Difference: EventWeights (1 vs. 23)

Revision 23
21 Nov 2009 - Main.JennyHolzbauer
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META TOPICPARENT name="Trash.Trash/Tier3WebHome"

Event Weights for Monte Carlo Samples

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Added:
>
>

Weights for v15.5.1

We use weights from this website: https://twiki.cern.ch/twiki/bin/view/AtlasProtected/TopReferences10TeV. Note that the website recommendation is to multiply the cross-section by a factor that includes the k-factor as well as other factors.
 

Table of Weights

The following tables list the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section.
Revision 22
16 Oct 2009 - Main.TomRockwell
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Event Weights for Monte Carlo Samples

Introduction to Event Weights

Revision 21
13 Oct 2009 - Main.ChipBrock
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META TOPICPARENT name="WebHome"
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Event Weights for Monte Carlo Samples

Introduction to Event Weights

Revision 20
10 Oct 2008 - PatRyan
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Line: 33 to 33
 

Table of Weights

Changed:
<
<
The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section. In the 121403 MC version, run 1206, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.
>
>
The following tables list the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section.

For v13030, the column σ shows σ multiplied by the branching ratio.

Table for v13030

Run Sample Generator Matrix Element σ (pb) BR NEvents Weight
5200 ttbar->no_had Herwig+Jimmy MC@NLO 833.0 0.555 36708.0 1.25944
5500 Wt Pythia acerMC 66.0 0.333 4000.0 0.54945
5501 s-channel Phythia acerMC 10.65 0.333 10000.0 0.03546
5502 t-channel Phythia acerMC 246.0 0.333 38950.0 0.21032
6410 W->enu+2Jets Herwig+Jimmy Alpgen 826.0 1.0 208000.0 0.39712
6411 W->enu+3Jets Herwig+Jimmy Alpgen 239.0 1.0 43150.0 0.55388
6412 W->enu+4Jets Herwig+Jimmy Alpgen 67.4 1.0 36000.0 0.18722
6413 W->enu+5Jets Herwig+Jimmy Alpgen 24.0 1.0 3000.0 0.80000
6414 W->munu+2Jets Herwig+Jimmy Alpgen 826.0 1.0 212300.0 0.38907
6415 W->munu+3Jets Herwig+Jimmy Alpgen 236.0 1.0 17100.0 1.38012
6416 W->munu+4Jets Herwig+Jimmy Alpgen 68.3 1.0 51950.0 0.13147
6417 W->munu+5Jets Herwig+Jimmy Alpgen 24.3 1.0 0.0 1.00000

In the 121403 MC version, run 1206, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.
 

Table for Version 121403, weights calculated for 100pb-1

Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) BR NEvents Weight
5200 ttbar->no_had Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.555 401336.0 0.11519
Revision 19
08 Oct 2008 - PatRyan
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Event Weights for Monte Carlo Samples

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WNLO = WNLO / σLO ) = σNLOL/N0
Added:
>
>

Branching Ratio

If the MC samples were genereated to produce a certain final state, for example ttbar -> dileptons, then the branching ratio, BR, for that final state must be included in the weight calculation;

W = BRσL/N0
 

Sources of information

The information needed to calculate event weights were collected from the following places:
Line: 61 to 66
 

Table for Version 1213

Changed:
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<
File Sample Branching Ratio Cross-section Luminosity(pb-1) MC Events Weight
>
>
File Sample Cross Section Branching Ratio Luminosity(pb-1) MC Events Weight
 
5200 t-tbar -> lepton + jets and dilepton 872.8 0.555 100 592300 0.08178356
5200 t-tbar -> dilepton 872.8 0.111 100 117516 0.08244052
5200 t-bar -> lepton + jets 872.8 0.444 100 474784 0.08162095
Revision 18
23 Jul 2008 - PatRyan
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Introduction to Event Weights

Changed:
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<
When a Monte Carlo (MC) sample is generated the size of the sample is determined by requesting the generation of a certain number of events. The cross section of the sample is a fixed quantity dependent on the process generated. Since number of events, sample size, and luminosity are related according to σ = L/NEvents, the luminosity of a MC sample varies according to the number of events generated and the cross section of the process.
>
>
When a Monte Carlo (MC) sample is generated the size of the sample is determined by requesting the generation of a certain number of events. The cross section of the sample is a fixed quantity dependent on the process generated. Since number of events, sample size, and luminosity are related according to σ = NEvents/L, the luminosity of a MC sample varies according to the number of events generated and the cross section of the process.
 

The amount of data collected in an experiment is expressed in terms of luminosity since this quantity can be determined from known properties of the colliding beams. In order to perform a simulation of the data at given luminosity, it is necessary to weight the MC sample to correspond to this luminosity. This allows, for example, to predict the number of top events that will be produced in an amount of data corresponding to that luminosity.
Revision 17
18 Jun 2008 - Main.SarahHeim
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Introduction to Event Weights

Changed:
<
<
When a Monte Carlo (MC) sample is generated the size of the sample is determined by requesting the generation of a certain number of events. The cross section of the sample is a fixed quantity dependent on the process generated. Since number of events, sample size, and luminosity are related according to &sigma = L/NEvents, the luminosity of a MC sample varies according to the number of events generated and the cross section of the process.
>
>
When a Monte Carlo (MC) sample is generated the size of the sample is determined by requesting the generation of a certain number of events. The cross section of the sample is a fixed quantity dependent on the process generated. Since number of events, sample size, and luminosity are related according to σ = L/NEvents, the luminosity of a MC sample varies according to the number of events generated and the cross section of the process.
 

The amount of data collected in an experiment is expressed in terms of luminosity since this quantity can be determined from known properties of the colliding beams. In order to perform a simulation of the data at given luminosity, it is necessary to weight the MC sample to correspond to this luminosity. This allows, for example, to predict the number of top events that will be produced in an amount of data corresponding to that luminosity.
Revision 16
18 Jun 2008 - Main.SarahHeim
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Revision 15
18 Jun 2008 - Main.SarahHeim
Line: 1 to 1
 
META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Introduction to Event Weights

When a Monte Carlo (MC) sample is generated the size of the sample is determined by requesting the generation of a certain number of events. The cross section of the sample is a fixed quantity dependent on the process generated. Since number of events, sample size, and luminosity are related according to &sigma=L/NEvents, the luminosity of a MC sample varies according to the number of events generated and the cross section of the process.
Changed:
<
<
The amount of data collected in an experiemnt is expressed in terms of luminosity since this quantity can be determined from known properties of the colliding beams. In order to perform a simulation of the data at given luminosity, it is necessary to weight the MC sample to correspond to this luminosity. This allows, for example, to predict the number of top events that will be produced in an amount of data corresponding to that luminosity.
>
>
The amount of data collected in an experiment is expressed in terms of luminosity since this quantity can be determined from known properties of the colliding beams. In order to perform a simulation of the data at given luminosity, it is necessary to weight the MC sample to correspond to this luminosity. This allows, for example, to predict the number of top events that will be produced in an amount of data corresponding to that luminosity.
 

The weighting of the MC can be expressed as N = WN0, where N is the number of weighted events, N0 is the number of events in the original sample, and W is the weight. The weight must be a ratio of the desired luminsoity to the original luminosity of the sample, W = L/L0. Expressing the original luminosity in terms of cross section and number of events,
Revision 14
30 Jan 2008 - Main.JennyHolzbauer
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

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Table of Weights

Changed:
<
<
The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section. In the 121403 MC version, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.
>
>
The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section. In the 121403 MC version, run 1206, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.
 

Table for Version 121403, weights calculated for 100pb-1

Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) BR NEvents Weight
5200 ttbar->no_had Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.555 401336.0 0.11519
Revision 13
30 Jan 2008 - Main.JennyHolzbauer
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Line: 30 to 30
 

Table of Weights

The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section. In the 121403 MC version, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.

Table for Version 121403, weights calculated for 100pb-1

Changed:
<
<
Run Sample Generator Version Matrix Element &sigmaLO &sigmaNLO BR NEvents Weight
Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) BR NEvents Weight
>
>
Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) BR NEvents Weight
 
5200 ttbar->no_had Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.555 401336.0 0.11519
52001 ttbar->lep+jets Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.444 321720.0 0.11496
52002 ttbar->dilep Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.111 79616.0 0.11614
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Event Weights for Monte Carlo Samples

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Table of Weights

The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section. In the 121403 MC version, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.
Changed:
<
<

Table for Version 121403

Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) NEvents Lumi(pb-1) Weight
>
>

Table for Version 121403, weights calculated for 100pb-1

Run Sample Generator Version Matrix Element &sigmaLO &sigmaNLO BR NEvents Weight
Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) BR NEvents Weight
 
5200 ttbar->no_had Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.555 401336.0 0.11519
52001 ttbar->lep+jets Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.444 321720.0 0.11496
52002 ttbar->dilep Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.111 79616.0 0.11614
Revision 11
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

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Table of Weights

Changed:
<
<
The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section.
>
>
The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section. In the 121403 MC version, the W+Jets weights include branching ratio, alpgen matching efficiency and filtering efficiency.

Table for Version 121403

Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) NEvents Lumi(pb-1) Weight
5200 ttbar->no_had Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.555 401336.0 0.11519
52001 ttbar->lep+jets Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.444 321720.0 0.11496
52002 ttbar->dilep Herwig+Jimmy 12000601 MC@NLO 830.63 833.0 0.111 79616.0 0.11614
5500 Wt Pythia 12000601 acerMC 80.1 66.0 0.333 48350.0 0.04546
5501 s-channel Phythia 12000601 acerMC 9.9 10.65 0.333 48300.0 0.00734
5502 t-channel Phythia 12000601 acerMC 243.9 246.6 0.333 41428.68 0.19821
6210 W+0Jets Herwig+Jimmy 12000604 Alpgen 731.62 0.0 0.0 364950.0 0.20047
6211 W+1Jets Herwig+Jimmy 12000604 Alpgen 6249.0 0.0 0.0 896949.0 0.69670
6212 W+2Jets Herwig+Jimmy 12000604 Alpgen 2021.45 0.0 0.0 630834.0 0.32044
6213 W+3Jets Herwig+Jimmy 12000604 Alpgen 818.0 0.0 0.0 133046.0 0.61482
 
Added:
>
>

Table for Version 1214

 
Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) NEvents Lumi(pb-1) Weight
005001 minBias Phythia 11004103 - - 80 - 5.00E+05 6.25E-06 5000 160000000.0
005200 ttbar->no_had Herwig+Jimmy 11000505 MC@NLO 0.54 461 - 5.00E+05 1.08E+003 598700 0.925926
Revision 10
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

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Table for Version 1213

Changed:
<
<
file Branching Ratio Cross-section Luminosity MC Events Weight
5200 (t-tbar -> lepton + jets and dilepton) 872.8 0.555 100 592300 0.08178356
5200 (t-tbar -> dilepton) 872.8 0.111 100 117516 0.08244052
5200 (t-bar -> lepton + jets) 872.8 0.444 100 474784 0.08162095
5500 (Wt) 62.1 1/3 100 48350 0.0428128
5501 (tb) 10.65 1/3 100 48050 0.0073881
5502 (tq) 246.6 1/3 100 43950 0.1870307
>
>
File Sample Branching Ratio Cross-section Luminosity(pb-1) MC Events Weight
5200 t-tbar -> lepton + jets and dilepton 872.8 0.555 100 592300 0.08178356
5200 t-tbar -> dilepton 872.8 0.111 100 117516 0.08244052
5200 t-bar -> lepton + jets 872.8 0.444 100 474784 0.08162095
5500 Wt 62.1 1/3 100 48350 0.0428128
5501 s-channel (tb) 10.65 1/3 100 48050 0.0073881
5502 t-channel (tq) 246.6 1/3 100 43950 0.1870307
 

Revision 9
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Event Weights for Monte Carlo Samples

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file Branching Ratio Cross-section Luminosity MC Events Weight
5200 (t-tbar -> lepton + jets and dilepton) 872.8 0.555 100 592300 0.08178356
5200 (t-tbar -> dilepton) 872.8 0.111 100 117516 0.08244052
Changed:
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<
5200 (t-bar -> lepton + jets 872.8 0.444 100 474784 0.08162095
>
>
5200 (t-bar -> lepton + jets) 872.8 0.444 100 474784 0.08162095
 
5500 (Wt) 62.1 1/3 100 48350 0.0428128
5501 (tb) 10.65 1/3 100 48050 0.0073881
5502 (tq) 246.6 1/3 100 43950 0.1870307
Revision 8
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Event Weights for Monte Carlo Samples

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008204 W->mv(4parton_exe) Herwig+Jimmy 11004206 ALPGEN - 28.4 - 1.50E+04 16.2E+003 18050 0.061728
Added:
>
>
 

Table for Version 1213

file Branching Ratio Cross-section Luminosity MC Events Weight
Changed:
<
<
5200 (t-tbar) 872.8 0.555 100 592300 0.08178356
>
>
5200 (t-tbar -> lepton + jets and dilepton) 872.8 0.555 100 592300 0.08178356
5200 (t-tbar -> dilepton) 872.8 0.111 100 117516 0.08244052
5200 (t-bar -> lepton + jets 872.8 0.444 100 474784 0.08162095
 
5500 (Wt) 62.1 1/3 100 48350 0.0428128
5501 (tb) 10.65 1/3 100 48050 0.0073881
5502 (tq) 246.6 1/3 100 43950 0.1870307
Revision 7
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Line: 47 to 47
 

Table for Version 1213

Changed:
<
<
file Branching Ratio Cross-section Luminosity MC Events Weight 5200 (t-tbar) 872.8 0.555 100 592300 0.08178356
>
>
file Branching Ratio Cross-section Luminosity MC Events Weight
5200 (t-tbar) 872.8 0.555 100 592300 0.08178356
 
5500 (Wt) 62.1 1/3 100 48350 0.0428128
5501 (tb) 10.65 1/3 100 48050 0.0073881
5502 (tq) 246.6 1/3 100 43950 0.1870307
Deleted:
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<
-- PatRyan - 19 Feb 2007 -- JennyHolzbauer - 01 Aug 2007
  \ No newline at end of file
Added:
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>
-- PatRyan - 19 Feb 2007, -- JennyHolzbauer - 01 Aug 2007
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Revision 6
01 Aug 2007 - Main.JennyHolzbauer
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Line: 46 to 46
 
008204 W->mv(4parton_exe) Herwig+Jimmy 11004206 ALPGEN - 28.4 - 1.50E+04 16.2E+003 18050 0.061728
Added:
>
>

Table for Version 1213

file Branching Ratio Cross-section Luminosity MC Events Weight 5200 (t-tbar) 872.8 0.555 100 592300 0.08178356
5500 (Wt) 62.1 1/3 100 48350 0.0428128
5501 (tb) 10.65 1/3 100 48050 0.0073881
5502 (tq) 246.6 1/3 100 43950 0.1870307
 

-- PatRyan - 19 Feb 2007 \ No newline at end of file
Added:
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>
-- JennyHolzbauer - 01 Aug 2007
  \ No newline at end of file
Revision 5
27 Jul 2007 - PatRyan
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META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Introduction to Event Weights

Changed:
<
<
The general formula for event weights is W = σL/NEvents, where σ is the cross section of the generated process, L is the generated luminosity of the MC sample, and NEvents is the number of generated events.
>
>
When a Monte Carlo (MC) sample is generated the size of the sample is determined by requesting the generation of a certain number of events. The cross section of the sample is a fixed quantity dependent on the process generated. Since number of events, sample size, and luminosity are related according to &sigma=L/NEvents, the luminosity of a MC sample varies according to the number of events generated and the cross section of the process.
 
Changed:
<
<
The MC samples we are using were generated with the correct weights and therefore in the simplest case we would not have to weight our events. However, the weighting of events is desired in the following cases:
>
>
The amount of data collected in an experiemnt is expressed in terms of luminosity since this quantity can be determined from known properties of the colliding beams. In order to perform a simulation of the data at given luminosity, it is necessary to weight the MC sample to correspond to this luminosity. This allows, for example, to predict the number of top events that will be produced in an amount of data corresponding to that luminosity.
 
Changed:
<
<

NLO vs. LO

All the MC samples were genereated using a LO cross section prediction. For the single top processes (s, t, and Wt channels), the cross sections are known to NLO and the weights are scaled by a ratio of NLO to LO cross sections to reflect this.
>
>
The weighting of the MC can be expressed as N = WN0, where N is the number of weighted events, N0 is the number of events in the original sample, and W is the weight. The weight must be a ratio of the desired luminsoity to the original luminosity of the sample, W = L/L0. Expressing the original luminosity in terms of cross section and number of events,

W = σL/N0.
 
Changed:
<
<
Wnew = (σNLOLO)W.
>
>
All histograms are weighted by multiplying the quantity used to fill the histogram (N, pT, eta, etc) by the event weight. In the MSU analysis code, the actual weighting takes place in the method myTH1F::Fill().
 
Changed:
<
<

Predictions for a certain amount of Data

We would like to determine how many single top events we will see in 1fb-1 of data. This is achieved by scaling the weight by the ratio of 1fb-1 to the generated luminosity, L (1fb-1 = 1000pb-1).
>
>

NLO vs. LO

All the MC samples were genereated using a LO cross section prediction. For the single top (s, t, and Wt channels) ttbar processes, the cross sections are known to NLO. In this case the weight is scaled by the ratio of NLO to LO cross sections
 
Changed:
<
<
Wnew = (1000 pb-1/L)W.
>
>
WNLO = WNLO / σLO ) = σNLOL/N0
 

Sources of information

Changed:
<
<
The information (cross sections, luminosities, etc) needed to calculate event weights were collected from the following places:
>
>
The information needed to calculate event weights were collected from the following places:
 
Line: 27 to 28
 

Table of Weights

Changed:
<
<
The following table lists the properties of the MC samples used in the Single Top analysis. The weight was calculated by the formula W = (1000pb-1). In addition, for the single top channels (s, t, and Wt), the weight was scaled by the ratio (σNLO / σLO).
>
>
The following table lists the properties of the MC samples used in the Single Top analysis. The weights for the single top channels (s, t, and Wt) and ttbar channels were calculated using the NLO cross section.
 
Changed:
<
<
Run Sample Generator Version Matrix_Ele Filter σLO(pb) σNLO(pb) NEvents Lumi(pb-1) NEventsMeasured Weight
>
>
Run Sample Generator Version Matrix_Ele σLO(pb) σNLO(pb) NEvents Lumi(pb-1) Weight
 
005001 minBias Phythia 11004103 - - 80 - 5.00E+05 6.25E-06 5000 160000000.0
005200 ttbar->no_had Herwig+Jimmy 11000505 MC@NLO 0.54 461 - 5.00E+05 1.08E+003 598700 0.925926
005204 ttbar->all_had Herwig+Jimmy 11004206 MC@NLO 0.46 369 - 2.00E+05 5.42E+002 77600 1.845018
Revision 4
20 Feb 2007 - PatRyan
Line: 1 to 1
 
META TOPICPARENT name="WebHome"

Event Weights for Monte Carlo Samples

Line: 26 to 26
 
Added:
>
>

Table of Weights

The following table lists the properties of the MC samples used in the Single Top analysis. The weight was calculated by the formula W = (1000pb-1). In addition, for the single top channels (s, t, and Wt), the weight was scaled by the ratio (σNLO / σLO).

Run Sample Generator Version Matrix_Ele Filter σLO(pb) σNLO(pb) NEvents Lumi(pb-1) NEventsMeasured Weight
005001 minBias Phythia 11004103 - - 80 - 5.00E+05 6.25E-06 5000 160000000.0
005200 ttbar->no_had Herwig+Jimmy 11000505 MC@NLO 0.54 461 - 5.00E+05 1.08E+003 598700 0.925926
005204 ttbar->all_had Herwig+Jimmy 11004206 MC@NLO 0.46 369 - 2.00E+05 5.42E+002 77600 1.845018
005205 ttbar->lep+jet Pythia 11004206 acerMC - 460 - 5.00E+05 - 434650 -
005223 W->ev(2parton_exe) Herwig+Jimmy 11004206 ALPGEN - 504 - 1.50E+04 8.24E+003 4000 0.121359
005224 W->ev(3parton_exe) Herwig+Jimmy 11004206 ALPGEN - 122 - 1.50E+04 6.58E+003 15200 0.151976
005225 W->ev(4parton_exe) Herwig+Jimmy 11004206 ALPGEN - 28.4 - 1.50E+04 16.3E+003 15200 0.061350
005226 W->ev(5patron_inc) Hewwig+Jimmy 11004206 ALPGEN - 6.1 - 1.50E+04 10.0E+003 7000 0.100000
005500 Wt Pythia 11000505 acerMC - 26.7 22.0 1.00E+04 3.75E+002 72600 2.197253
005501 s-channel Phythia 11004209 acerMC - 3.3 3.55 1.00E+04 3.03E+003 82950 0.355036
005502 t-channel Phythia 11004207 acerMC - 81.3 82.2 1.00E+04 1.23E+002 8400 8.220082
008203 W->mv(3parton_exe) Herwig+Jimmy 11004206 ALPGEN - 122 - 1.50E+04 7.91E+003 5000 0.126422
008204 W->mv(4parton_exe) Herwig+Jimmy 11004206 ALPGEN - 28.4 - 1.50E+04 16.2E+003 18050 0.061728
 

-- PatRyan - 19 Feb 2007 \ No newline at end of file
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19 Feb 2007 - PatRyan
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Event Weights for Monte Carlo Samples

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Wnew = (1000 pb-1/L)W.
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Sources of information

The information (cross sections, luminosities, etc) needed to calculate event weights were collected from the following places:
 

-- PatRyan - 19 Feb 2007 \ No newline at end of file
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META TOPICPARENT name="WebHome"
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Event Weights info here
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Event Weights for Monte Carlo Samples

Introduction to Event Weights

The general formula for event weights is W = σL/NEvents, where σ is the cross section of the generated process, L is the generated luminosity of the MC sample, and NEvents is the number of generated events.

The MC samples we are using were generated with the correct weights and therefore in the simplest case we would not have to weight our events. However, the weighting of events is desired in the following cases:

NLO vs. LO

All the MC samples were genereated using a LO cross section prediction. For the single top processes (s, t, and Wt channels), the cross sections are known to NLO and the weights are scaled by a ratio of NLO to LO cross sections to reflect this.

Wnew = (σNLOLO)W.

Predictions for a certain amount of Data

We would like to determine how many single top events we will see in 1fb-1 of data. This is achieved by scaling the weight by the ratio of 1fb-1 to the generated luminosity, L (1fb-1 = 1000pb-1).

Wnew = (1000 pb-1/L)W.
 

 
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