Search for Randall-Sundrum Gravitons with 1 fb -1 of Data Amitabha Das

February 6, 2007Amitabha Das2  Theory  Detector  Analysis  Result OUTLINE

February 6, 2007Amitabha Das3 Standard Model  Quarks  Leptons Gluon - Mediator of strong force Photon - Mediator of electromagnetic force W  and Z 0 – Mediators of weak force

February 6, 2007Amitabha Das4 NOT a complete theory..  Higgs field is needed to generate mass  Higgs mass ~ W mass.  Try to include gravity – Drives up the higgs mass Gravitational force much weaker than other forces in nature. “ Hierarchy Problem ”

February 6, 2007Amitabha Das5 Solution ??  New mechanism where the higgs mass doesn’t go up in Planck scale OR  The fundamental Plack scale is not so big. Theories based on the idea of extra dimension try to look into the second possibility.

February 6, 2007Amitabha Das6  One extra dimension in addition to the (1+3)-dimensional space-time.  There are two branes embedded in this five-dimensional bulk.  Visible brane : Contains the Standard model fields  Invisible brane : Only gravitational field can propagate to this brane. Randall-Sundrum Model Lisa Randall and Raman Sundrum, Phys. Rev. Lett. 83, 3370 (1999)

February 6, 2007Amitabha Das7 Visible brane Contain SM field. Gravity is weak. Invisible brane Gravity is strong.  Fundamentally gravitational force is strong.  Wave function exponentially suppressed away from the invisible (Planck) brane. Exponentially suppressed

February 6, 2007Amitabha Das8 Phenomenology How we search for gravitons  Graviton – Mediator of gravitational force.  Theory predicts graviton decays to fermion or boson pair  We look for excited graviton through the final states :

February 6, 2007Amitabha Das9 Free Parameters  In RS Model there are two free parameters : 1.Mass of the excited state of Graviton M 1 2.Coupling to standard model field k√8  /M Pl to 0.1

February 6, 2007Amitabha Das10 DO Detector at Fermilab

February 6, 2007Amitabha Das11 Calorimeters Tracker Muon System Beamline Shielding Electronics protons 20 m Tracker Calorimeter Anti-proton

February 6, 2007Amitabha Das12 Tracking System  Track reconstruction of the charged particles.  Silicon Tracker  Fiber Tracker  Calculates the momentum of the charged particle.  Solenoidal magnetic field

February 6, 2007Amitabha Das13 Silicon Microstrip Tracker (SMT) and Central Fiber Tracker (CFT)  CFT together with SMT enables track reconstruction of the charged particles.  Whole tracker inside a 2T magnetic field.  Measure the momentum from the curvature of the charged particle.

February 6, 2007Amitabha Das14 Calorimeter  Measurement of particle energy and particle Identification.

February 6, 2007Amitabha Das15 D0 Trigger System

February 6, 2007Amitabha Das16 D0 Trigger System Silicon Track Trigger (STT) No STT trigger used in this analysis.

February 6, 2007Amitabha Das17 Idea behind STT  Main Goal – Fast selection of events with ‘b’ quarks.  Selecting tracks with large Impact Parameter.

February 6, 2007Amitabha Das18 STT Conceptual Schematic Cluster CFT Data SMT Data Fiber Road Card Silicon Trigger Card Hits Track Fit Card Road Silicon Trigger Card (STC) Makes clusters using the SMT. Using “road” data get the clusters within road : Hits. To L2 Road

February 6, 2007Amitabha Das19 STT Crate Layout

February 6, 2007Amitabha Das20 STT Mother Board

February 6, 2007Amitabha Das21 Six STT Sector Crates

February 6, 2007Amitabha Das22 Performance of STT  STT trigger included in the D0 trigger list since Summer Efficiency How well STT tracks match with offline reconstructed tracks. (The D0 Run II Impact Parameter Trigger, physics/ )

February 6, 2007Amitabha Das23 Definitions

February 6, 2007Amitabha Das24  Pseudo-rapidity

February 6, 2007Amitabha Das25 Transverse Momentum

February 6, 2007Amitabha Das26 Integrated Luminosity  Instantaneous luminosity : Number of interaction per unit cross-section, per unit time  Integrated luminosity : Integrate over a period of time Unit : 1/cross-section L integrated x Cross-section = Number of events

February 6, 2007Amitabha Das27 ObjectIdentification

February 6, 2007Amitabha Das28 Electron and Photon Identification Electrons and photons deposit most of their energy in the electromagnetic (EM) calorimeter 1.Identify a region in the EM calorimeter with high energy deposition 2.Several variables to characterize a shower originating from an electron or photon

February 6, 2007Amitabha Das29 Some of the variables … 1.What fraction of the total energy is deposited in the electromagnetic calorimeter region. 2.In an event with electron or photon as final state, they should be isolated from other particles, a measure of, by how much the electrons or photons are isolated. 3.Shower shape : A shower originating from electrons or photons is narrow and does NOT penetrate deep in the calorimeter compared to a shower originating from other particles.

Analysis

February 6, 2007Amitabha Das31 Data :  Data used for this analysis was taken between Oct and Feb Monte Carlo (Simulation) :  Simulated events were used for background prediction and signal efficiency.  All the events were generated using PYTHIA

February 6, 2007Amitabha Das32 Graviton Mass  (LO) No. of events generated 200 GeV28.7 pb GeV20.2 pb GeV0.34 pb GeV0.12 pb GeV0.041 pb GeV0.015 pb GeV0.005 pb1000 Invariant Mass  (LO) No. of events generated GeV188 pb GeV1.3 pb GeV0.10 pb27000 >500 GeV0.004 pb25000 Invariant Mass  (LO) No. of events generated GeV29 pb GeV1.0 pb GeV0.11 pb2000 >500 GeV0.01 pb3000 Monte Carlo (MC) Samples Signal (graviton) MC Drell-Yan MC Direct diphoton MC

February 6, 2007Amitabha Das33 DATA Event Selection Signal + Background Estimate Background Excess Signal No Excess DISCOVERY Set Upper Limit of cross-section at 95% confidence level

February 6, 2007Amitabha Das34 Event Selection Final state : e + e - and gamma gamma  Events having two electromagnetic (EM) objects  Both the EM objects should be in the central calorimeter region  < 1.1.  Require both the EM object to have  Transverse momentum : p T > 25 GeV  In addition some quality cuts were applied. Do not distinguish between electron and photon

February 6, 2007Amitabha Das35 Sources of Background  Standard model background :  Drell-Yan  Direct diphoton Estimate contribution : Use simulated events  Instrumental Background :  Misidentified electromagnetic objects Estimate contribution : Get sample rich in misidentified electromagnetic object from data by applying reverse quality cuts

February 6, 2007Amitabha Das36 Background Estimation Step 1 : Fit the invariant mass spectra at low mass region N SM = Invariant mass spectra from Drell-Yan + Diphoton N QCD = Invariant mass spectra from instrumental background  Invariant Mass Spectra : Calculate the invariant mass for the events which pass the “Event Selection” cuts

February 6, 2007Amitabha Das37 Data = W + (1-W) Instrumental background. Standard Model background. Get the weight “W” corresponding to the best fit Fit region

February 6, 2007Amitabha Das38 Fit at Low Mass

February 6, 2007Amitabha Das39 Step 2 : Apply the weight ‘W’ to the full mass spectra

February 6, 2007Amitabha Das40 How a signal would look like … 350 GeV 600 GeV 900 GeV

February 6, 2007Amitabha Das41 DATA Event Selection Signal + Background Estimate Background Excess Signal No Excess DISCOVERY Set Upper Limit of cross-section at 95% confidence level

February 6, 2007Amitabha Das42 Set 95% Confidence Limit Total probability of having cross-section <  Upper is 95%

February 6, 2007Amitabha Das43 Calculating upper limit of Signal cross-section (  u ) at 95% confidence limit The number of observed events N is given by: N = b +  L b=background  =cross-section  = efficiency L = Integrated luminosity  P(A | B) = Probability of proposition A when proposition B is true.   (x | B) = Probability of the continuous variable between x and x+dx when proposition B is true. Probability density.

February 6, 2007Amitabha Das44  The upper limit (  u ) at 95% CL is defined as: I – All prior information k - No. of observed events  If we know  (  |k,I) then the solution of the above integration gives the upper limit at 95% confidence level.

February 6, 2007Amitabha Das45 LimitCalculator Data Background +/- Err Efficiency +/- Err Luminosity +/- Err Upper Limit Inputs for the limit calculator

February 6, 2007Amitabha Das46 Calculate Integrated Luminosity  From normalized background spectra - Get number of Drell-Yan events, N =  The drell-yan cross-section is 254 +/- 10 pb R. Hamberg, W. L. Van Neerven, and T. Matsura, Nucl. Phys. B359, 343 (1991)  Get luminosity = 1.1 +/ fb -1

February 6, 2007Amitabha Das47 Mass Window Get Data and Background  Data: N = No. of events in a mass window  Background: B = Total background in same mass window

February 6, 2007Amitabha Das48  Signal Efficiency  N = Number of RS Graviton Monte Carlo events for a given mass  n = Number of events that pass selection cuts + mass window cut Uncertainties PRL 95, Uncertainty on background ~ 9% Uncertainty on efficiency ~ 10%

February 6, 2007Amitabha Das49  We set upper limit on cross-section for :  It is found :  Quoting limit for :

February 6, 2007Amitabha Das50 N = 0 b = / L = 1.1 fb -1  = / Example: M=900 GeV

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February 6, 2007Amitabha Das54 Preliminary Result ICHEP 2006 At 95% Confidence Level Graviton Mass < 865 GeV excluded for coupling 0.1 Graviton Mass < 240 GeV excluded for coupling 0.01 Graviton Mass < 240 GeV excluded for coupling 0.01

February 6, 2007Amitabha Das55 Thank You

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February 6, 2007Amitabha Das57