1 / 6

Initial Physics and Plans for CMS

Matthew Jones (associate professor) David Silvers (graduate student – supported by NSF CAREER award). Early physics results ϒ production properties overlaps with CDF physics program Detector characterization using available data Absolute track reconstruction efficiency

amma
Download Presentation

Initial Physics and Plans for CMS

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. Matthew Jones (associate professor) David Silvers (graduate student – supported by NSF CAREER award) Early physics results ϒ production properties overlaps with CDF physics program Detector characterization using available data Absolute track reconstruction efficiency Longer term interests Trigger hardware upgrade Initial Physics and Plans for CMS http://www.physics.purdue.edu/~mjones/talks/mjones_cms_Aug_2010.ppt 2010 DOE virtual site visit

  2. Physics Context • Involvement in CMS physics program is a natural extension of CDF interests: • Small data samples, but large cross sections. • Interesting physics questions that merit further investigation. • Extended rapidity coverage alone is very useful. • Analysis of muonic final states form a coherent effort at Purdue. • Purdue involvement has already influenced the structure of CMS analyses: strong emphasis on proven experimental techniques developed at CDF. 2010 DOE virtual site visit

  3. Track Reconstruction Efficiency • Motivated by analysis which was patterned after the CDF J/ψ cross section measurement. • Allows muon/selection efficiencies to be determined using data rather than based entirely on Monte Carlo • Define muon selection/reconstruction efficiencies relative to tracking efficiency • Measure track reconstruction efficiency by embedding simulated hits in data events • Precision not limited by available statistics • Non-trivial interface with event data model • General interest in CMS, but in particular from the heavy ion group: very difficult to measure in any other way. 2010 DOE virtual site visit

  4. Example from Track Embedding Analysis • Results from CMS AN-2010/209 and public TRK-10-002: • Tracking acceptance is well modeled by detector simulation. • Efficiency is high, but not accurately described by the simulation. • Differences may become increasingly important at high luminosity • Suggest sensitivity to local activity, ie. proximity to jets • This powerful framework allows detailed studies of these effects. • Complementary to other estimates of tracking efficiency which average over wide ranges of kinematic variables. • These results used to support a variety of analyses presented at ICHEP, but in particular were used directly in ϒ cross section measurement. Monte Carlo Data 2010 DOE virtual site visit

  5. Longer Term Interests • Prior experience operating CDF at high instantaneous luminosity, L1/L2 hardware upgrades. • Infrastructure in place at Purdue for design and production of contemporary electronics systems. • Currently capitalizing on availability of good students from department of Electrical and Computer Engineering. • Interested in hardware development for extending L1 trigger capability at CMS. • Currently supported by NSF award, but overlaps with commitments to DOE. 2010 DOE virtual site visit

  6. Example from Pixel Jet Trigger Studies • Construct Level-1 trigger primitives from sensors in barrel pixel detector: • Identify jets, measure η, φ and z-vertex position: achievable resolutions well matched to calorimeter segmentation. • Provide z-vertex position information to L1 calorimeter trigger • Controls rate of multi-jet triggers when multiple interactions per bunch crossing. • Studies performed using emulation of “implementable” hardware: • Fast pattern recognition in FPGA’s • Bandwidth constraints on existing fibers • Results presented at CMS upgrade workshop, October 2009. • However: • Currently unclear how this would fit in with upgrade efforts. • Strong support from Wisconsin, Fermilab: provides a way to learn about advanced trigger hardware before it becomes essential for CMS operations. • Less strong support from PSI: Why can’t we just increase jet trigger thresholds to control rates? • Long term plan must evolve with the evolving constraints on CMS upgrade efforts. 2010 DOE virtual site visit

More Related