| Geant4 Cross Reference |
1 2 Examples for event biasing: B01, B02 and B03 3 -------------------------------------------- 4 5 B01, B02 and B03 applications demonstrate the usage of different variance 6 reduction techniques supported in Geant4, or possible from the user 7 applications. 8 9 General remark to variance reduction 10 ------------------------------------ 11 The tools provided for importance sampling (or geometrical splitting and 12 Russian roulette) and for the weight window technique require the user to 13 have a good understanding of the physics in the problem. This is because 14 the user has to decide which particle types have to be biased, define the 15 cells (physical volumes, replicas) and assign importances or weight 16 windows to that cells. If this is not done properly it can not be 17 expected that the results describe a real experiment. The examples given 18 here only demonstrate how to use the tools technically. They don't intend 19 to produce physical correct results. 20 21 General remark to scoring 22 ------------------------- 23 Scoring is carried out using the built-in Multifunctional detectors. For 24 parallel geometries this requires a special scoring physics process. 25 See examples/extended/runAndEvent (especailly RE05) for clarification. 26 27 Known problems - should not happen 28 ---------------------------------- 29 In the following scenario it can happen that a particle is not 30 biased and it's weight is therefore not changed even if it crosses 31 a boundary where biasing should happen. 32 Importance and weight window sampling create particles on boundaries 33 between volumes. If the GPIL method of a physical process returns 34 0 as step length for a particle on a boundary and if the PostStepDoIt of 35 that process changes the direction of the particle to go back in the 36 former volume the biasing won't be invoked. 37 This will produce particles with weights that do not correspondent to the 38 importance of the current volumes. 39 40 Further information: 41 -------------------- 42 Short description of importance sampling and scoring: 43 https://geant4.web.cern.ch/collaboration/working_groups/geometryTransport/#development-documents (Under the Event Biasing & Tallies Section) 44 45 Example B01 46 =========== 47 48 The example uses importance sampling or the weight window technique 49 according to an input parameter. It uses scoring in both cases. 50 Importance values or weight windows are defined according to the mass 51 geometry. In this example the weight window technique is configured such 52 that it behaves equivalent to importance sampling: The window is actually 53 not a window but simply the inverse of the importance value and only 54 one energy region is used that covers all energies in the problem. 55 The user may change the weight window configuration by changing the 56 initialization of the weight window algorithm in example,cc. 57 Different energy bounds for the weight window technique may be specified 58 in B01DetectorConstruction. 59 60 The executable takes one optional argument: 0 or 1. Without argument or 61 with argument: 0, the importance sampling is applied with argument: 1, 62 the weight window technique is applied. 63 64 A modular approach is applied to the physicslist and the extension for biasing. 65 66 Example B02 67 =========== 68 69 This example uses a parallel geometry to define G4GeometryCell objects 70 for scoring and importance sampling. The output should be equivalent to B01. 71 72 A modular approach is applied to the physicslist and the extension for biasing. 73 The parallel geometry is included in this extension. 74 75 Example B03 76 =========== 77 78 This example uses a parallel geometry to define G4GeometryCell objects 79 for scoring and importance sampling. The output should be statistically 80 equivalent to B02 (and B01). 81 82 This demonstrates a customised "flat" physics implementation with the addition 83 of biasing. Complementary approach to the modular physics lists of B01 and B02 84 85 86 ___________________________________________________________________________ 87 88 89 Generic biasing examples GB01 - GB06 90 ------------------------------------ 91 92 These examples illustrate the usage of a biasing scheme implemented since 93 version Geant4 10.0. 94 The scheme is meant to be extensible, not limited to these six examples. 95 96 Example GB01: 97 ============= 98 99 This example illustrates how to bias process cross-sections in this scheme. 100 101 102 Example GB02: 103 ============= 104 105 Illustrates a force collision scheme similar to the MCNP one. 106 107 108 Example GB03: 109 ============= 110 111 Illustrates geometry based biasing. 112 113 114 Example GB04: 115 ============= 116 117 Illustrates a bremsstrahlung splitting. 118 119 120 Example GB05: 121 ============= 122 123 Illustrates a "splitting by cross-section" technique: a splitting-based 124 technique using absorption cross-section to control the neutron population. 125 126 127 Example GB06: 128 ============= 129 130 Illustrates the usage of parallel geometries with generic biasing. 131 132 Example GB07: 133 ============= 134 135 Illustrates the usage of leading particle biasing with generic biasing. 136 137 138 ___________________________________________________________________________ 139 140 141 Reverse MonteCarlo Technique example: ReverseMC01 142 ------------------------------------------------- 143 144 Example ReverseMC01 145 =================== 146 147 Example illustrating the use of the Reverse Monte Carlo (RMC) mode in a Geant4 148 application. See details in ReverseMC01/README. 149