| Geant4 Cross Reference |
1 1
2 Examples for event biasing: B01 2 Examples for event biasing: B01, B02 and B03
3 ------------------------------- 3 --------------------------------------------
4 4
5 B01, B02 and B03 applications demonstrate the 5 B01, B02 and B03 applications demonstrate the usage of different variance
6 reduction techniques supported in Geant4, or p 6 reduction techniques supported in Geant4, or possible from the user
7 applications. 7 applications.
8 8
9 General remark to variance reduction 9 General remark to variance reduction
10 ------------------------------------ 10 ------------------------------------
11 The tools provided for importance sampling (or 11 The tools provided for importance sampling (or geometrical splitting and
12 Russian roulette) and for the weight window te 12 Russian roulette) and for the weight window technique require the user to
13 have a good understanding of the physics in th 13 have a good understanding of the physics in the problem. This is because
14 the user has to decide which particle types ha 14 the user has to decide which particle types have to be biased, define the
15 cells (physical volumes, replicas) and assign 15 cells (physical volumes, replicas) and assign importances or weight
16 windows to that cells. If this is not done pro 16 windows to that cells. If this is not done properly it can not be
17 expected that the results describe a real expe 17 expected that the results describe a real experiment. The examples given
18 here only demonstrate how to use the tools tec 18 here only demonstrate how to use the tools technically. They don't intend
19 to produce physical correct results. 19 to produce physical correct results.
20 20
21 General remark to scoring 21 General remark to scoring
22 ------------------------- 22 -------------------------
23 Scoring is carried out using the built-in Mult 23 Scoring is carried out using the built-in Multifunctional detectors. For
24 parallel geometries this requires a special sc 24 parallel geometries this requires a special scoring physics process.
25 See examples/extended/runAndEvent (especailly 25 See examples/extended/runAndEvent (especailly RE05) for clarification.
26 26
27 Known problems - should not happen 27 Known problems - should not happen
28 ---------------------------------- 28 ----------------------------------
29 In the following scenario it can happen that a 29 In the following scenario it can happen that a particle is not
30 biased and it's weight is therefore not change 30 biased and it's weight is therefore not changed even if it crosses
31 a boundary where biasing should happen. 31 a boundary where biasing should happen.
32 Importance and weight window sampling create p 32 Importance and weight window sampling create particles on boundaries
33 between volumes. If the GPIL method of a physi 33 between volumes. If the GPIL method of a physical process returns
34 0 as step length for a particle on a boundary 34 0 as step length for a particle on a boundary and if the PostStepDoIt of
35 that process changes the direction of the part 35 that process changes the direction of the particle to go back in the
36 former volume the biasing won't be invoked. 36 former volume the biasing won't be invoked.
37 This will produce particles with weights that 37 This will produce particles with weights that do not correspondent to the
38 importance of the current volumes. 38 importance of the current volumes.
39 39
40 Further information: 40 Further information:
41 -------------------- 41 --------------------
42 Short description of importance sampling and s 42 Short description of importance sampling and scoring:
43 https://geant4.web.cern.ch/collaboration/worki << 43 http://cern.ch/geant4/working_groups/geometry/biasing/Sampling.html
44 44
45 Example B01 45 Example B01
46 =========== 46 ===========
47 47
48 The example uses importance sampling or the we 48 The example uses importance sampling or the weight window technique
49 according to an input parameter. It uses scori 49 according to an input parameter. It uses scoring in both cases.
50 Importance values or weight windows are define 50 Importance values or weight windows are defined according to the mass
51 geometry. In this example the weight window te 51 geometry. In this example the weight window technique is configured such
52 that it behaves equivalent to importance sampl 52 that it behaves equivalent to importance sampling: The window is actually
53 not a window but simply the inverse of the imp 53 not a window but simply the inverse of the importance value and only
54 one energy region is used that covers all ener 54 one energy region is used that covers all energies in the problem.
55 The user may change the weight window configur 55 The user may change the weight window configuration by changing the
56 initialization of the weight window algorithm 56 initialization of the weight window algorithm in example,cc.
57 Different energy bounds for the weight window 57 Different energy bounds for the weight window technique may be specified
58 in B01DetectorConstruction. 58 in B01DetectorConstruction.
59 59
60 The executable takes one optional argument: 0 60 The executable takes one optional argument: 0 or 1. Without argument or
61 with argument: 0, the importance sampling is a 61 with argument: 0, the importance sampling is applied with argument: 1,
62 the weight window technique is applied. 62 the weight window technique is applied.
63 63
64 A modular approach is applied to the physicsli 64 A modular approach is applied to the physicslist and the extension for biasing.
65 65
66 Example B02 66 Example B02
67 =========== 67 ===========
68 68
69 This example uses a parallel geometry to defin 69 This example uses a parallel geometry to define G4GeometryCell objects
70 for scoring and importance sampling. The outpu 70 for scoring and importance sampling. The output should be equivalent to B01.
71 71
72 A modular approach is applied to the physicsli 72 A modular approach is applied to the physicslist and the extension for biasing.
73 The parallel geometry is included in this exte 73 The parallel geometry is included in this extension.
74 74
75 Example B03 75 Example B03
76 =========== 76 ===========
77 77
78 This example uses a parallel geometry to defin 78 This example uses a parallel geometry to define G4GeometryCell objects
79 for scoring and importance sampling. The outpu 79 for scoring and importance sampling. The output should be statistically
80 equivalent to B02 (and B01). 80 equivalent to B02 (and B01).
81 81
82 This demonstrates a customised "flat" physics 82 This demonstrates a customised "flat" physics implementation with the addition
83 of biasing. Complementary approach to the modu 83 of biasing. Complementary approach to the modular physics lists of B01 and B02
84 84
85 85
86 _____________________________________________ 86 ___________________________________________________________________________
87 87
88 88
89 Generic biasing examples GB0 << 89 Generic biasing examples GB01, GB02
90 ---------------------------- << 90 ------------------------------------
91 91
92 These examples illustrate the usage of a biasi 92 These examples illustrate the usage of a biasing scheme implemented since
93 version Geant4 10.0. 93 version Geant4 10.0.
94 The scheme is meant to be extensible, not limi << 94 The scheme is meant to be extensible, not limited to these two examples.
95 95
96 Example GB01: 96 Example GB01:
97 ============= 97 =============
98 98
99 This example illustrates how to bias process c 99 This example illustrates how to bias process cross-sections in this scheme.
100 100
101 101
102 Example GB02: 102 Example GB02:
103 ============= 103 =============
104 104
105 Illustrates a force collision scheme similar t 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" tec <<
124 technique using absorption cross-section to co <<
125 <<
126 <<
127 Example GB06: <<
128 ============= <<
129 <<
130 Illustrates the usage of parallel geometries w <<
131 <<
132 Example GB07: <<
133 ============= <<
134 <<
135 Illustrates the usage of leading particle bias <<
136 106
137 107
138 _____________________________________________ 108 ___________________________________________________________________________
139 109
140 110
141 Reverse MonteCarlo Technique exam 111 Reverse MonteCarlo Technique example: ReverseMC01
142 --------------------------------- 112 -------------------------------------------------
143 113
144 Example ReverseMC01 114 Example ReverseMC01
145 =================== 115 ===================
146 116
147 Example illustrating the use of the Reverse Mo 117 Example illustrating the use of the Reverse Monte Carlo (RMC) mode in a Geant4
148 application. See details in ReverseMC01/README 118 application. See details in ReverseMC01/README.
149 119