Durham University. Monte Carlo Event Generators. Lecture 1: Basic Principles of Event Generation. Peter Richardson IPPP, Durham University. So the title I was given for these lectures was ‘Event Generator Basics’
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Durham University
Monte Carlo Event Generators
Lecture 1: BasicPrinciples of Event Generation
Peter Richardson
IPPP, Durham University
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‘Event Generator Basics’
‘Why I Shouldn’t Just Run PYTHIA’
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http://www.thep.lu.se/~torbjorn and then Talks
http://seymour.home.cern.ch/seymour/slides/CERNlectures.html
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http://www.phys.psu.edu/~cteq/schools/summer04/mrenna/mrenna.pdf
http://wwwcdf.fnal.gov/physics/lectures/herwig_Oct2004.html
http://arxiv.org/pdf/hepph/0403045
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Today we will cover
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where
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However only if the derivatives exist and are finite. Otherwise the convergence of the Trapezium or Simpson’s rule will be worse.
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where
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which gives
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and the weight is
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Generate flat in m2
Generate using transform
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where ai is the weight for a given term such that Sai=1.
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which is easy to implement by generating a random number between 0 and 1 and keeping the value of x if the random number is less than the probability.
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2
=
n
n1
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Hard Perturbative scattering:
Usually calculated at leading order in QCD, electroweak theory or some BSM model.
Modelling of the soft underlying event
Multiple perturbative scattering.
Perturbative Decays calculated in QCD, EW or some BSM theory.
Initial and Final State parton showers resum the large QCD logs.
Finally the unstable hadrons are decayed.
Nonperturbative modelling of the hadronization process.
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1
1
1
1
1
1
1
A
A
A
A
B
B
B
n
n
n
n
n
n
n
2
2
2
1
+
B
+
+
n
*
*
*
*
There are a number of ways of calculating the matrix element
=
+
+
+
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1
A
n
2
1
+
B
+
n
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1
l+1
=
1
1
+
n
m
m+1
m
l
m+1
n
n
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+

+

+
+
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+
+

+


+
+

+


+
=
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Faster
Faster
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