Gabriele Cosmo
155 lines
6.1 KiB
Plaintext
155 lines
6.1 KiB
Plaintext
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Examples for event biasing
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--------------------------
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This directory includes example applications to demonstrate the usage of
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different biasing techniques supported in Geant4, or possible from the
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user applications.
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General remark to biasing
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-------------------------
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The tools provided for importance sampling (or geometrical splitting and
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Russian roulette) require the user to have a good understanding of the
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physics in the problem. This is because the user has to decide which
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particle types have to be biased, define the regions (physical volumes,
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replicas) and assign importances to that regions. If this is not done
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properly it can not be expected that the results describe a real
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experiment. The examples given here only demonstrate how to use the tools
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technically. They don't intend to produce physical correct results.
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General remark to scoring
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-------------------------
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A interface G4VPScorer is provided for the user. The user may create his
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own class to perform the desired scoring. The user defined class
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therefore should inherit from the interface G4VPScorer.
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There are two example scorers G4PScorer and G4PIScorer provided.
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When scoring is done in a "scoring" or in a "importance" geometry
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special action has to be taken to prevent counting of
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"collisions" with boundaries of the tracking geometry as interactions.
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This is differently handled when scoring is done in the tracking geometry.
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The scorers B01Scorer and B02Scorer show the difference in that case.
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The Scorer B06Scorer checks for consistency of importance and weight.
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Known problems
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In the following scenario it can happen that a particle is not
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biased and it's weight is therefore not changed even if it crosses
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a boundary where biasing should happen.
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The importance sampling creates particles on boundaries
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between volumes. If the GPIL method of a physical process returns
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0 as step length for a particle on a boundary and if the PostStepDoIt of
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that process changes the direction of the particle to go back in the
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former volume the biasing won't be invoked.
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This will produce particles with weights that do not correspondent to the
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importance of the current volumes.
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I. Examples for scoring without biasing
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=======================================
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I. 1. Example B01
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-----------------
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This example shows how to use scoring in the "tracking" geometry.
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It scores several values for neutrons for every physical volume
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in the tracking geometry.
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All scored values are printed after the running. In addition a more
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exclusive output of selected values is printed. The way the
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last output is produced shows how to extract certain values from all
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scored values.
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I. 2. Example B02
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-----------------
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This example shows how to use scoring in a "parallel" or "scoring"
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geometry. In this example a tracking and a scoring geometry is
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constructed. Gammas are scored in the scoring geometry. The scored values
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are dumped to the screen after the run. How to access the score values
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more exclusively is shown in example B01.
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II. Examples for biasing without scoring
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========================================
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II. 1. Example B03
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------------------
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This example shows how to use biasing in the "tracking" geometry.
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It does not do scoring. The importances are setup during the
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mass detector construction in the file:
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B03/src/B03DetectorConstruction.cc.
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II. 2. Example B04
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------------------
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This example shows how to use biasing according to a "parallel"
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or "importance" geometry. The importances are setup during the
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construction of the parallel geometry in the file:
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B04/src/B04ImportanceDetectorConstruction.cc.
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III. Examples for biasing and scoring
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=====================================
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III. 1. Example B05
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-------------------
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Biasing and Scoring in the "tracking" geometry.
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The importances are setup during the mass detector construction
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in the file: B05/src/B05DetectorConstruction.cc.
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Scoring is done with G4PIScorer from transportation. G4PIScorer
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scores several values for all the physical volumes of a geometry.
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It also checks that the importance value times track weight = 1,
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which should hold in "simple" cases.
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III. 2. Example B06
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-------------------
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Biasing and scoring in a "parallel" geometry.
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The importances are setup during the construction of the parallel geometry
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in the file B06/src/B06ImportanceDetectorConstruction.cc.
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Customised scorer B06Scorer and printer B06ScorePrinter are used.
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III. 3. Example B07
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-------------------
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Biasing neutrons and gammas in a "parallel" geometry.
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The physics list used in this example creates only processes for
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gammas and neutrons. Other particles that my be produced
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will have no processes and can therefore not produce
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any particles.
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The idea is to have the simulation performing somewhat like a
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transportation Monte Carlo that only knows about neutrons and gammas and
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is only used in a limited energy range.
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IV. Example for weight window sampling
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-------------------------------------
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IV.1 Example B08
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----------------
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This is an example using importance sampling and weight window biasing
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together with scoring in a parallel geometry. Only the sampler
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for importance, weight window sampling and scoring in a parallel geometry
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exists at the moment.
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The example setup:
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A 180 cm long concrete shield is divided into 18 cells of 10 cm each.
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The cells are created in a parallel geometry. Importance values
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can be applied via an init.mac file. Scoring is done according to the
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cells for neutrons and gammas.
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Since this example intents to show the weight window sampling
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the primary neutrons are created with the relatively high
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energy of 300 MeV. Neutrons with this energy
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penetrate the concrete (according to the chosen physics list)
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relatively easy. So no importance sampling would be necessary.
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The high energy is selected to show the effect of the weight window
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sampling. High energetic secondaries which are not importance sampled
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may create neutrons which have a weight different from the inverse of
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the importance in the cell. If a finite weight window is chosen this
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results in relative average weights of the tracks in a given cell not
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equal to one.
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If the upper and lower limit of the weight window is set to 1
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the relative weights are 1.
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