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Experimental Techniques and their Impact onand their Impact on
Phenomenological AnalysesPart 1
Jonathan Butterworth
MC4LHC/MCnet/HEPTOOLS/Artemis training event
5th & 6th Jan 2009
Jon Butterworth, UCL 1
Thanks to K.McFarland, E. Nurse, P.Renton, F. Siegert, R.Thorne…
OutlineOutline
• Introduction
• Fundamental or observable?
• Corrections, corrections
• Jets and Jet Algorithms
• Leptons and photons
• Inclusive or exclusive
• Monte Carlos and tuning
Jon Butterworth, UCL 2• Inconclusion
IntroductionIntroduction
• The aim of these lectures is to discuss how choices which are made by experimentalists have an impact onwhich are made by experimentalists have an impact on the usefulness of the data for phenomenological analysis.
• Seemingly arbitrary choices can sometimes dramatically affect the shelf-life and impact of a measurement!
Jon Butterworth, UCL 3
Fundamental or ObservableFundamental or Observable“Fundamental” things (top, W, H masses, couplings etc) are often only defined
within the theory, and so are often rather model dependent, whereas
“observable” things (proton mass, charged particle multiplicity, inclusive lepton
cross section etc) are well defined but difficult to interpretcross section etc) are well defined but difficult to interpret.
Jon Butterworth, UCL 4
Precision (pseudo-)observables
ll FBhad
0hZ A M ΓΓΓΖ σ
tau polarisation Ae(1)
Z lineshape (5)
tau polarisation - Ae(1)
left-right asymm -Ae (1)
Z (b,c) properties (6) cbcFB
bFB
0c
0b A A A A R R
2 lept hadsin (Q ) (1)ϑ
W properties (2) WW M Γ Total of 17 at high Q2
(assuming lepton universality)
peff FBsin (Q ) (1)ϑ
top quark mass (1)(assuming lepton universality)
from > 1000 measurements with (correlated) uncertainties
Jon Butterworth, UCL 5Pete Renton Jul/ Aug 2008
progress vs. timePete Renton 2008
2008 direct mt and mw
2008 indirect mt and mw2008 indirect mt and mw
1995 indirect mt and mw
1995 direct mt and mw1995 direct mt and mw
Jon Butterworth, UCL 6ICHEP08 Pete Renton Jul/ Aug 2008
Fundamental or ObservableFundamental or Observable
• Note that H1 andNote that H1 and ZEUS do not even plot and fit F2 here;2
• The reduced cross section is an obserable(modulo electroweakcorrections), F2 is not.
Jon Butterworth, UCL 8
Fundamental or ObservableFundamental or Observable
• Parton densities areParton densities are
transportable to other
experiments within the SM
(QCD, factorization).
• Good example of experiments
making measurements and
doing the phenomenological
analysis themselves, but also
making the data available to
others (MSTW CTEQ NNPDF
Jon Butterworth, UCL 9
others (MSTW, CTEQ, NNPDF
etc…)
Fundamental or ObservableFundamental or Observable
• So the biggest headline derived from a measurement isSo the biggest headline derived from a measurement is not the same thing as the measurement itself– It is often not even really a measurement.
• Ask yourself: if – (e.g.) the LHC proves that the SM is wrong in some possibly
bi ( Hi i l l t f KK ti l i l lbizarre way (no Higgs in loops, lots of KK particles in loops, low mass gluino or gravitino)
– Or some theorist makes a much better calculation of my process
how does a given result need to be modified?– For a real measurement, the answer should be “it doesn’t” or at
l t “it d ’t b d th t ti t i ti ”
Jon Butterworth, UCL 10
least “it doesn’t beyond the systematic uncertainties”.
Corrections correctionsCorrections, corrections
• Many corrections are or may be applied on the way to publishing a measurement;– Dead time, trigger acceptance, detector geometry, energy
scale, dead material, pile-up, electroweak radiative corrections, FL, “underlying event”, “hadronisation”…FL, underlying event , hadronisation …
• If a correction requires intimate knowledge of the detector, then apply it.pp y– After our experiment finishes, no-one is going to be able to (or
want to!) correct for our trigger efficiencies, energy scale and resolution etc
Jon Butterworth, UCL 11
resolution etc
Corrections correctionsCorrections, corrections
• If a correction requires intimate knowledge of a developing• If a correction requires intimate knowledge of a developing theory, or a Monte Carlo model of some poorly-known physics, do not apply it!*physics, do not apply it!– After your experiment finishes, if someone does a NNLO
calculation, or really understands underlying events, hopefully d t i f l!your data remain useful!
• There’s obviously a sliding scale, and a grey area…Dead time trigger acceptance detector geometry energy– Dead time, trigger acceptance, detector geometry, energy scale, dead material, pile-up, electroweak radiative corrections, FL, “underlying event”, “hadronisation”…
Jon Butterworth, UCL 12
*or at very least, present the uncorrected version first!
Corrections correctionsCorrections, corrections
• If a correction requires intimate knowledge of a developing• If a correction requires intimate knowledge of a developing theory, or a Monte Carlo model of some poorly-known physics, do not apply it!physics, do not apply it!– After your experiment finishes, if someone does a NNLO
calculation, or really understands underlying events, hopefully d t i f l!your data remain useful!
• There’s obviously a sliding scale, and a grey area*…Dead time trigger acceptance detector geometry energy– Dead time, trigger acceptance, detector geometry, energy scale, dead material, pile-up, electroweak radiative corrections, FL, “underlying event”, “hadronisation”…
Jon Butterworth, UCL 13
*although personally I don’t think it’s very big!
Corrections correctionsCorrections, corrections
S it i b t t h b th ( l HERA DIS ti• So it is best to have both (a la HERA DIS: cross sections and PDFs), but if you are only going to have one it must be the observable!the observable!
• Few, if any, measurements are completely model-independentindependent.– There will probably be some model dependence in our
detector corrections (e.g different hadronisation models ff )affect how we understand calorimeter response)
– Minimise it and include in systematic error bars.
Jon Butterworth, UCL 14
Corrections correctionsCorrections, corrections• An example of something in the grey area
• W-asymmetry or lepton asymmetry at Tevatron?
• next slides slides from Kevin McFarland (Rochester) ( )DIS08
Jon Butterworth, UCL 15
Corrections, correctionsCorrections, corrections• W-asymmetry or lepton asymmetry at Tevatron?
• Previous slides slides from Kevin McFarland (Rochester) DIS08
• W asymmetry has a more direct relationship to the distribution of particular partons
And it contains real extra information (from the missing p )– And it contains real extra information (from the missing pT)
• BUT sensitivity to sea quarks is lost and replaced by a systematic errorsystematic error– Easier for PDF fitters to fit the lepton asymmetry.
• Similar issues at LHC (less severe if one assumes anti-u
Jon Butterworth, UCL 26
Similar issues at LHC (less severe if one assumes anti uand anti-d converge at low x.
Jets and Jet AlgorithmsJets and Jet Algorithms
• What is a jet?
• Some requirements on jet definitionsSome requirements on jet definitions
• Available algorithms
Jon Butterworth, UCL 27
What is a Jet?What is a Jet?• Protons are made up of quarks and gluons.
• Quarks and gluons are coloured and confined – we only ever see hadrons.
• A jet of hadrons is the signature of a quark or gluon in the final state.
• The gross properties (energy, momentum) reflect the properties of the quark
or gluon, and stand out above the rest of the event.
• Jets have a complex substructure. High PT Jet Production
PT(hard)
Outgoing Parton
Initial-State Radiation
Proton Proton Underlying Event Underlying Event
Jon Butterworth, UCL 28Outgoing Parton
Final-State Radiation
Picture from Rick Field
What is a Jet?What is a Jet?• Evolution from a hard parton to a jet of partons takes
place in a regime where:– Energy scale is high enough to use perturbation theory
x is not very small– x is not very small– Collinear logarithms are large– Multiplicities can be large– This is largely understood QCD, and can be
calculated
• Hadronisation (non-perturbative) stage has a small ( p ) g
effect (sub-GeV level) and is well modelled by tuned
Monte Carlo simulation (e.g. Lund string)
Jon Butterworth, UCL 29
What is a Jet?What is a Jet?
• Jets are not just less-well-measured leptons or “smeared” partons.j p p– Hard radiation interference at amplitude level– Matching at high scales with Matrix element
M t hi t l l ith t d iti d h d i ti– Matching at low scales with parton densities and hadronisationmodel
– potentially useful information in the internal jet structure, and in particle/energy flow between the jetsparticle/energy flow between the jets
• Jets have no existence independent of the algorithm– even if the “algorithm” = event display + physicisteven if the algorithm event display physicist
Jon Butterworth, UCL 30
What is a Jet?What is a Jet?
• So jet algorithms don’t so much find a pre-existing jet as definej g p g j
one.
• A “jet” (or a pattern of jets) is a complex QCD event shape, j ( p j ) p p ,
designed to reflect as closely as possible the short distance
degrees of freedom (quarks, gluons, H, Z, W…)– The degrees of freedom themselves are generally not physical
observables, but can only be extracted within some theory or model– The cross section for quark production in the final state at LHC is zero
(unless we find something very exciting…)
Jon Butterworth, UCL 31
What is a Jet? (continued)What is a Jet? (continued)
• We want to connect what we measure back to the fundamental degrees g
of freedom of our (Standard) model, so we can publish for example:– Parton densities– Top, W, (Higgs?) masses– Deviations from the Standard Model (or limits derived from their absence)
• (Usually) requires comparison to state of the art theory so our jet• (Usually) requires comparison to state-of-the-art theory, so our jet
finding procedure had better be something the theory/model can
replicatep– Clear separation between detector corrections (model independent) and
interpretation (model dependent).
“T th” i l ith fi l t t t th l i t d t “ t ”
Jon Butterworth, UCL 32
• “Truth” is algorithm+final state, not the calorimeter and not “partons”
Example (from my own experience)
• Jet photoproduction at HERA– Was a completely new energy regime: Photoproduction of jets never before
observed (some analogy to what we are about to embark on)observed (some analogy to what we are about to embark on)
• ZEUS tried kT cluster, plus two implementations of “Snowmass” cone
algorithmsg– One based on a sliding window, one based on a seed. Both respectable at
the time (the seeded one was based on the CDF algorithm of the time)
NLO (Kl K ) d d t ( th t)• NLO (Klasen, Kramer) drew cones around partons (max three per event)– Two partons separated by R ~ 2 may still be in a single cone of R=1, but may
not be found if there is no seed in between them.– Introduce Rsep, the maximum separation allowed between two partons (Ellis,
Kunszt & Soper 1992).
Jon Butterworth, UCL 33
Example • Rsep has a large effect on the NLO theory (left)
• This has no analogy in a final state jet algorithm.
• No common jet definition possible.
• Difference between cone algorithms has large effect on the experiment
(right)– NLO theory cannot use either of ZEUS’s IR unsafe cone algorithms
From JMB, L.Feld, G.Kramer, M.Klasen,
Jon Butterworth, UCL 34
M.Klasen, hep-ph/9608481
Example p• Neither theory and experiment knows how reproduce the other
Actually they can be made to agree by tweaking R– Actually they can be made to agree by tweaking RSEP
• Predictive power of NLO QCD practically gone
• Not a problem if both use the same algorithm• Not a problem if both use the same algorithm – in the ZEUS case we went with kT
From JMB, L.Feld, G.Kramer, M.Klasen,
Jon Butterworth, UCL 35
M.Klasen, hep-ph/9608481
What is a Jet?What is a Jet?
• One good place to look: Les Houches 2007 accords (arXiv:0803.0678)
• Jet definition specifies all details of the procedure by which an arbitrary
set of four-momenta is mapped into a set of jets. Composed of:– Jet algorithm (e.g inclusive, longitudinally boost-invariant kT). – All the parameters of the jet algorithm (e g R=0 7)All the parameters of the jet algorithm (e.g. R 0.7)– The recombination scheme (e.g four-vector recombination, or E-scheme,
or…)
Jon Butterworth, UCL 36
What is a Jet?What is a Jet?
• One good place to look: Les Houches 2007 accords (arXiv:0803.0678)
• Final-state truth-level specification– What is the input (at the truth level). e.g. all final state particles with lifetimes
longer than some cut… – Theory and experiment can correct to this level, within some controlled
systematic error.
Jon Butterworth, UCL 37
Jets for different applicationsJets for different applications
• If you are doing simple searches at high pT, jets are obviousy g p g pT, j– …maybe– Certainly even the “event display + physicist” algorithm should be pretty
reproducible for counting ~1 TeV jets at LHCreproducible for counting ~1 TeV jets at LHC • (really? How precise is that 1 TeV cut?)
• If you are making precision measurements of jet cross sections
(energy scale ~1%) then you will need to compare at least to NLO
QCD.– In this case it is mandatory to have a jet definition which can also be
applied to NLO QCD
• Consequence: This means a detector-independent, infrared &
Jon Butterworth, UCL 38
q p
collinear safe algorithm
Infrared Safety?
• Adding an arbitrarily soft gluon to the event should not change the jets.
N i f d f j l i h b d i hi h d• Non-infrared-safe jet algorithms cannot be used in higher order
calculations.
if th i th i t t t th b t th• so if we use them in the experiment we cannot compare to the best theory
(at least without making some intermediate model-dependent correction).
Actually infrared instabilities undermine the claim of a jet algorithm to be• Actually, infrared instabilities undermine the claim of a jet algorithm to be
telling us about the short distance physics.
• We should also worry about sensitivity to arbitrarily low noise or arbitrarily• We should also worry about sensitivity to arbitrarily low noise, or arbitrarily
soft pions, for example.
• An example of an infrared instability is the “seed” in old cone algorithm
Jon Butterworth, UCL 39
• An example of an infrared instability is the seed in old cone algorithm.
But there are others (e.g. in the splitting/merging)
Precision Application• ZEUS Jet measurements
• 1% energy scale, kT algorithm
• Compared to NLO QCD, used in NLO
PDF fits
Extrapolation: A. Cooper-Sarkar,
Jon Butterworth, UCL 40
Extrapolation: A. Cooper Sarkar, C.Gwenlan, C.Targett-Adams, HERA-LHC Workshop, hep-ph/0509220
Jets for different applicationsJets for different applications• Our “hard” events will be complicated. Many hard jets, minijet vetos and
rapidity gaps. Several different hard scales in the event (pT, MW, Mt…
Mplanck???)Thi i h QCD b k d l l ti t ll h d d iti it t– This is when QCD background calculations get really hard, and sensitivity to soft effects and higher orders becomes critical.
– Clearly we will take as much background information as we can from the data but equally clearly there will still be a need for stable jet definitions anddata, but equally clearly there will still be a need for stable jet definitions, and for some modelling and comparison with theory • e.g. extrapolating the W pT from the Z pT at the Tevatron
C R it t d f d ibl & t bl d fi iti• Consequence: Reiterates need for a reproducible & stable definition
• Consequence: Our jet algorithms must be pretty fast even for very high
lti li iti
Jon Butterworth, UCL 41
multiplicities
Jets for different applicationsJets for different applications
• Our the environment our “hard” events are in will be complicated.– Underlying event and pile-up, not to mention experimental noise & efficiency
C O j l i h d b d i ki h• Consequence: Our jet algorithms need to be good at picking out the
“hard” physics.– Not just “reproducible” underlying event corrections but small onesNot just reproducible underlying event corrections, but small ones
Jon Butterworth, UCL 42
Jets for different applicationsJets for different applications
• Our high pT jets will sometimes have stuff in them (High pT top, W, Z,
Higgs, SUSY particles…)
• Consequence: Useful to have an algorithm which can be “unpicked”,
has a recombination scheme which conserves energy & momentum,
and is stable against soft physics.
Jon Butterworth, UCL 43
Available AlgorithmsAvailable Algorithms• “Cone” algorithms
– Generally seek to find geometric regions which maximise the momentum in a given region (often not actually a cone!)
– Sort of mimics the “event display + eye” method
• “Cluster” algorithms– Generally start from the smallest objects available, and perform an iterative
pair wise clustering to build larger objects (using either geometric orpair-wise clustering to build larger objects (using either geometric or kinematic properties of the objects)
– Sort of inverts the QCD parton shower idea
Jon Butterworth, UCL 44
Recombination SchemesRecombination Schemes• In principle can choose how to calculate the momentum of a (pseudo) jet
from its constituents
• In practice, two main possibilities used:
• Snowmass/ET scheme– ET = Σ(ET
i) ; η = Σ(Eti ηi)/Σ(ET)
F l j t f l ti l ( d idit idit E– Forces massless jets from massless particles (pseudorapidity=rapidity, ET = pT)
• Four-vector addition– Preserves mass information, although normally starts with massless objects– Care needed (pT or ET, η or y?)
Jon Butterworth, UCL 45
Cone algorithmsCone algorithms• “Simple” (snowmass) cone algorithm not fully specified
– Many subtly different algorithms go under the name “cone algorithm” (with or without the Snowmass badge).
– Often re-implemented and changed within each experiment, which is bad for inter-experiment comparison and for reproducibility.
– Solved by using an external package, e.g. fastJet (Cacciari & Salam)
• IterativeIterative– Find a cone,– Calculate the centroid– Redraw cone around the new centre– Recalculate centroid– Etc (look for stable solutions)
Jon Butterworth, UCL 46
( )
Cone algorithms• If they rely on a seed to start cone finding, and many older ones did, they
are not infrared safe.– Using midpoints of seeds as well helps, but only postpones the problem to
the next highest order.– Seedless cone algorithms (e.g. SiSCone, Salam & Soyez) now available.
• “Progressive Removal” type (as current in CMS)– start with the highest momentum seed (not colinear or IR safe!)
Fi d t bl d it– Find a stable cone and remove it– Continue
• Split/merge (as is the current “ATLAS cone”) Sp t/ e ge (as s t e cu e t S co e )– Find all stable cones.– If two stable cones overlap, merge if the overlap is > X (~ 50-75%) .
Otherwise assign energy to the higher p one
Jon Butterworth, UCL 47
Otherwise assign energy to the higher pT one.
Cone algorithmsCone algorithms• Geometrical localisation is appealing when mapping on to a real detector
(which is of course geometrically localised!)– Although note, the overlap issue means that the “cone” is not in fact regular,
especially in high multiplicity events.p y g p y– (Can be very large, in fact, depending on the split/merge treatment)– But its edges are fairly sharp.
• SiSCone does now provide a practical (i.e. fast enough) infrared safe &
seedless cone algorithm in public codeUsed a sliding window idea to find all possible stable cones– Used a sliding window idea to find all possible stable cones
– Has a split-merge step– arXiv:0704.0292[hep-ph], Salam & Soyez
Jon Butterworth, UCL 48
Cluster algorithms• Again, many possibilities
– Jade, kT, Cambridge/Aachen, Anti-kT , …– Each has a distance measure and merges the “closest” objects by this– Each has a distance measure, and merges the closest objects by this
measure until some criteria is reached (could be a specified multiplicity, or “distance”)
• Modern ones (k Cambridge anti k ) belong to a general class where• Modern ones (kT, Cambridge, anti-kT) belong to a general class where
the distance parameter is given as– p=1 for kT, 0 for Cam/Aachen, -1 for anti-kTp T T
• Can be very slow at high multiplicities– recently solved in fastJet (Cacciari & Salam, Phys.Lett.B641:57-61,2006)
• No seed needed
Jon Butterworth, UCL 49
• All objects assigned uniquely to one jet (no separate split/merge stage)
kT algorithm• Catani et al Phys Lett B269 (1991); Nucl. Phys. B406 (1993); Ellis and
Soper Phys Rev D48 (1993).
• p=1
• Successively merge objects with low relative kT
• If the k 2 of an object w r t the beam is lower than k 2 w r t anything elseIf the kT of an object w.r.t the beam is lower than kT w.r.t anything else
in the event divided by R2, don’t merge any more; call it a jet.
• Mimics (inverts) the QCD parton showerMimics (inverts) the QCD parton shower.
• Soft stuff merged into the nearest hard stuff.
• Can undo merging (Y splitter) Last merge is the hardest
Jon Butterworth, UCL 50
• Can undo merging (Y splitter). Last merge is the hardest.
Cambridge/Aachen algorithmg g• Dokshitzer, Leder, Morretti, Webber (JHEP 08 (1997) 01; Wobisch and
Wengler hep-ph/9907280
• p=0
• Successively merge objects with low relative Δ.
• Objects with Δ2 > R2 not mergedObjects with Δ > R not merged
• Can undo merging. Last merge is the hardest. Last merge is the furthest
away (so is often the softest)away (so is often the softest).
Jon Butterworth, UCL 51
Anti-kT algorithm• Cacciari, Salam, Soyez JHEP 0804:063,2008
• p=-1p 1
• Successively merge objects with high relative k• Successively merge objects with high relative kT
• dij is determined soley by the kT of the harder of i & j, and by Δ. Soft stuff
within R2 of a high k object will be merged with it If two hard jets arewithin R of a high kT object will be merged with it. If two hard jets are
close the energy will be shared based on Δ.
• Shape of jet is unaffected by soft radiationShape of jet is unaffected by soft radiation.
• Can undo merging (but I don’t yet understand quite what it would mean).
Jon Butterworth, UCL 52
Scales in the experiment• (1) Proton mass / becomes possible to accurately calculate using
perturbative QCD
● around 1 - 5 GeV.
• (2) W, Z mass / electroweak symmetry-breaking scale / Higgs
mass if it exists
● around 50-300 GeV
(3) LHC l O(10 T V)• (3) LHC scale O(10 TeV).
• Because of (3) the LHC is the first machine to produce copious
hi hl b t d ti l ith t l 2 hi hhighly-boosted particles with masses at scale 2, or very high
multiplicities of jets each at scale 2.
Jon Butterworth, UCL 53
Summary for JetsSummary for Jets
• We know a LOT more about QCD and jets now than did b f LEP HERA d th T twe did before LEP, HERA and the Tevatron
– Lots of important interaction between experiment and phenomenology at these machinesp gy
• The LHC is going into qualitatively unknown territory for QCD, never mind for everything else.
• We should take the best technology with us.
Jon Butterworth, UCL 54
Leptons and PhotonsLeptons and Photons
• Some issues similar to jets – Isolation from hadronic activity: define “activity”– Electrons in e+e-/DIS: QED initial state radiation
• “Radiative return” to the Z peak.El t h QED fi l t t di ti– Electrons anywhere: QED final state radiation• How photons were radiated? • Were they included in the electron object?y j• Best not to have an implicit cut based on your calorimeter
geometry.
Jon Butterworth, UCL 55
Leptons and PhotonsLeptons and Photons• In a MC comparison, take the “true”
l telectron– Large sensitivity to FSR
• Include photons within dR<0 2 of the• Include photons within dR<0.2 of the electron– Reduced sensitivityReduced sensitivity
• But what does the measurement correspond to? p
Jon Butterworth, UCL 56
Inclusive or exclusiveInclusive or exclusive• An inclusive “measurement” is often easy for the theorist,
but misleading
• More exclusive observables are harder to calculate predictions for but experimentally honest
• In general, avoid integrating into “different” regions where you have zero sensitivity (i.e. Φ is generally ok but not pT)
Jon Butterworth, UCL 57
Inclusive or exclusiveInclusive or exclusive• Many examples where errors new measurement just about bracket the
th t i ti b th th SAME THING!theory uncertainties: because they are the SAME THING!– e.g. early ZEUS D* measurement extrapolated to high y and low pT
– Or measured with jets, differential, in a region of good acceptancej g g p
Nucl.Phys.B729:492-525,2005
NLO from Frixione, Mangano, Nason, Ridolfi
Jon Butterworth, UCL 58
Rivet robustness and tuningRivet, robustness and tuning
Ri t “R b t I d d t V lid ti f E i t t• Rivet: “Robust Independent Validation of Experiment at Theory”
If ’t it A l i ti f it it’ b bl• If you can’t write a Analysis routine for it, it’s probably not a measurement.
• Advert > Hendrik Hoeth’s talk (Or Mike’s)• Advert -> Hendrik Hoeth s talk. (Or Mike s)
Jon Butterworth, UCL 59
InconclusionInconclusionThe separation between theory and experiment is not as p y pclear cut as one might think.
Clarity on the difference and as much separation asClarity on the difference and as much separation as possible is desirable in the measuring and analysing of data
Less separation is desirable between the communities working on these things!g g
Points of clear contact: jet definitions, Monte Carlo and exclusive calculations PDF fits EW effects may rise
Jon Butterworth, UCL 60
exclusive calculations, PDF fits. EW effects may rise again!)