Les Houches SM and NLO multi-leg group: experimental introduction and

chargeG. Heinrich, J. Huston, J. Maestre, D. Maitre, R. Pittau,

G. Soyez (jet liason)

Understanding cross sections at the LHC

PDF’s, PDF luminositiesand PDF uncertainties

Sudakov form factorsunderlying eventand minimumbias events

LO, NLO and NNLO calculations K-factors

jet algorithms and jet reconstruction

benchmark cross sections and pdfcorrelations

We’ll be dealing with all of these topics in this session,in the NLM group, in the Tools/MC group and in overlap.

Understanding cross sections at the LHC

We’re all looking for BSM physics at the LHC

Before we publish BSM discoveries from the early running of the LHC, we want to make sure that we measure/understand SM cross sections detector and reconstruction

algorithms operating properly SM physics understood

properly especially the effects of

higher order corrections SM backgrounds to BSM

physics correctly taken into account

This is the first Les Houches at which we have LHC data to test in addition to a plethora of

data from the Tevatron, including some mysteries

List of topics (from web page)

Higher order calculations and techniques->Roberto’s talk Public computational tools/templates->(mostly) Roberto’s talk NLO/PS matching (joint with Tools/MC WG)->(mostly) Roberto’s

talk Jetology

jet observables boosted object tagging connections/differences between LO, NLO and MC jet

clustering for complex n-parton final states variations in NLO multi-parton cross sections with jet

algorithms, jet sizes and scales Higgs observables To this, I would add PDFs (also in parallel with Tools/MC group I

would say)

We had 3 evo pre-meetings

May 6: HO computations and techniquesMay 13: JetologyMay 20: Higgs observables

Start with the wishlist Began in 2005, added to in 2007 and

2009 only process 12 left among NLO

Are there other motivated needs for NLO multi-parton final states? from dedicated calculation or

automatic calculation? one thing we promised to do last

Les Houches is provide a table of the needed accuracy for each final state

Should we move on to expanding the NNLO list?

There’s also the issue of how experimentalists can use these calculations aMC@NLO: but what is the

learning curve to get to say W + 3,4 jets at NLO

ntuples more practical for immediate future, i.e. before next Les Houches?

Calculations

Once we have the calculations, how do we (experimentalists) use them?

If a theoretical calculation is done, but it can not be used by any experimentalists, does it make a sound?

We need public programs and/or public ntuples

Example: Blackhat+Sherpa ntuples

Born loop: lc and fmlc real

vsub

so this is not Sherpa the parton shower,but Sherpa usedas a (very efficient) fixed order matrix elementgenerator

How it’s put together

Born loop: lc and fmlc real

vsub

for W+3 jets,W+3 parton tree-levelmatrix elements

all of the virtual terms, both leading color and full-minus-leading color; the latter is typically a few % effect, but much of the complexity of the calculation

all of the real emission terms,(W+4 partons for W + 3 jets), modified by the dipole subtraction terms; divergences are gone

the dipole subtraction termsevaluated in n-body phase space; to make matters more complex,vsub can be either + or -,compensated by otherterms in the total crosssection; note the sum over all quarks andantiquarks; makes mattersmore complex when coming to scale uncertainties

ROOT ntuples More complex to use than MCFM

no manual for example and you don’t produce the events

yourself my student Brian Martin and I are

the beta users ntuples produced separately by

Blackhat + Sherpa for No jet clustering has been performed;

that’s up to the user a difference from MCFM, where

the program has to be re-run for each jet size/algorithm

What algorithms/jet sizes that can be run depends on how the files were generated i.e. whether the right counter-

events are present For the files on the right at 7 TeV (for

W+ + 3 jets), one can use kT, antikT, siscone (f=0.75) for jet sizes of 0.4, 0.5, 0.6 and 0.7

bornLO (stands alone for pure LO comparisons; not to be added with other contributions below) 20 files, 5M events/file, 780

MB/file Born

18 files, 5M events/file, 750 MB/file

loop-lc (leading color loop corrections) 398 files, 100K events/file, 19

MB/file loop-fmlc (needed for full color loop

corrections) 399 files, 15K events/file, 3

MB/file real (real emission terms)

169 files, 2.5 M event/file, 5 GB/file

vsub (subtraction terms) 18 files, 10M events/file, 2.8

GB/file

Jet Clustering

For jet clustering, we use SpartyJet, and store the jet results in SJ ntuples and they tend to be big

since we store the results for multiple jet algorithms/sizes

Then we friend the Blackhat+Sherpa ntuples with the SpartyJet ntuples producing analysis ntuples (histograms with cuts) for each of the event categories

Add all event category histograms together to get the plots of relevant physical observables

http://projects.hepforge.org/spartyjet/

If interested, please contactBrian.thomas.martin@cern.ch

Logistics

So total file disk space is quite large, multi-TB (and there are many events to be processed) I bought a 20TB disk specifically for this

purposeBut they’re divided into few GB files

(Blackhat+SJ)So we can make our analysis parallel using

350 nodes at MSUPossible to run through W + 3 jet NLO analysis

in few days (much faster without the scale variations) somewhat longer with more variations included

…so for example

W+ + 3 jets at 7 TeV for standard cuts (plus for electron cuts) |ym|<2.4

pTm>20 GeV/c

pTn> 25 GeV/c

PTjet>20 GeV/c

|yjet|<2.8

mT(m,n)>40 GeV

New cuts or histograms means re-running through the ntuples

For antikT4 born: 22.69 pb loop-lc: -0.69 pb loop-fmlc: 0.39 pb vsub: 27.16 pb real: -17.34 pb Total: 32.21 pb

Predictions

From Blackhat+Sherpa, we have ntuples (in same format) for W + 1,2, 3,4 jets

Makes it easy to make plots for different jet multiplicities and/or combined jet multiplicities including PDF uncertainties including scale uncertainties

would like to explore a CKKW-like scale at NLO at Les Houches

examining dependence on jet size/algorithm

Lead jet pT

Scale dependence

Factorization and renormalization scale dependence for any cross section can be calculated (relatively easily) independent of the evaluation of the full matrix element, if you’re careful to collect the relevant terms

In new version of Blackhat+Sherpa ntuples, they were careful to collect the relevant terms

Reweighting

can reweight each event tonew

-PDF-factorization scale-renormalization scale-as (tied to the relevant

PDFs)

based on weights stored in ntuple (and linking with LHAPDF)

so, for example, the events were generated with CTEQ6,and were re-weighted to CTEQ6.6

Reweighting, cont.

complex:carry both single and doublelogs

we run into thesum over quarksand antiquarksagain

9

PDF Errors

Better than what is done in MCFM (as far as disk space is concerned); PDF errors aregenerated on-the-fly through calls to LHAPDF. But then don’t store information for individual eigenvectors.

Example scale/PDF uncertainty

LO at thispoint for 4 jets

…calculated using ntuples

LO/NLO predictions for jet cross sections

Don’t believe (fixed) LO predictions for jet cross sections

Let’s look at predictions for W+ + 3 jets for two different jet algorithms as a function of jet size at the LHC (7 TeV)

At LO, both antikT and SISCone show a marked decrease in cross section as the jet size increases because of the log(1/DR)

terms But at NLO, the two cross

sections show little dependence on the jet size, and are similar to each other due to addition of extra gluon

in jet possible at NLO You’ll see the same thing in

ATLAS Monte Carlo

note NLO~LO because a scale of HT

has been used; if a scale like mW

2+pTW2 is used K-factor <<1

Blackhat + Sherpa

Predictions for jet cross sections

Compare to ATLAS ALPGEN+PYTHIA samples for jet sizes of 0.7

At parton level, antikT is ~25%higher than SISCone (same aswe observe here at LO)

At topocluster level, antikT is~2% higher than SISCone (not the 7% observed here)

Why 2%, not 7%? Some of the W + 3 partonevents reconstructed as 2 jets at the parton level forSISCone are reconstructed as3 jets at the hadron. The crosssection for 3 jets increases.

Try this out in ATLAS/CMS Monte Carlo

Take W + 2 parton events (ALPGEN+PYTHIA), run SISCone 0.7 algorithm on parton level, hadron level (not shown) and topocluster level

Plot the probability for the two sub-jets to merge as a function of the separation of the original two partons in DR

Color code: red: high probability for merging blue: low probability for merging everything for DR<0.7 is merged

for SISCone (and antikT) Parton level reconstruction agrees

with naïve expectation Topocluster level reconstruction

agrees with need for Rsep

I’d like to come to some resolution/better understanding on this issue at Les Houches, using a standardized file of W + jets events

Choosing jet size

Experimentally in complex final

states, such as W + n jets, it is useful to have jet sizes smaller so as to be able to resolve the n jet structure

this can also reduce the impact of pileup/underlying event

Theoretically hadronization effects

become larger as R decreases

for small R, the ln R perturbative terms referred to previously can become noticeable

this restriction in the gluon phase space can affect the scale dependence, i.e. the scale uncertainty for an n-jet final state can depend on the jet size,

…to be investigated

Another motivation for the use of multiple jet algorithms/parameters in LHC analyses. Can we explore this further?

Jet sizes and scale uncertainties: the Goldilocks theorm

Take inclusive jet production at the LHC for transverse momenta of the order of 50 GeV

Look at the theory uncertainty due to scale dependence as a function of jet size

It appears to be a minimum for cone sizes of the order of 0.7 i.e. if you use a cone size of 0.4, there are residual un-

cancelled virtual effects if you use a cone size of 1.0, you are adding too much tree

level information with its intrinsically larger scale uncertainty

This effect becomes smaller for jet pT values on the order of 100 GeV/c how does it translate for multi-parton final states? …good subject for investigation here

Scale choices

Take inclusive jet production at the LHC

Canonical scale choice is mr=mf=1.0*pT

Close to saddle point for low pT

But saddle point moves down for higher pT

Can we think about recommendations for scale choices (and ranges) for the LHC?

I know there is worry about typical scale choices that can lead to negative cross sections, for example at very forward rapidities

Rather than look for some magic formula, we should try to understand what is going on the kinematic/scale point-of-view

R=0.4antikT

Scale dependence also depends on jet size

R=0.4antikT

R=0.6antikT

One scheme F. Olness and D. Soper,

arXiv:0907.5052 Define x1 and x2

Make a circle of radius |x|=2 around a central scale (could be saddle point, or could be some canonical scale) and evaluate the scale uncertainty

AJ and MJK carry information on thescale dependence beyond NLO

col

Fred is here,so maybewe can explore thisfurther, comparingto the LHCdata

Another scheme

Higgs Cross Section Working GrouparXiv:1101.0593

Scale dependence: jet algorithms

Look at results for SISCone/antikT; antikT cross sections larger than SISCone, smaller scale dependence?

H. Ita, SLAC Hadronic Final State Forum

Z + 3 jets: scale dependence

Note that peak cross sections are actually quite close; the cross sections just peakat different scales.

1004.1659Can we understand/quantify this better? For LHC cross sections.

Scales: CKKW and NLO

Applying a CKKW-like scale at LO also leads to better agreement for shapes of kinematic distributions

(Partially) investigated at last Les Houches; needs more work at this Les Houches

0910.3671 Melnikov, ZanderighiSee review of W + 3 jets in Les Houches2009 NLM proceedings

Jet vetos For some cross sections, the scale dependence improves with a jet veto,

and in others the scale dependence worsens I think it would be worthwhile to collect this information And of course, these conclusions are drawn from using fixed order

predictions only

WWjet tTbB

Uncertainties for Higgs production with jet binning

…large logs result fromjet vetoing

naïve scalevariation may provide toosmall an estimate of scale uncertainty

have to resum these logs;can re-weight MC@NLOor Powheg using thisinformation

maybe we can generalizeto other processes at the LHC

F. Tackmann May 20 evo

CDF Wjj Potentially an important

discovery, but are current tools capable of modelling the W + jets background precisely enough

Session on Saturday afternoon

You know that it’s important when it makes it to prime-time TV

…if you paid close attention

CDFWjjanalysiscuts

LHC jets ATLAS and CMS are both

using an IR-safe jet algorithm (anti-kT)

Unfortunately no common sizes 0.4 and 0.6 for ATLAS 0.5 and 0.7 for CMS

It would be nice to have at least one common

jet size exploit any capability to

perform analyses with multiple jet sizes/algorithms

ATLAS topoclusters have the potential to allow for more flexibility in jet analyses

Should be similar potential in CMS with particle flow, etc

UE/pileup corrections: Jet areas

note that the kT

algorithm hasthe largest jet areas, SISConethe smallest and anti-kT the most regular; one of the reasons we like the antikt

determined byclustering ghostparticles of vanishing energy;see jet references

Jets: area-based correction: Cacciari/Salam/Soyez

Used by both ATLAS and CMS. Can we understand what works/what needs improvement in the light of LHC data with significant pileup?

Aside: Photon isolation at the LHC

From a theoretical perspective, it’s best to apply a Frixione-style isolation criterion, in which the amount of energy allowed depends on the distance from the photon; this has the advantage of removing the fragmentation contribution for photon production, as well as discriminating against backgrounds from jet fragmentation

But most of the energy in an isolation cone is from underlying event/pileup At Les Houches, we started to develop (being continued by Mike Hance, Brian,…in

ATLAS): (1) an implementation of the Frixione isolation appropriate for segmented

calorimeters (2) a hybrid technique that separates the UE/pileup energy from fragmentation

contributions using the jet density approach

more developmentat this Les Houches?

Jets at parton level and in (NLO) MC

…from Jet Pair Production in Powheg, arXiv:1012.3380

note that theory/datahas a slope notevident with fixedorder comparisons(NLO corrected byUE/hadronization)

also observed inATLAS comparisons;differences observedwhen using Pythia asshower instead of Herwig

an effect we need tounderstand; this will affect all global PDF fits, for example; Les Houches is a good place to do it

PDFs We’ve learned a lot from the PDF4LHC exercises In particular, we’ve seen where the PDFs agree and where they don’t The exercise was at NLO; now we are in a position to continue it at NNLO

Plots by G. Watt

…as well as to start adding LHC data

…and alreadyseeing differences between Experiments

Note that resummed predictions areimportant

PDF correlations Consider a cross section X(a), a

function of the Hessian eigenvectors ith component of gradient of X is

Now take 2 cross sections X and Y or one or both can be pdf’s

Consider the projection of gradients of X and Y onto a circle of radius 1 in the plane of the gradients in the parton parameter space

The circle maps onto an ellipse in the XY plane

The angle f between the gradients of X and Y is given by

The ellipse itself is given by

• If two cross sections are verycorrelated, then cosf~1• …uncorrelated, then cosf~0• …anti-correlated, then cosf~-1

…from PDF4LHC report

Correlations, continued…

one interesting angle to calculateis the angle between the gradientfor a particular physics processand the hyperplane formed by thefirst n eigenvectors

take gg->Higgs (120 GeV)

eigenvector cos f =1 0.028<=2 0.077<=3 0.077<=4 0.534 <=5 0.551<=6 0.553<=7 0.602<=8 0.604<=9 0.609<=10 0.808<=11 0.808

so very strong correlation (0.8) between the Higgs crosssection and the hyperplane formed by the first 11 (of 22)eigenvectors in CTEQ6.6

low number eigenvectors have quadratic c2 behavior

Being used by Higgs combination groups

Can we extend this use?

Summary

Due to lack of time, haven’t mentioned boosted jets/analyses, but clearly this is an important aspect of this workshop some people are coming straight from

BOOST2011 There are a lot of interesting physics

topics at this Les Houches, as well as LHC data (for the first time) and greatly improved NLO technology

It should be an interesting week and a half