Transcript Slide 1

MR draft
SUSY Hadronic/GMSB Meeting 26-08-10
Christopher Rogan
California Institute of Technology
The Search for SUSY
 Here we re-introduce a new set of variables for a fully-inclusive SUSY
search:
 See talks in: SUSY meeting 6-5-2010, HWW meeting 28-5-10 or
 backup slides or
 arXiv:1006.2727v1 [hep-ph]
Log(N)
Log(N)
 In general, an analysis using these variables, relative to a canonical
SUSY search looking in a MET/MHT/HT tail for an excess:
 Yields higher signal efficiency w.r.t. the inclusive SUSY x-section
 More control over background distributions
 Distinctive signature: tail search becomes bump hunt
SIG
x
SIG SIG
x’
Christopher Rogan - SUSY All Hadronic/GMSB Meeting 26-08-10
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Kinematic Variables for SUSY
 Two variables designed to be used together for discovery 
and characterization of SUSY
arXiv:1006.2727v1 [hep-ph]
 Doesn’t involve MET
 Uses both transverse and
longitudinal information
 Invariant under long. boosts
 Peaks for signal:
 Dimension-less variable used for S/B discrimination
 Not only suppresses backgrounds, but also shapes their
distributions in the variable
in a predictable and wellunderstood way - the Razor
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Selection/Sample Details
 For everything shown in this talk:
 7 TeV MC (see back-up slide for list of samples)
 7 TeV Data (up to run 140387 right now ~318 nb-1)
 OR of HT200 and Jet110 triggers (for the moment)
 PF MET used (tcMET or corrected caloMET fine too)
 Require di-jets satisfying (parallel analyses):
Corrected Calo jets
Loose jet ID
Corrected PF jets
Loose jet ID
Uncorrected Track jets
Only high quality tracks
w/ vertex consistent
with reco PV considered
for clustering
 NO explicit lepton/photon reco or ID in constructing these variables
 If > 2 reco jets, form two hemispheres by minimizing invariant masses
added in quadrature (see back-up slides)
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PF jets
The Razor in practice
LM1 MC
QCD MC
(ALPGEN)
 Cut on R gives many orders of magnitude
suppression of QCD background
 More importantly, cut on R dictates the
shape of the surviving background events
(QCD and others) in the variable MR (see
next slide)
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PF jets
The Razor and MR
DATA behaves as
expected
Backgrounds fall ~exponentially after exceeding relevant scale (set by process
scale+trigger/reco
requirements) - slope set by R cut
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MC Search Expectations
PF Jet Analysis
Normalized to 10 pb-1
Here, LM1 + largest bkgs
There are two exclusive
classes of events analogous variables to R
and MR defined also in the
“primed” case (see
arXiv:1006.2727v1 [hep-ph])
See back-up for all signal and bkg tables
 Assuming reasonable precision for bkg
estimates (see following slides) we
should be sensitive to LM1 with ~10 pb-1
in PF jet analysis
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MC Search Expectations
Calo Jet Analysis
Normalized to 10 pb-1
Here, LM1 + largest bkgs
See back-up for all signal and bkg tables
 Assuming reasonable precision for bkg
estimates (see following slides) we
should be sensitive to LM1 with ~10 pb-1
in Calo jet analysis
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MC Search Expectations
Track Jet Analysis
Normalized to 10 pb-1
Here, LM1 + largest bkgs
See back-up for all signal and bkg tables
 Assuming reasonable precision for bkg
estimates (see following slides) we
should be sensitive to LM1 with ~10 pb-1
in Track jet analysis
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Towards Background Estimations
 To zero-th order, we can use low MR
region to predict high MR background
yield
 Can even go further by defining
mutually exclusive “boxes” defined
using lepton ID/tracker isolation
(independent of definition of MR and R)
 As of now, 9 exclusive boxes:
Two  at least one ISO
One e, one  ISO
One  ISO
Two e
Other
Two , no ISO
One e, one  non-ISO
One  non-ISO
One e
 For a given bkg type, exponential
slope in MR the same in each box
(physics object final state independent)
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Towards Backgrounds Estimations
 Using a loose R-cuts we
have a QCD dominated
sample which we can use to
measure the QCD slope, as
a function of R-cut, in the
low MR region
 Can do this in any box with
QCD population in low MR
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Towards Backgrounds Estimations
 Using a loose R-cuts we
have W+jets dominated
samples (single lepton
boxes) which we can use to
measure the W slope, as a
function of R-cut, in the
medium MR region (range
depending on R-cut)
 Can do this in several
different boxes, with several
different R-cuts
 MC predicts same
exponential slope for
W/Z/top+X - don’t need to
assume this though
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Towards Backgrounds Estimations
 Using a loose R-cuts we
have top dominated samples
(opposite flavor lepton
boxes) which we can use to
measure the ttbar slope, as a
function of R-cut, in the
medium MR region (range
depending on R-cut)
 Can do this in different
boxes, with several different
R-cuts
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Discovery Potential
3 Observation
5 Discovery
Here, we look at estimated sensitivity for a PF Jets based search, doing a
counting experiment and estimating systematic uncertainty assuming ratios of
events in control regions to signal region (conservative estimate)
Sensitivity comparable for each jet type considered
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Outlook
 SUSY search using variables MR and R appears to have good potential for
SUSY discovery -
 Simple analysis defined in a fully inclusive way (with variables that are
independent of certain topological considerations)
 Construction of variables allows us to control background shapes - can
easily evolve analysis as a function of integrated luminosity
 Work on background estimation techniques underway - with mutually
exlusive box definitions we will be able to over-constrain the relevant
backgrounds
 Immediate TODO:
 Analysis note nearly complete
 Additional jet types and MET types also (JPT, uncorrected jets, calo MET,
tcMET) to be added for parallel analyses/cross-checks
 Analyze full available data-set
 Sensitivity estimations to be updated with “final” analysis when converged
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BACK-UP SLIDES
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SUSY dijets
 Let’s consider a SUSY di-jet final state topology where two squarks are
produced and each decay to a quark and an LSP
x
z
For the moment we neglect any potential transverse boost
to the entire di-squark system (from ISR for example)
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 We define the variable MR as ( j1 and j2 are quark jets from
previous slide):
 It is like a 1D analogue of the invariant mass, along the z-axis
 It is invariant under longitudinal boosts
 See paper for more details on it’s derivation:
arXiv:1006.2727v1 [hep-ph]
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Properties of
 Returning to the di-squark example, if
(the squarks
are produced exactly at threshold) then
 We find that, even if
deviates from 1 (which it will in
practice) that MR still peaks
For QCD di-jets (assuming no
mis-measurements, no pt to dijet
system etc.)
Conceptually, we expect to see a
peaking signal over a steeply falling
background
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The Razor
 Unfortunately, the rate of QCD (even at high
) is prohibitively high
such that we will not be able to observe this signal without some
additional discriminating variable(s)
 Such a variable is the Razor, denoted

.
and defined as:(
behaves similarly to the stransverse mass or
Then
has a kinematic endpoint at
)
, such that if
 Hence, similarly to
or
, we take the ratio of two variables with
dimension mass (or energy if you prefer) and cut on a scale-less
variable.
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Properties of
 As defined, MR is very robust against jet mis-measurements,
especially ‘catastrophic’ under-measurements of jets’ energy
 This is because it is, in a sense, a geometric average of the two
jet’s momentum
 The large transverse momentum imbalance that can result from
jet mis-measurements or jets falling outside of phase-space
acceptance, or unclustered energy - which can result in potentially
large missing ET - is largely protected against by the use of the
Razor. MTR and MR measure the same scale, but are also largely
uncorrelated
 Rather than demonstrating this analytically, we will see some of
these properties illustrated in these slides
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Generalizing to an inclusive environment
 Up until this point, we restricted ourselves to a 2 jet final state. For
a number of reasons we would like to generalize to a multi-jet (or
even fully inclusive) final state
 final state radiation will occur, and is something we don’t really capture
in our current MC samples
 For better or worse, if nature includes SUSY then we shouldn’t restrict
ourselves to looking for right-handed squarks decaying directly to LSP’s
 To do this, we will take all the jets (or all the objects) in our final
state and group them into two mega-jets, or hemispheres
 In the following examples, we do this my minimizing the invariant
masses of the two hemispheres
 We have studied several other “hemisphere” algorithms, and find
that these results are not sensitive to this choice (since all the
algorithms get the assignments often wrong anyway)
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Toy examples
 What were our two jets are now two hemispheres, and MR is defined
as before with this substitution (hemisphere masses set to zero, like
jets)
 To understand what should happen to MR in a more general class of
scenarios, we consider 3 toy examples:
 (A) production of two different heavy particles with
 (B) production of two identical heavy particles, with one decaying
through the lighter massive particle and then to jet+LSP
 (C) Both identical heavy particles decaying like this
A
B
Christopher Rogan - SUSY All Hadronic/GMSB Meeting 26-08-10
C
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Pythia vs. ALPGEN QCD Modeling
Pythia QCD
ALPGEN QCD
DATA
 For multi-jet analyses - especially those which rely on the angular
correlations between jets - Pythia is NOT reproducing the observed
data, qualitatively OR quantitatively
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Calo Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
Track Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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Normalized to 10 pb-1
PF Jet Analysis
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MC samples
 NLO x-sections from
https://twiki.cern.ch/twiki/bin/viewauth/CMS/StandardModelCrossSecti
ons used when available for backgrounds, otherwise LO x-sections
returned from generator
 Samples those listed in:
https://twiki.cern.ch/twiki/bin/view/CMS/ProductionSummer2009at7TeV
 PYTHIA: QCD, LM signal points, di-bosons, QCD di-photons
 MADGRAPH: Single top (s-chan,t-chan, tW), ttbar, W(l)+jets,
Z(ll)+jets, Z()+jets, +jets
 ALPGEN: QCD (beginning to look at other bkg)
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