of interaction of particles with detector • tails on resolution distributions from all known effects • to the extent that these tails/effects are important… • including noise, pileup, geometry, sensitivity, etc. • Because we can make the simulation perfect doesn’t mean we should • currently victims of our own hard work/success • when things look “too good”, analysts will expect perfection • in reality, it will never be perfect • some a posteriori corrections will always be necessary will need to plan for implementation of these corrections • Goal: reduce the size of necessary corrections and the associated errors so that they have minimal impact on physics • implies improvements to Simulation if needed • needs to be “good enough” Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  3. Talk Overview The 64M Lira Question: “What is ‘Good Enough’?” • Right now, we don’t know the answer... • Here, review strategies for achieving Data/MC agreement, look at advantages/disadvantages of each approach • Run-Dependent Monte Carlo • Technical Readiness • Possible Implementation Scenarios • Data Recovery Test • Event Re-Weighting (or “Run-Independent” MC) • Overview of Techniques • Examples Emphasize: Studies needed to arrive at MC Production Strategy Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  4. Realistic MC • Definition of “Realistic MC”: • IOV-based (= run-number based) • uses DB to control live/dead channels, calibrations, etc. • Realistic “Conditions” • beam spot in correct position for a given run • pileup distribution matches • “Realistic” Detector Geometry • mis-alignments/smeared geometry matching the real detector • NOT: completelyrealistic trigger simulation • Offline L1 Triggers do not exactly match what was run online • (Manpower needed here from subdetectors) • One proposal: Create MC samples with a run distribution that statistically samples all Data runs with proper luminosity distribution • Note: this implies IOV-dependence of all conditions for all objects is known before doing a Redigi-ReReco MC step – acceptable delay? Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  5. Status of Necessary Pieces (I) • Run-number setting (√) • Simulation/Framework allows the specification of arbitrary lists of runs, each with a probability weight, to assign run numbers for Generation • set before SIM step • Run-number dependent code in Sim Packages (√) • All subdetectors have code that reads conditions from the DB for simulation of masked/dead channels • can easily be made run-dependent by assigning IOVs • Beam Spot from DB (X) • under discussion with experts to evaluate time scale • not complicated, could be done quickly • not absolutely necessary for first validations • must be set before SIM step, matching Run number  any changes require re-Sim ( = expensive) Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  6. Status of Necessary Pieces (II) • Arbitrary Pileup Distributions (√) • currently, distributions must be put in “by hand” • either a root file or a list of numbers • reading from the DB would obviously be better • another relatively quick project • actual distributions will have to be measured • correspondence number of vertices with true number of interactions, for example • Dedicated pileup studies needed • Geometry (X) • “Large” movements, such as mis-centering of pixels with respect to Silicon Tracker, beampipe, (Ecal?) will be put in Geant geometry (CMSSW_3_10?) • studies ongoing to determine optimal procedure to include shifts • Geometry DB would allow use of new and old samples Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  7. Realistic Conditions? A couple of items missing from previous discussion: • Beam Backgrounds • may be time-dependent • should be taken directly from data if necessary • we don’t know what the impacts are on analysis yet • Asynchronous HPD noise in Hcal • Request (plan?) for Hcal to use data in simulation as default • Thermal neutrons in cavern • simulation plan evolving; may be difficult to get right • All these may be easiest using DataMixer • Not clear if such detail is necessary... Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  8. Comments on DataMixer Some attractive attributes: • Backgrounds, multiple interactions, detector noise, etc. are automatically “correct” if samples are properly formulated • no incorrect physics model of low-pT interactions • taken directly from Nature • Overlay is done at Digi level, so can be re-done without excessive computation But: it is the ultimate run-dependent MC • beamspots must match between simulated and overlay events • zerobias samples will need to be constructed before MC production representing a given time period can start • some care necessary to make sure IOVs are correct for MC Need Pileup Studies (Data/MC comparisons) to know whether or not (or at what level) we need to use data overlay Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  9. “Data Recovery” Test • Working with DPGs, we will generate run-dependent MC for some runs that are currently declared “BAD” due to hardware problems • use DB to kill MC hits in channels that are off • (will have to watch load on DPGs if this becomes routine) • e.g.: Tracker power supply failure • DPGs/POGs will check MC/Data agreement for these epochs • “Good” agreement between Data and MC may allow the “recovery” of some data with minor problems, since MC will correctly simulate degradation  Same json file for Data & MC Gordon Kaußen Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  10. Reweighting Techniques • Almost all physics analyses will not be able to use “straight” MC, but instead will need to apply correction factors (i.e., “scale factors”) or efficiencies to correct for MC/Data disagreement • In some very simple cases, these may be able to be applied after running over the MC samples. • e.g., electron reconstruction efficiency/scale factor that is independent of the electron kinematics for a single electron analysis. • In many (most?) cases, it is either necessary or much easier to apply these corrections/efficiencies while running over the MC. E.g. • Electron efficiency/scale factor that is not independent of kinematics. • Electron efficiencies for multi-electron analyses. • B-tagging efficiencies depending on jet kinematics • Jet energy corrections • etc. Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  11. Reweighting Techniques • Sample from Monte Carlo generated with various conditions to build a MC analysis dataset equivalent to the Data • different “correction factors” for different data epochs • Can make use of constants stored in the Performance DB (PerfDB) and IOVs • MC sample must supply run & luminosity information to PerfDB to obtain appropriate correction factors • distribution of runs matches Data • caveat: often, have to worry about changing conditions for more than one object (i.e., b-tagging, electron efficiencies, etc.) • overlapping IOVs have to be treated correctly, e.g.: relative weights given by integrated lumi • Run number:        1 2 3   4  5  6  7  8   9   10 • B tag efficiency IOVs: • Electron efficiency IOVs: • Total IOVs modeled in MC:  A B C Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  12. Making Generic MC Run-Dependent • General idea: • Query the PerfDB about the different IOVs for the quantities in which we are interested. • Get luminosity profile for data in which we are interested. • Calculate intersection of data luminosity and IOV lists. • When running over MC, a run-lumituple will be generated for each event such that the different IOVs will be represented in the correct fraction as dictated by the data. • Complete tools would/will be provided that work both in cmsRun and FWLite • central solution, not 40 different ones… • Reweighting will be necessary whether or not we have Run-Dependent MC – tools should be centrally developed • some already available, coordinate with Analysis Tools? manpower? Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  13. Luminosity Reweighting • For first pass, assume we only need to worry about number of pile up interactions. • General idea: • Split data into IOVs as previously discussed • For each data IOV, convert luminosity profile into distribution of expected number of pile-up interactions. • This depends on bunch structure at LHC and not just instantaneous luminosity. • also will have to worry about out-of-time pileup… • Get expected number of pile-up interactions summed over all data IOVs (i.e., sum up distributions from step 2 above). • For MC sample, get distribution of pile-up interactions. • For each MC event, given its number of pile-up interactions, weight event based on pileup distributions and pick IOV based on distributions of the number of pileup interactions to match overall Data distribution Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  14. Quick Aside: Pileup at CMS • We now have all of the tools in place to estimate pileup at CMS. • Data/Prediction agree well: circulation rate Predicted vs. Measured Primary Verticies Data (lum. weighted zero bias data) Predicted (Instantaneous luminosity information convolved with MC minimum bias vertex efficiency) Charles Plager Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  15. Example of Luminosity Reweighting • Take a Tevatron sample as an example Unnormalized weights  Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  16. Example of Luminosity Reweighting • A MC event with one pileup interaction: is much more likely to come from early data, use this IOV ratio (early/late) for conditions use this weight Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  17. Example of Luminosity Reweighting • A MC event with 6 pileup interactions: is equally likely to come from early or late data, use this IOV ratio (early/late) for conditions use this weight Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  18. Reweighting Redux • Requires no knowledge of detector conditions for MC generation • if reweighting is sufficient for run-dependence • potentially faster turn-around for physics analysis • Adaptable to most corrections for MC/Data agreement • However, requires most corrections to be in the form of scale factors, not something more subtle • Widely used • will be necessary to correct for residual MC/Data disagreement • e.g., deficiencies in generators, if nothing else • Will put quite some strain on Performance DB • may need careful design considerations, light payloads Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  19. Back to Run-Dependent MC • Do we need it? • Questions to answer: (not a complete list) • Do we have “epochs” of dramatically different detector performance that have impacts on physics? • either large correction factors or different simulation • can we recover “BAD” data with proper simulation • How much does beam spot motion affect • tracking efficiency? • tracking errors  B-tagging efficiency? • NB: beam spot motion cannot be re-done at Digi time • What are the effects of beam backgrounds on physics, and do they vary in time in a way that should be modeled? • same for neutrons in cavern • Are there significant differences in pileup distributions between Data and MC that we cannot simulate by modifying MC parameters? • what about degradation of detector over time? Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  20. Back to Run-Dependent MC • Do we need it? • Will need to explore both weighting and Run-Dependent options to decide what mix is necessary • implies efforts from Physics, POGs, DPGs to study issues () • close coordination with simulation effort • In particular, we now have sufficient quantities of events with large numbers of interactions in a single beam crossing • need to have matching MC samples to make thorough comparison studies: • Can we simulate pileup, or should we use data instead? • need some sort of Pileup Study Group to coordinate • again, close coordination between Physics and Simulation/Generators () • plan meeting series or small workshop to study issues Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

  21. Conclusions • MC will never be perfect • Reweighting tools will be necessary and should be centrally developed • Studies needed to determine how perfect a MC is necessary • quite broad in scope • pileup • efficiency epochs • beamspot effects • need central coordination • Technically, Run-Dependent MC is possible ~now • some small updates needed • validation needed  Help from POGs/PAGs/DPGs needed! Mike Hildreth/Charles Plager – CMS Physics Week, Bodrum

More Related