| Geant4 Cross Reference |
1
2 Examples for event biasing: B01
3 -------------------------------
4
5 B01, B02 and B03 applications demonstrate the
6 reduction techniques supported in Geant4, or p
7 applications.
8
9 General remark to variance reduction
10 ------------------------------------
11 The tools provided for importance sampling (or
12 Russian roulette) and for the weight window te
13 have a good understanding of the physics in th
14 the user has to decide which particle types ha
15 cells (physical volumes, replicas) and assign
16 windows to that cells. If this is not done pro
17 expected that the results describe a real expe
18 here only demonstrate how to use the tools tec
19 to produce physical correct results.
20
21 General remark to scoring
22 -------------------------
23 Scoring is carried out using the built-in Mult
24 parallel geometries this requires a special sc
25 See examples/extended/runAndEvent (especailly
26
27 Known problems - should not happen
28 ----------------------------------
29 In the following scenario it can happen that a
30 biased and it's weight is therefore not change
31 a boundary where biasing should happen.
32 Importance and weight window sampling create p
33 between volumes. If the GPIL method of a physi
34 0 as step length for a particle on a boundary
35 that process changes the direction of the part
36 former volume the biasing won't be invoked.
37 This will produce particles with weights that
38 importance of the current volumes.
39
40 Further information:
41 --------------------
42 Short description of importance sampling and s
43 https://geant4.web.cern.ch/collaboration/worki
44
45 Example B01
46 ===========
47
48 The example uses importance sampling or the we
49 according to an input parameter. It uses scori
50 Importance values or weight windows are define
51 geometry. In this example the weight window te
52 that it behaves equivalent to importance sampl
53 not a window but simply the inverse of the imp
54 one energy region is used that covers all ener
55 The user may change the weight window configur
56 initialization of the weight window algorithm
57 Different energy bounds for the weight window
58 in B01DetectorConstruction.
59
60 The executable takes one optional argument: 0
61 with argument: 0, the importance sampling is a
62 the weight window technique is applied.
63
64 A modular approach is applied to the physicsli
65
66 Example B02
67 ===========
68
69 This example uses a parallel geometry to defin
70 for scoring and importance sampling. The outpu
71
72 A modular approach is applied to the physicsli
73 The parallel geometry is included in this exte
74
75 Example B03
76 ===========
77
78 This example uses a parallel geometry to defin
79 for scoring and importance sampling. The outpu
80 equivalent to B02 (and B01).
81
82 This demonstrates a customised "flat" physics
83 of biasing. Complementary approach to the modu
84
85
86 _____________________________________________
87
88
89 Generic biasing examples GB0
90 ----------------------------
91
92 These examples illustrate the usage of a biasi
93 version Geant4 10.0.
94 The scheme is meant to be extensible, not limi
95
96 Example GB01:
97 =============
98
99 This example illustrates how to bias process c
100
101
102 Example GB02:
103 =============
104
105 Illustrates a force collision scheme similar t
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
137
138 _____________________________________________
139
140
141 Reverse MonteCarlo Technique exam
142 ---------------------------------
143
144 Example ReverseMC01
145 ===================
146
147 Example illustrating the use of the Reverse Mo
148 application. See details in ReverseMC01/README
149