Fast b tagging at L2

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B tagging meeting XX-XX-04. Fast b tagging at L2. Sascha Caron (NIKHEF). … using the Silicon Track Trigger (STT) Methods to do a very fast b tagging Some first results and a proposal for a L2 algorithm. Silicon Track Trigger. The STT is the. STT status. - PowerPoint PPT Presentation

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Fast b tagging at L2Fast b tagging at L2 B tagging meeting XX-XX-B tagging meeting XX-XX-0404

Sascha Caron (NIKHEF)

• … using the Silicon Track Trigger (STT)

• Methods to do a very fast b tagging

• Some first results and a proposal for a L2 algorithm

Sascha Caron (NIKHEF) 2

Silicon Track Trigger

• The STT is the

Sascha Caron (NIKHEF) 3

STT statusSTT status

• hardware installed, working and STT info is implemented in v13 test

trigger list• STT simulator agrees well with

hardware• STT output correlates well with D0

reconstruction

Time to think about using the STT improved L2 track information for b tagging

Sascha Caron (NIKHEF) 4

TrigsimTrigsim

• STT information for Monte Carlo events gained using a modified trigsim

t04.05.00 (with p17.01.00 STT routines) and trigsimcert to get the root tuple• Events used are the “usual” sets for b tagging Certification: QCD: pt>40 GeV file with 10000 events (id 8791) Z-> bb: 10000 events (id 8845) Z-> cc: 1000 events (id

Top-> all jets Z-> bb with 12 multiple interactions : 1000 events

Sascha Caron (NIKHEF) 5

Comparison STT simulation code and modified trigsim/trigsimcert

Agreementin the used variables(chi2, impact parameter significance)

Sascha Caron (NIKHEF) 6

ELIP method

Sascha Caron (NIKHEF) 7

ELIP method Pdf derived using Kernel estimation

Each sample pointis smeared by pulling10000 sample pointsout of a Gaussian witha width optimized asa function of S

Probability for a track to come from the vertex is justthe integral of thepdf from S to inf.

Sascha Caron (NIKHEF) 8

LM (likelihood method)• Derive probability density function of the track significance S for

signal (Z) and background (QCD) events• Use all “good” tracks with a scaled chi2<5• Idea : Store

R(S)=pdfSignal(S)/ pdfbackground(S)

in a lookup table for S (256 entries)

Loop over all “good” tracks i and derive the product of R

Derive a Likelihood as a descriminant:

Sascha Caron (NIKHEF) 9

LM: Kernel estimationLM: Kernel estimation

pdf using kernel estimationmethod with Gaussians

Sascha Caron (NIKHEF) 10

MULM method• Significance is heavily dependent on the goodness of the track fit • Goodness the track fit given by scaled chi2 (less pt dependent)Idea: Include chi2 information in discriminator

by using 2d p(S,chi2) pdfs

This degrades tracks with large chi2 while stillUsing the full information provided by the STT.

Sascha Caron (NIKHEF) 11

MULM

Sascha Caron (NIKHEF) 12

SummarySummary

High energy ep collisions at HERA are a unique testing ground for the SM

Various searches for new physics are performed (model independent and dedicated)

Some interesting events are found

… and HERA 2 has just started !