Import Geant4 11.4.0 source tree

examples/extended/biasing/README.md

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+\page Examples_biasing Category "biasing"
+
+## B01, B02 and B03
+
+B01, B02 and B03 applications demonstrate the usage of different variance
+reduction techniques supported in Geant4, or possible from the user
+applications.
+
+### General remark to variance reduction
+
+The tools provided for importance sampling (or geometrical splitting and
+Russian roulette) and for the weight window technique require the user to 
+have a good understanding of the physics in the problem. This is because 
+the user has to decide which particle types have to be biased, define the 
+cells (physical volumes, replicas) and assign importances or weight 
+windows to that cells. If this is not done properly it can not be 
+expected that the results describe a real experiment. The examples given 
+here only demonstrate how to use the tools technically. They don't intend 
+to produce physical correct results.
+
+### General remark to scoring
+
+Scoring is carried out using the built-in Multifunctional detectors. For
+parallel geometries this requires a special scoring physics process.
+See examples/extended/runAndEvent (especailly RE05) for clarification.
+
+### Known problems - should not happen
+
+In the following scenario it can happen that a particle is not
+biased and it's weight is therefore not changed even if it crosses
+a boundary where biasing should happen.
+Importance and weight window sampling create particles on boundaries 
+between volumes. If the GPIL method of a physical process returns 
+0 as step length for a particle on a boundary and if the PostStepDoIt of
+that process changes the direction of the particle to go back in the 
+former volume the biasing won't be invoked. 
+This will produce particles with weights that do not correspondent to the
+importance of the current volumes.
+
+### Further information:
+
+Short description of importance sampling and scoring:
+https://geant4.web.cern.ch/collaboration/working_groups/geometryTransport/#development-documents (Under the Event Biasing & Tallies Section)
+
+### \ref ExampleB01
+
+The example uses importance sampling or the weight window technique 
+according to an input parameter.
+
+### \ref ExampleB02
+
+This example uses a parallel geometry to define G4GeometryCell objects
+for scoring and importance sampling. The output should be equivalent to B01.
+
+A modular approach is applied to the physicslist and the extension for biasing.
+The parallel geometry is included in this extension.
+
+### \ref ExampleB03
+
+This example uses a parallel geometry to define G4GeometryCell objects
+for scoring and importance sampling. The output should be statistically 
+equivalent to B02 (and B01).
+
+This demonstrates a customised "flat" physics implementation with the addition
+of biasing. Complementary approach to the modular physics lists of B01 and B02
+
+
+## Generic biasing examples GB01 - GB06
+
+These examples illustrate the usage of a biasing scheme implemented since
+version Geant4 10.0.
+The scheme is meant to be extensible, not limited to these six examples.
+
+### \ref ExampleGB01
+
+This example illustrates how to bias process cross-sections in this scheme.
+
+### \ref ExampleGB02
+
+Illustrates a force collision scheme similar to the MCNP one.
+
+### \ref ExampleGB03
+
+Illustrates geometry based biasing.
+
+### \ref ExampleGB04
+
+Illustrates a bremsstrahlung splitting.
+
+### \ref ExampleGB05
+
+Illustrates a "splitting by cross-section" technique: a splitting-based
+technique using absorption cross-section to control the neutron population.
+
+### \ref ExampleGB06
+
+Illustrates the usage of parallel geometries with generic biasing.
+
+### \ref ExampleGB07
+
+Illustrates the usage of leading particle biasing with generic biasing.
+
+## Reverse MonteCarlo Technique example
+
+### \ref ExampleReverseMC01
+
+Example illustrating the use of the Reverse Monte Carlo (RMC) mode in a Geant4
+application. See details in \ref ExampleReverseMC01 Example README page
+\endlink.