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0001 \page Examples_biasing Category "biasing"
0002
0003 ## B01, B02 and B03
0004
0005 B01, B02 and B03 applications demonstrate the usage of different variance
0006 reduction techniques supported in Geant4, or possible from the user
0007 applications.
0008
0009 ### General remark to variance reduction
0010
0011 The tools provided for importance sampling (or geometrical splitting and
0012 Russian roulette) and for the weight window technique require the user to
0013 have a good understanding of the physics in the problem. This is because
0014 the user has to decide which particle types have to be biased, define the
0015 cells (physical volumes, replicas) and assign importances or weight
0016 windows to that cells. If this is not done properly it can not be
0017 expected that the results describe a real experiment. The examples given
0018 here only demonstrate how to use the tools technically. They don't intend
0019 to produce physical correct results.
0020
0021 ### General remark to scoring
0022
0023 Scoring is carried out using the built-in Multifunctional detectors. For
0024 parallel geometries this requires a special scoring physics process.
0025 See examples/extended/runAndEvent (especailly RE05) for clarification.
0026
0027 ### Known problems - should not happen
0028
0029 In the following scenario it can happen that a particle is not
0030 biased and it's weight is therefore not changed even if it crosses
0031 a boundary where biasing should happen.
0032 Importance and weight window sampling create particles on boundaries
0033 between volumes. If the GPIL method of a physical process returns
0034 0 as step length for a particle on a boundary and if the PostStepDoIt of
0035 that process changes the direction of the particle to go back in the
0036 former volume the biasing won't be invoked.
0037 This will produce particles with weights that do not correspondent to the
0038 importance of the current volumes.
0039
0040 ### Further information:
0041
0042 Short description of importance sampling and scoring:
0043 https://geant4.web.cern.ch/collaboration/working_groups/geometryTransport/#development-documents (Under the Event Biasing & Tallies Section)
0044
0045 ### \ref ExampleB01
0046
0047 The example uses importance sampling or the weight window technique
0048 according to an input parameter.
0049
0050 ### \ref ExampleB02
0051
0052 This example uses a parallel geometry to define G4GeometryCell objects
0053 for scoring and importance sampling. The output should be equivalent to B01.
0054
0055 A modular approach is applied to the physicslist and the extension for biasing.
0056 The parallel geometry is included in this extension.
0057
0058 ### \ref ExampleB03
0059
0060 This example uses a parallel geometry to define G4GeometryCell objects
0061 for scoring and importance sampling. The output should be statistically
0062 equivalent to B02 (and B01).
0063
0064 This demonstrates a customised "flat" physics implementation with the addition
0065 of biasing. Complementary approach to the modular physics lists of B01 and B02
0066
0067
0068 ## Generic biasing examples GB01 - GB06
0069
0070 These examples illustrate the usage of a biasing scheme implemented since
0071 version Geant4 10.0.
0072 The scheme is meant to be extensible, not limited to these six examples.
0073
0074 ### \ref ExampleGB01
0075
0076 This example illustrates how to bias process cross-sections in this scheme.
0077
0078 ### \ref ExampleGB02
0079
0080 Illustrates a force collision scheme similar to the MCNP one.
0081
0082 ### \ref ExampleGB03
0083
0084 Illustrates geometry based biasing.
0085
0086 ### \ref ExampleGB04
0087
0088 Illustrates a bremsstrahlung splitting.
0089
0090 ### \ref ExampleGB05
0091
0092 Illustrates a "splitting by cross-section" technique: a splitting-based
0093 technique using absorption cross-section to control the neutron population.
0094
0095 ### \ref ExampleGB06
0096
0097 Illustrates the usage of parallel geometries with generic biasing.
0098
0099 ### \ref ExampleGB07
0100
0101 Illustrates the usage of leading particle biasing with generic biasing.
0102
0103 ## Reverse MonteCarlo Technique example
0104
0105 ### \ref ExampleReverseMC01
0106
0107 Example illustrating the use of the Reverse Monte Carlo (RMC) mode in a Geant4
0108 application. See details in \ref ExampleReverseMC01 Example README page
0109 \endlink.
