Transcript Slide 1

LHC Physics: an
experimentalist’s perspective
Claudio Campagnari
UC Santa Barbara
1
What are these lectures about?
• For HEP theory graduate students
– Unknown (to me) mix of formal/model builders/phenomenology
• About 1 year before start of LHC physics
– A new energy regime  hopefully will lead to historic discoveries
• But with no guarantees.. 
• Give you a flavor of how we (experimentalists) go about this
business
• Help you in understanding experimental issues
– Help you understand and appreciate results as they come along
– Even as a theorist need some intuition if you want to be “in the game”
• Point out issues on the theoretical side
• Personal slant
• Based on talks (2006) at the West Coast LHC Theory Network
and at the LHC Olympics
2
What this talk is not about
• A status report on LHC machine and detectors
• A collection of pretty pictures
– Although the detectors and machine pictures are pretty
• A collection of results from physics reach studies, eg,
if there is SUSY with this set of parameters, we’ll have
a 5 signal in XX fb-1, or we’ll exclude it at 95% CL in
YY fb-1
–
–
–
–
(Perhaps) interesting and important but ….. boring (to me)
New Physics models are guesses anyway
I don’t believe these studies all that much
You will not learn very much. IMHO, more important to think
in terms of general principles
– I will, however, show some such results to illustrate the
principles
3
Disclaimer
• Most (all) of the LHC related pictures/plots
that I will show to illustrate my points are
from CMS
• Not because I do not like Atlas
• But because I am on CMS
– easier for me to find CMS material
– and I understand it better
• Much of what I'll talk about will be quite
general and applies to Atlas also
4
Outline
1. Detectors 101
•
•
How do these detectors work in broad terms, capabilities,
limitations
Physics Objects
2. Physics “landscape” at the LHC
•
Cross sections, rates for SM processes and generic NP
3. Searches for NP
•
•
•
How are they done, what are the ingredients
Issues on the theoretical side
Case studies
Obviously, can only scratch the surface. Give
rules of thumb to help you think about this stuff
5
Detectors 101
• Detectors for high PT at colliders are designed to
identify and measure the "objects" that are used
to do physics
–
–
–
–
–
electrons
muons
taus
photons
quark and gluons as jets
• including b-quark jets
– neutrinos (and dark matter, etc)
• as missing energy
• A "generic" detector is a cylinder (with endplugs)
6
with concentric layers of detector elements
Detector Slice
muon
hadronic
calorimeter
Tracking in solenoidal B-field
to measure PT
tracking
EM cal.
e

, K, p..


Artwork by Corinne Mills
7
A more realistic slice (CMS)
8
And what it actually looks like (late April)
9
Physics Objects
•
Go through the physics objects one-by-one
–
Not many details, but general picture
•
•
•
•
How are they detected?
How well are they measured?
How are they misidentified?
Will conclude with score card on objects
•
A little understanding of how this works useful to
1. Appreciate the forthcoming exp. results
2. If you want to participate in the LHC program
10
Electron signature
• Track in the inner detector
• Shower and complete energy deposition in EM calorimeter
– electron bremsstrahlung
– e+e- pair production
http://www.irs.inms.nrc.ca/EGSnrc/pirs701/node22.html
http://www.irs.inms.nrc.ca/EGSnrc/pirs701/img12.png
11
Electron Signature (2)
www-zeus.physik.uni-bonn.de/~brock/
http://student.physik.uni-mainz.de/~reiffert/atlas/em-shower.jpg
X0 = radiation length
PbW04: 0.9 cm, Pb: 0.6 cm, Cu:1.4 cm
12
Photons
• Just like electron, but no track
• Resolution of EM calorimeters very good, eg, CMS
(E in GeV)
• Gets better with increasing E
• Question: where do all these terms come from?
• Answers
– 1st term: shower statistics (fluctuations of number of
particles in shower)
– 2nd term: mostly module-to-module calibration
– 3rd term: noise, pileup, etc
13
Hadrons
• Track in inner detector (unless neutral, eg, n)
• Hadronic interaction
– Some energy deposition in EM calorimeter
– Energy deposition in HAD calorimeter
Interaction length 
PbWO4: 22 cm
Pb: 17 cm
Cu: 15 cm
14
http://student.physik.uni-mainz.de/~reiffert/atlas/hardron-shower.jpg
EM vs HAD showers
•
The pretty pictures look similar, but the physics is different
–
with important consequences
X0 << 
1.
•
•
Longitudinal (and transverse) evolutions quite different
e/ on average shower 1st and stop 1st
 use it to separate e from 
This is a good thing
2. Hadronic shower fluctuations large
•
•
Energy resolution poor
Response often not linear with E
This is not a good thing
15
Calorimeter response to  (CMS)
Poor resolution compared to e/
Non-linear response
16
Jets
• Traditionally reconstructed by summing the
energy in nearby calorimeter towers
• Limitations in the had
energy measurement leads
to poor resolution
17
Aside on rapidity
• In hadron collider not very convenient to use angular
cylindrical coordin ates (, q)
– even if the geometry is cylindrical
• Basically because the CM is boosted
• Rapidity y = ½ log(E+PZ)/(E-PZ)
• d3p/(2E) = ½ dPT2 dy d
– Phase space: flat in dy
• Longitudinal boost (eg takes from LAB to CM frame):
– y  y + y
–  = tanhy (same for all particles)
• Pseudorapidity  = log(cot(q/2)) = y in the limit E>>m
– Jets of given PT have constant  ~  at all q
18
Muons
• Measured in the inner tracker, go through the
calorimeter, measured again outside
CMS
• Unlike e case, resolution gets
worse at high energy. Why?
19
Neutrinos (or dark matter)
• Sum up the momenta of everything, what is left to get back to zero
(missing energy) is the neutrino(s)
• Longitudinal information is lost down the
beampipe  can only do in transverse plane
– Missing transverse energy (MET)
• If > 1 , you only infer the sum of the  trans.
momenta
20
Missing Transverse Energy
• Fake MET mostly from jets, resolutions and tails
1 min bias event contribution to MET
component in a given direction  ~ 6 GeV
• Also from missed muons
• Also from "underlying event"
CMS
CMS
And the tails don't come without some work....
D0
21
Taus
• Detect decay products
• 25% as e or 
• Remainder: narrow jet with 1 or 3 charged
tracks
High momentum 
Boosted
daughters
• Energy resolution intrinsically poor (miss )
22
B-jets
• Wouldn’t it be nice to be able to say: this jet
comes from a gluon. Or an up-quark. Or a
down-quark. Or….
• Dream on!
• Fortunately we can do it for b-jets
– And c-jets, to some extent
– Because (b) ~ 1.5 psec  for P=40 GeV mean
decay length = c ~ 4 mm
Find evidence of “long” lived particles inside a
jet to “tag” a b-jet
• Efficiency typically ~ 50% per jet
• And can use bc (ce) also
23
Instrumental backgrounds (fakes)
• In a given analysis you select the objects (e, ,
, b-jets, etc) for the specific physics channel
that you are interested in
• But how do you know that what you called an
electron (say) isn’t really something else?
• And does it really matter?
– Interestingly enough, in some cases you don’t really
care that much (will see some examples later)
• Although if you don’t know, it is guaranteed that you will find
someone in the collaboration that will make your life
miserable when you try to publish
– But in most cases it does matter, and in some cases it
is the most important/difficult piece of the analysis
• e.g., many searches for rare NP processes
24
Fakes
1. Where do they come from
2. How can we deal with them
25
Fake electrons (1)
Electron
shower
Hadron
shower
Vs
• Sometimes a hadron shower looks like an EM
shower
• Or 0 , e+e- conversion in material
• Or ….
EM shower

High momentum 0
e+

e-
26
Fake electrons (2)
• Usually we are interested in high PT, isolated electrons
• High momentum hadrons that can fake the electron
signature are in jets
– And there are a lot of jets, as we will see later
• These hadrons are usually not isolated
– So requiring “isolation” helps
– But occasionally jet fragments to a leading particle
• Typical probability of “jet faking isolated electron” ~ 10-410-5.
• Watch out! Some jets can have real electrons, e.g.,
bce
27
Fake photon
• Same picture as before, high momentum
EM shower
0 
High momentum 0


• Can look just like single 
• Again: high momentum 0 from jets
• Probability of “jet faking isolated ” ~ 10-4
28
Fake muons
• A hadron can occasionally “sail through” without
interacting
– It will then look exactly like a muon
•  and K decays in flight
• Again: from high PT pions and kaons in jets
• Typical probability of “jet faking isolated ” 10-4-10-5
29
Fake taus
High momentum 
Boosted
daughters
• Sometimes a jet will fragment in a small number
of well collimated tracks, and look like a 
• Typical “probability of jet faking a ” ~ 10-2-10-3
• Much worse than for e and 
• A real shame
– 3rd generation in many NP scenarios is special
– Heavier than e and , higher coupling to Higgs,
window on EWSB
30
Fake b-tagged jets
• Best b-tag: evidence of long lived particles inside
a jet
– Typical flight lengths ~ O(mm)
• Fake b-tags
– Track reconstruction errors, resolution tails
– Residual long-lived particles inside a jet that have
nothing to do with b-quarks, eg, KS  +-, p
– Particles directly originating from collision, eg, 
conversions, nuclear interactions in beam pipe
– b-quark creation as part of jet evolution. Gluon
splitting g bb
• Typical “probability of jet faking b-tag” ~ 1%
31
Fakes
1. Where do they come from
2. How can we deal with them
32
Dealing with fakes
• Clearly: try to do the best job you can and be as
smart as you can to reduce them
• But you will never get rid of them. And you need
to understand them.
• In general you do not get these from simulation
– You are looking at improbable occurrences in the tail
of distributions
• Jet fragmentation
• Detector response
• Two general approaches
33
1st approach: use fake probabilities
• Suppose you are looking for a process with
X+Y+b-tag (where X and Y are, eg, electrons or
muons, or taus).
• You are worried about background from X+Y+jet
with jet faking a b-tag
• You figure out your rate of X+Y+jet
– Either from theory (Monte Carlo) or data (better)
– You measure the fake probability somewhere else
• This is not always easy!
– You apply it to X+Y+jet to predict the background from
X+Y+(fake b-tag)
34
Some fake probabilities
D0
Lauer PhD Thesis
Iowa State
Jets as 
Jeans (Rome, CDF)
LHC Symposium 05
Btag fake rate
35
2nd approach to fakes
• Relax your requirements, let backgrounds in
• By studying how much background comes in as
a function of your requirements, try to estimate
how much background is left after your final
requirements
36
Final Comments on fakes
• Jets can fake lepton/b signature
– not very probable
– but "jets are everywhere"
• we'll come back to this later
• A major component of the physics program at a collider is to
develop robust criteria for lepton/b identification
– efficiency vs rejection
• Generally not emphasized much when you hear a talk at a
conference
– experimentalists take it "as a given", (some) theorists are oblivious to it
• Some appreciation of this required if you want to participate to
the LHC program
– A paper suggesting to look at a signature for NP which is swamped by
instrumental backgrounds is (nearly) useless
37
• Nearly: do not underestimate the cleverness of your exp. when challenged
ScoreCard on objects
Object
Notes
Typical eff
Jet fake rate
e
Excellent resolution
Improves with E
~ 90%
~ 10-4-10-5

Excellent resolution
Degrades with E
~ 90%
~ 10-4-10-5

So-so resolution
~ 50%
~ 10-2 - 10-3

Excellent resolution
Improves with E
~ 90%
~ 10-3-10-4
Jet
Poor resolution (> 10%)
~ 100% if above
threshold
-
~ 50%
~ 1%
Btag
MET
Depends on everything
else in the event!
38
Outline
1. Detectors 101
•
•
How do these detectors work in broad terms,
capabilities, limitations
Physics objects
2. Physics “landscape” at the LHC
•
Cross sections, rates for SM processes and generic
NP
3. Searches for NP
•
•
•
How are they done, what are the ingredients
Issues on the theoretical side
Case studies
39
Hadron Collider
LHC opens up new energy regime
– 14 TeV in CM vs 2 TeV at the Tevatron
– With higher luminosity
– I will not belabor this point…
Hadron collider = collisions of two broadband beams
of partons (q, q, and gluons)
40
http://www.physics.nmt.edu/~raymond/classes/ph13xbook/img2047.png
Parton-parton luminosities
• A way to think about this and develop a semi-quantitative
intuition: parton-parton luminosities
• Reminder: luminosity is a measure of the intensity and
brightness of the beam: N=L 
• Define "effective luminosity" for parton-parton collisions
as a function of the ECM of the parton-parton system
• Parton-parton x-section, i+j  X:
• pp (or pp) x-section, ppX or ppX:
(the sum is over all the i's and j's that result in X)
41
Parton Distribution functions
fi(x) = probability of parton i having momentum fraction x
cannot be calculated from first principles
Go to http://durpdg.dur.ac.uk/HEPDATA/PDF click around
and make your own plots. It’s pretty cool!
The LHC is mostly a gluon-gluon collider!
42
Parton-parton luminosities (2)
• We had: pp (or pp) x-section, ppX or ppX:
• Rewrite it as:
Luminosity for parton-parton collisions as a function of parton-parton ECM
EHLQ
RMP 56 579 (1984)
43
Parton-Parton luminosities (3)
gg luminosity @ LHC
qq luminosity @ LHC
gg luminosity @ Tevatron
qq luminosity @ Tevatron
44
Zooming-in on the < 1 TeV region
gg luminosity @ LHC
qq luminosity @ LHC
gg luminosity @ Tevatron
qq luminosity @ Tevatron
45
Ratio of LHC and Tevatron parton luminosities
LHC vs Tevatron
gg
qq
1st (simplistic) rule of thumb:
– For 1 TeV gg processes, 1 fb-1 at FNAL is like 1 nb-1 at LHC
– For 1 TeV qq processes, 1 fb-1 at FNAL is like 1 pb-1 at LHC
46
Another rule of thumb:
LHC
dL/d falls steeply with ECM
• In multi-TeV region, ~ by
factor 10 every 600 GeV
• New states produced near
threshold
• Suppose you have a limit
on some pair-produced
object, M > 1 TeV
• How does your sensitivity
improve with more data?
gg
qq
gg
qq
Answer: by ~ (600/2)=300 GeV =
30% for 10 times more lumi
47
Improving sensitivity with lumi is tough....but you might turn a hint into discovery
Cross Sections
T. Han
Tev4LHC
Good to keep these in mind when thinking about NP
48
Total x-section: ppanything
•
Three components
1. pppp (elastic)
2. pppX (diffractive)
3. ppX (inelastic)
•
Don’t know to 10-20%
–
–
•
Order 100 mb
Will measure it (TOTEM)
Interaction rate:
–
N=L¢
•
For L = 1033 cm-2 sec-1 :
N = 100 MHz
49
What does the average event look like?
Minimum Bias events: events selected with a minimal interaction trigger
Trigger when “something happened”, ie, the protons broke up
d3p/(2E) =
½ dPT2 dy d
About 6 charged particles per unit rapidity (+ neutral)
 Of order 90 particles in detector acceptance
Plots stolen from: Czech. Jour. of Phys., Vol.54 (2004), Suppl. A, p221
50
More min bias
One min-bias event in CMS HCAL
Charged Particle Density
http://home.fnal.gov/~sceno/jpg/minutes/aug121999/dg_doc.pdf
1.0E+00
Pythia 6.206 Set A
CDF Min-Bias Data
Charged Density dN/dddPT (1/GeV/c)
1.0E-01
1.8 TeV ||<1
1.0E-02
PT(hard) > 0 GeV/c
1.0E-03
1.0E-04
1.0E-05
CDF Preliminary
1.0E-06
0
2
4
6
8
10
12
14
PT(charged) (GeV/c)
Lots of soft particles
51
Moving on to harder scatters: jets
52
Jets
Jet rates are enormous….Compared to anything else that is interesting
53
A two jet event from D0 (di-jet)
Two jets back-to-back in 
Note: 45 GeV of MET
Also: looks like there is more stuff in the event (underlying event)
54
More on jets
• At lowest order: 2 back-to-back jets
• Higher order diagrams: multijets
– Suppressed by ~ s per additional jet
• Because of the high x-section for QCD jet
processes it is very difficult to look for NP in final
states with jets only, eg, Hbb
– Not entirely true. Interesting to look for deviations
from QCD. Some great examples later
– Need to key off e, , , MET, etc
• A real limitation of hadron colliders
• Perhaps the main reason for ILC
55
Underlying event & Pileup
• The D0 di-jet event looked to have additional stuff besides the two
jets
• This is what you expect. The remnant of the protons after the hard
scatter must end up somewhere! They recombine into hadrons and
the show up in the detector
• A nuisance: underlying event
– Looks like min bias (sort of)
• Also: pileup
– At LHC luminosity there will be on average several interactions per
beam crossing (up to ~ 20 at full luminosity)
– Even more of a nuisance!
• eg high track multiplicity degrades tracking performance
56
Pileup
Missing Et resolution degraded by pileup
1 min bias event contribution to MET
component in a given direction  ~ 6 GeV
CMS
57
Further down in x-section….
(bb, high PT) ~ 1 b
(W  l) ~ 60 nb
(tt) ~ 1 nb
(WW) ~ 200 pb
(tt) ~ 1 nb
TeV scale SUSY ~ pb
58
tt
• (tt) huge compared to the Tevatron
– 1 nb vs 10 pb
• Coupled with the high luminosity, LHC is a top factory
– This is a great thing!
• On the other hand: ttleptons + jets + MET
– This is similar to many possible NP signatures
 tt is background to many NP searches
Yesterday’s hard won discovery is today’s background!
59
Outline
1. Detectors 101
•
•
How do these detectors work in broad terms,
capabilities, limitations
Physics objects
2. Physics “landscape” at the LHC
•
Cross sections, rates for SM processes and generic
NP
3. Searches for NP
•
•
•
How are they done, what are the ingredients
Issues on the theoretical side
Case studies
60
NP discoveries at the LHC
3 + 1 ingredients
0. Detector and machine: If they don't work, forget it
•
How fast will they come up? Don't know, but probably not
fast.
1. Trigger: If you didn't trigger on it, it never happened
•
See following discussion
2. Backgrounds: It's the background, stupid
•
Need to understand SM and instrumental backgrounds
•
•
•
Instrumental BG: us (experimentalists, mostly)
Physics BG: you (theorists, mostly)
There are exceptions....
3. Searches: If you look for something, you may not
find it. But if you don't look, you will never find it 61
•
Model independent vs model dependent searches
Trigger (1)
• Inelastic cross section O(100 mb)
• For low luminosity ~ 1033 cm-2 sec-1, event
rate ~ 100 MHz
• Data Acquisition Capability: ~ 100 Hz
• Most of the events are thrown away!
62
Trigger (2)
• The decision on what to trigger on has enormous impact on
the physics that we can do
• Trigger selects objects (e, , jets..) or combinations thereof
• All kinematical distributions fall steeply with PT  trigger
selects objects above a threshold
•
It is always a compromise
•
A balance between competing
priorities
•
A source of great debate in the
collaboration
•
If you, as a theorist have a great
idea for NP…..
1.
Check that your events have been
triggered on
2. If not, try to convince people to
devote bandwidth to your theory
And your argument better be good… 63
Example of possible CMS
33
trigger menu (L=2 x 10 )
64
Comments on the trigger menu
• Will grow to be much more
complicated
– More lower threshold prescaled
triggers
– More triggers with combinations of
objects aimed at specific channels
– ……..
D0 We
• Thresholds for di-objects <
thresholds for single objects
– eg 2e:ET>17 GeV 1e:ET>29 GeV
• Some of these thresholds are
already pretty high!
65
New Physics discoveries @ LHC
Broadly speaking, three possibilities
1. Self Calibrating
•
e.g., a mass peak
2. Counting experiments
•
The number of observed events of some type
is >> than the SM prediction
3. Distributions
•
The distribution of some kinematical quantity
is inconsistent with the SM prediction
NB: the distinction is not always clean, but still
66
useful to think in these terms
Self Calibrating Signals (SCS)
• A NP signal that obviously stands out
– where you do not need to know the SM BG very
precisely
• or do you?
• watch out for irrational exuberance
• For example:
– A mass peak
– A huge distortion to some kinematical distribution
67
Reminder: Drell-Yan
e- or e+ or +
SM Drell-Yan
Di-jet background
WW background
68
SCS example: Z'  
What a 100 pb-1 expt
might look like
Cousins, Mumford, Valuev
UCLA
69
Another SCS example: di-jet resonances
e.g., excited quarks, axigluons, E6 di-quarks, Z', W',...
Rules of thumb:
• If produced strongly  about same cross section as
QCD at same mass, fairly easy to see
• If produced weakly, tougher
CMS
CMS
70
Di-jet resonances (cont.)
95% CL Sensitivity to Dijet Resonances
CMS
Published
Exclusion (Dijets)
CMS
100 pb-1
CMS
1 fb-1
CMS
10 fb-1
E6
Diquark
Excited
Quark
Axigluon
or Coloron
Color Octet
Technirho
W’
RS
Graviton
Esen and Harris
(FNAL)
Gumus and Akchurin
(Texas Tech)
Z’
0
1
2
3
4
5
6
Mass (TeV)
71
(Yet) Another SCS example: di-jet mass distribution
• Distorts angular distributions
• More scatters at high angles
– More jets at high PT
– More di-jets at high mass
• Like Rutherford scattering,
but with quarks!
Quark Compositeness New Interactions
q
q
M~
M~
q
q
Dijet Mass << 
Quark Contact Interaction
q
q

QCD Background
q
q
QCD + Signal
Dijet Mass or jet PT
If the "edge" is low enough, this
could be a relatively easy discovery
(Self-calibrating variety)
72
Di-jet mass distribution distortion
• Ratio of events at high-low  is a sensitive
variable that eliminates many syst uncertaintes
CMS
CMS
Left-Handed
Quark Contact
Interaction
+ for
100 pb-1
(TeV)
+ for
1 fb-1
(TeV)
+ for
10 fb-1
(TeV)
95% CL Exclusion
6.2
10.4
14.8
5σ Discovery
4.7
7.8
12.0
Esen and Harris (FNAL)
Gumus and Akchurin (Texas Tech)
73
SCS: Edges
10 fb-1
M(l+l-)
74
Not all that glitters is gold
Pentaquarks
z(8.3)
Leptoquarks
40 GeV top
Buyer beware.
Especially in the tails of distributions
75
An aside
Tail of the jet ET distribution. Definitely not a self calibrating signal (SCS)
CDF PRL 77
438 (1996)
• Data in the tail not consistent with QCD
+ (then) existing sets of parton
distribution functions (PDFs)
• Looks like contact term  ~ 1.6 TeV
• Further PDF analysis found that the
discrepancy could be absorbed by
modifying gluon distribution
– without conflicting with other data
– even though all existing PDF fits were
"low"
• Modern PDFs include uncertainties
• A great step forward
Example of careful, not-so-glamorous,
phenomenological work that has a major impact
76
PDFs with error analysis
http://durpdg.dur.ac.uk/HEPDATA/PDF
77
Counting experiments, distributions
• Not all NP signals are as dramatic as a mass peak
• Counting experiment
– Select events passing some requirements
– Count them. Is the number of events consistent with the
SM prediction?
• Kinematical distributions
– Select events passing some requirements
– Look at kinematical distributions, eg, the PT of the jets
– Are these distributions consistent with the SM prediction?
• Of course: not mutually exclusive methods
– Ideally: do both
 Need the SM prediction
78
SM prediction
• In some cases the SM prediction can come entirely
from the experiment (data driven)
• Robust
• In other cases the SM prediction relies heavily on
theory
• Not so robust
• And of course the SM prediction must include
instrumental backgrounds...(fakes)
• A couple of examples to understand typical issues
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Example 1: CDF search for NP in lep +  + MET
•
www-cdf.fnal.gov/physics/exotic/r2a/20050714.loginov_LepPhotonX/
• A fairly simple final state
• Motivated by few weird events in Run 1 (before 1996)
• Run 2 (>2002): select events, then compare with SM
– both number of events and kinematical distributions
• Requires careful accounting of SM sources
• A lot of work!
– typical for this type of searches
– painstaking accounting of many BG sources
– you don't just "run the Monte Carlo"
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SM contributions to lep++MET (1)
• pp  W+jet, Wlep , jet fakes 
– estimated from observed rate of W+jet and measured
probability for jet to fake a 
– difficult (100% uncertainty), but data driven
• Drell-Yan e+e- pairs with hard brehmstrahlung,
where the electron is lost and looks like a  and
the MET fluctuates high
– estimated from observed rate of Zee and Ze"" and
observed MET distribution
– data driven
• pp  jets, jets fake leptons
– estimated from data by relaxing the lepton quality
requirements, and extrapolating
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SM contributions to lep++MET (2)
• pp  W or Z
– This turns out to be the main background
– Need theoretical input
– Tools are:
• LO parton level event generators, interfaced to Pythia
– yes: more than one
• NLO calculation
– Good case because the NLO calculation exists
• Often it doesn't
• The NLO/LO K-factor is ~ 1.5, but it varies across
phase space
• The LO MC is then "fudged" to account for that
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NLO V+ (V=W or Z)
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Baur, Han, and Ohnemus. PRD 57 (1998) 2823
NLO changes shape of distributions
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Results of CDF lep +  + MET search
Decent agreement in shape
and normalization
Without NLO,SM prediction ~ 26 ± ?
What would you have concluded?
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Results recently updated
Stolen from H. Frisch’s talk at Gordy Kane’s Symposium (Jan 2007)
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Example 2: UA2 Wtb search (1989)
• Ancient, but an example of a search based on a
shape analysis that is independent of theoretical
assumptions
– yes, sometimes this happens!
Z. Phys. C46, 179 1990
• Signal is Wtb, teb
– M(e) < MW
• BG is W+jets, We
– M(e) = MW
• Cannot reconstruct M(e)
– Because PZ() unknown
• Next best thing: transv. Mass
• Shape: kinematics + MET resolution
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Example 3: CDF tt evidence (1994)
• Also ancient, but example of counting expt independent of
theoretical assumptions
• Signal: lep + MET + ≥ 3 jets (≥ 1 of them b-tagged)
• Background: W+jets (fake b-tag), or Wbb (real b-tag)
many more
diagrams....
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tt search strategy
• Count number of events with lep + MET + ≥ 3 jets (≥
1 of them b-tagged)
• Compare with W + jet prediction
• If excess  signal !
• But where does the prediction come from?
• Measure probability of tagging ordinary jets in QCD
jet events. Sources are:
– Fakes. Should be the same in W + jets events
– Real b-quarks. Expect fraction of b-quarks/jet to be larger
in QCD jet events than in W+jets
• because QCD jet events are mostly gluons and gbb
 BG prediction overestimated BUT entirely from data!
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CDF tt evidence results
• Good agreement in events with N=1 or 2 jets where tt events
are expected to be (almost) absent
• Excess in N=3 and 4 jets, where tt is expected to show up
• Also: calculate BG from stateof-the-art theory of Wbb
(method 2)
– Confirm BG calculation
from data (method 1) is
pessimistic!
PRD 50
2966 1994
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Example 4
From Joe Lykken: Is particle physics ready for the LHC?
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92
93
94
What was the problem?
• Incorrect use of theoretical tools
• The general purpose Monte Carlos only have leading
order diagrams, eg,
q
q
Z


• If you run these event generators you will get events with
Z + jets
– When Z these are a source of jets + MET events
• The jets come from parton showers from the initial state
• For Z + 1 moderate PT jet, you get about the right answer
• For Z + many high PT jets you get the wrong answer
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Is everything lost?
• No. People have calculated, eg, Z + multijet.
• Leading order matrix element calculation only 
significant uncertainty
• And in order for exp to use this calculation, need to
interface to shower MC
• Lots of tricky issues. Need to be very careful
• As an experimentalist, relying on these tools to make
a discovery makes me a bit queasy
– Many of my colleagues are more optimistic than I am...
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Comments
• Often purely data driven BG estimates do not work
• SM BG to LO have large normalization uncertainties
– Makes counting experiments difficult
• SM LO event generators can have large shape
uncertainties
– Makes shape analyses difficult
• What are the uncertainties at LO? at NLO?
– Often can get handle from data, e.g., W+jets vs Z+jets
• Where is the smoking gun?
– As an experimentalist, more comfortable if uncertainties
are under my control
– As a theorist, you might feel differently
– Don't ask how sausages are made
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What can theorists do for us?
Slides from Z. Bern at LBNL LHC West Coast Theory Network meeting
And don't forget to implement them in a MC so that we can actually use them 
Now that we are about to get data, nuts-and-bolts
contributions can be more useful than suggestions
for another beyond the SM theory
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Model dependent vs. model
independent searches
• Can search for generic NP signatures
e.g., the lep +  + MET CDF search described earlier
• Or, for very specific, complicated signatures
e.g., ppTT, TtZ TbW, teb Z, W
• Because we do not know what the NP is, generic
searches are very powerful
• But in a generic search worry about missing
complicated signature
• With O(1000) physicists both approaches will be
pursued
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BaBar
Palano (Bari)
DsJ(2317) DS 0
PRL90 242001 (2003)
cs meson. Was expected to have
mass ~ 2.5 GeV, decay strongly to
DK, and therefore have broad width
So: noone bothered to look!
This huge signal had been in various data
sets for many years!!
– What is hiding in the Tevatron data sets?
– What was missed by the Tevatron triggers?
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A case study: tt at the Tevatron
• The high PT discovery at Tevatron
• Not NP, the ultimate known unknown
• Complicated signature, search narrowly focused on
expected SM properties
Would it have been seen in generic search?
• In the high statistics lep+jets channel probably not for
a long time
– Lots of BG, theoretical tools (W+multijet & Wbb
calculations/MC) developed specifically for the search
• In the dilepton channel would have slowly emerged as
excess of events with jets (and eventually, b-jets)
Power of multi-lepton searches
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If we see NP, can we tell what it is?
• Great question
– Supersymmetry and the LHC inverse problem (hep-ph/0512190)
• Ian Hinchliffe: I’ll discover it first, I’ll think about it on
the way to Stockholm, and I’ll tell you on the way
back
• It does not come as a surprise that figuring out
precisely what is going on at a hadron collider is not
trivial
– Motivation for ILC....
• Not something that keeps me awake at night
– Should we be so lucky!
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NP Interpretation
• Emphasis shifts to "Given that you see X,
if the NP is Y, you should see Z"
– suggestions with Z experimentally impossible not very
useful 
• but do not underestimate your experimental
colleagues!
– a well developed feel for experimental issues could
make a difference
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Conclusions
• LHC may trigger a revolution in particle physics
• I hope to have given you a flavor of how
searches for NP at the LHC can be carried out
• You are beginning your career at an exciting
time
• You have a golden opportunity to be part of this
adventure. Seize it!
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