Simulation in HEP

Γιώργος Λεστάρης

Η Προσομοίωση στη Φυσική Υψηλών Ενεργειών

και ο ρόλος της στην αναζήτηση της αλήθειας

Θεολογία και Σύγχρονη Φυσική - 10/10/2014

Η Προσομοίωση στη Φυσική Υψηλών Ενεργειών και ο ρόλος της στην αναζήτηση της αλήθειας

What is simulation?

Simulation is the imitation of the operation of a real-world process or system over time.

— Wikipedia

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What is simulation?

Simulation is the imitation of the operation of a real-world process or system over time.

— Wikipedia

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Not necessarily real-world e.g.: fantasy games, SciFi movie effects, etc

Simulation in HEP

• Designing the detectors of the experiments

• Testing experiment software:

• simulator produces data even in the same form as the experiment’s triggers

4 Η Προσομοίωση στη Φυσική Υψηλών Ενεργειών και ο ρόλος της στην αναζήτηση της αλήθειας

Simulation model

A Model is a set of elements that are simulated and their behaviours/functions defined using mathematical formulas.

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Excerpt from FRITIOF model paper section 2.2 — appeared in Nuclear

Physics B, Vol. 281 (1987).


Simulation model


Each model has its use cases — no model

for everything.

Simulating pi- showers in a (simplified) detector of CERN Atlas experiment

and comparing energy response of two Geant4 models.

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Apprximation algorithmsComputation of model’s formulas can be hard:


Neuton’s root-finding method using fixed point iteration.

Approximation algorithms do compute an approximation of a value produced by complex mathematical formulas.

The more accurate the approximation, the slower the algorithm (program).

Monte carlo simulation

Sometime computing the model formulas is unfeasible even approximative

• or there is uncertainty dew to many degrees of freedom in the simulated system



Introducing randomness to the simulation

• “throwing a dice” every time we simulate something and introducing its value into the simulation result


Monte carlo simulationImportance of the random number generator

• if randomness is biased, results will be biased as well




Implication: simulation is not deterministic, i.e.: running the same program with the same input twice, won’t give the same result



• so we run many times

• thousands of runs, millions of simulated events

• and run analysis to merge the results and produce some statistical distributions

• from which we extract the valuesDistribution of total energy for 10K

simulated events in an Atlas (LHC experiment) calorimeter.

Running the simulations

As mentioned above we need to run our simulations thousands of times daily

• but running a simulation, especially with the high energies of LHC is resource hungry!

• so resource hungry that a lot of manpower is spent into micro-optimisations


Running the simulations…but that’s what friends are for:

• Worldwide LHC Computing Grid

• Hundreds of research centres and universities contribute their resources for the needs of WLCG users


Running the simulations

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• hundreds of thousands of “jobs” are executed daily in WLCG

• simulation and data analysis are the two larger fragments


Physics validation


In software engineering, validation answers the question: “does the program do what the client expects?”

Physics validation goes for the question: “does the simulation for well known processes produces results statistically close to the truth?”

Physics validation…and for the question: “did the new version broke something?”


Energy response for pi- shower on Atlas (LHC experiment) calorimeter, between two Geant4 versions

Conclusion• Simulation in HEP: important part of building

and testing the experiments

• Models in simulation

• Approximative methods

• Monte carlo simulation: adding randomness to the results

• Worldwide LHC computing grid and its importance into “getting the job done”

• Physics validation: is the simulation correct?


Simulation in HEP

Science

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