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- Page 8 and 9: D. Kernel Distortion, Importance Sa
- Page 10 and 11: Appendix 5C:Solution of the Moment
- Page 13 and 14: !Chapter 1SCOPE AND STRUCTURE OF TH
- Page 15: 7. Shreider, Y. A., Ed,, Method sta
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- Page 31 and 32: 19After substitution and integratio
- Page 33 and 34: 21andT) - sincpand cp is equidistri
- Page 35 and 36: 23though many quantities not listed
- Page 37 and 38: D. ELEMENTARY INTERACTIONS OF PARTI
- Page 39 and 40: 27absorption, scattering, etc. rate
- Page 41 and 42: 29therefore:4,(P) cr(r,,E) cp(P) (2
- Page 43 and 44: 14. Irving, D. C, Freestone, R. M.,
- Page 45 and 46: 33Chapter 3DIRECT SIMULATION OF THE
- Page 47 and 48: 35The list presented above is not t
- Page 49 and 50: ¥7if t, is its area andTthen the c
- Page 51 and 52: 39B. PATH LENGTH SELECTIONAs has be
- Page 53 and 54: 41For the computer simulation outli
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43created. However, from the immedi
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45one gets a new formulation of the
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47The life of the primary photon is
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49from Equation (3.13) asE = -—-
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51the secondary neutron can appear
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53straightforward manner: select 3
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SSspace region. According to the tw
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57where R 11is the distance to the
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59By this technique the number of e
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61R-PDFIGURE 3.4.Geometry for the p
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63In the following Sections, an ele
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65as a sum of many contributions. I
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67Let us express the PDF A.l as a s
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mwhereS=*LI + 0.5625 a,,The applica
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71Following Erikson's results' 3the
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73' s' Method Q PiSelect p,q = y -
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75ComputeK=I +b8aL = - K + VKaVM =
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C. APPLICATION OF THE REJECTION TEC
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REFERENCES1. Amaldi, E., The produc
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81Chapter 4COLLISION DENSITY AND IM
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83Proof. The expected value of I of
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SSor — from Theorem 2.5 —x = ma
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The reader should refer here to the
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89Applications of multi-variable im
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91Our task is now to give some guid
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93If the estimations of h, and h 2a
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95whereI 1= JdXf(X)(Pj(X) (4.28)way
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97whereW 1 0= |dxQ(x)2. Select the
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99kind Fredholm-type integral equat
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dR = dsdr_ - R 2 ciRci J r i. s
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!©3for simple plausible explanatio
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1051. The Transition Kernel •.If
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107and now Equation (4.34) — and
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109ordPf;(P) x(P)The crucial point
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IllSimilarly, solid angles of inter
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113The expected track length is a s
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115In regions imbedded in non-zero
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117Thus,C(
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119r, readsR„ =V s4TT JR 2dR dEex
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123If (T is constant in the region,
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123andTCr 1^1 ?r,) = (l + expPtf R
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125the differential score. This pec
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duced and discussed in various ways
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129andX(r,E) = Jdr'T(r'-»r|E)«j>(
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13!The flux-at-a point pay-off give
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If the scatterer atom is hydrogen,
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Proof.Multiply Equation (4.36) by x
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137Let us assume now that the sourc
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139empirical variance. It can be us
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141The difference between Equations
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143Chapter 5THE MOMENT EQUATIONSWe
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MSA. RELATION OF THE EXPECTED SCORE
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The source term of the equation. 1(
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149and C(P',P"). Then the first two
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where T"(P,P') is the transition ke
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153The nonanalog transition kernel
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155simulation unbiased with respect
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157to be carried by the particles i
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559history from P (i.e., a history
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16!the score probability Equation (
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163This is the general moment equat
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165where again we have putM 2(P) =M
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LFT?and A and B follow from the bou
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,R a0.9-0.8-0.7-0.6050.40.30.20.10.
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171be the probability of the contri
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173and assuming again that the seco
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andC(P',P") =C(P',P")/c(P')Let us d
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177postcollision coordinates P". Th
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179If in, denotes this expected num
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181procedure, only the probabilitie
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1.83In certain applications, the ke
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185Proof. Let 9~(P,P') be the proba
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187As the splitting probabilities g
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189Inserting the equations above in
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191It is easy to see that the proce
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193where we use the notational conv
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195and assuming again deterministic
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197[Note that we have omitted the a
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The contribution functions f(P,P')
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201in an n-fold multiplication from
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203and making use of the results of
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205The conditions under which the t
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207ciple, may result in a game of z
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functions only, we define the trans
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211The simplest contribution functi
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213M 1(P) = M 1(P) if the weight ge
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2HLetn(P) = N(P) -N(P)Then n(P) sat
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21?The weight of a particle undergo
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219where, according to the weight g
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221P 1, P 2, ... P nand W 1, W 2, .
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a probability q s(P'), represented
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225Equation (5.205) determines the
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227possible events in a collision,
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22¾Theorem 5.16 — Given a set of
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Theorem 5.18 — Any linear combina
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233Let us consider transformation (
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235The general form of track-length
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237The details of the solution of E
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239In view of Equations (5.238) and
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241surrounded by a black absorber a
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243In the case of the collision rat
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245Integrating the first-moment equ
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247FIGURE 5.3. Collision rates in v
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249The quantity F characterizes the
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251therefore result in finite varia
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253i.e., ifM 2(P)/M,(P) = M 1(P) ¢
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255We have thus completed the const
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257andC(P',P") = C(P'.P")M,(P")/U(P
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259and3J 2(P') = c a(P') W 11(P') f
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261withF„(P',P") = i;(P',P") + 2f
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Subtraction of Equation (5.313) fro
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265Let the nonanalog transition ker
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267An Immediate consequence of this
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269and according to Equations (5.29
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27!After rearrangement, this relati
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273A {c)FIGURE 5.5. Efficiency of t
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275withV (P') =dP" C(P',F) Mf(F)dP"
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277score by the expectation estimat
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279Accordingly, the collision estim
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281where P = (r,to,E), P' = (r', -
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283This means that in a rather broa
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285Since no other biasing is assume
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28?A. ESTIMATION OF BILINEAR FORMSI
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289The final bilinear score in the
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291single type are present and vari
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293function is available that would
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295is either parallel to the direct
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297while all the other coefficients
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299In the derivation of the second
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(1 - - -ft) 2— aeexlciX'c - fl) (
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3«;39. Rief, H. and Fioretti, A.,
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306 Monte Carlo Particle Transport
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370 Monie Carlo Particle Transport
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N2 f f i ? )428 Mome Carlo Particle
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441Chapter 7OPTIMIZATION OF EFFICIE
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443estimated be the number of parti
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445and on the optical thickness X.
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447The variance of the escape rate
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449In view of Equation (7.15) and (
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451The solution of this equation go
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453formation can be chosen asb(x) =
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455or, equivalently, the stretched
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457andH(x,y) = y/(l + xy)The qualit
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459is w 2w,/n, and the expected sco
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461.where the parameter b is for th
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463An easy-to-use direct statistica
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465with a probabilityTR(JIk 1-,) =
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46?moment of the score isM 2= Mf[I
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469fact, the number of fragments ar
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471As for the first question, let u
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473of Equations (7.82) and (7.83) a
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475In the equation above we have in
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47'?Equations (7.103) and (7.104).t
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479importance function. Accordingly
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481- ---!'M + (I - i) - M + (i)l +
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483gives an opportunity of checking
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mi-11.5A 3.- QUALJTY FACTOR INLEAKA
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487due to a starter in a region is
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489of the directional dependence 41
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49!whereT(P,P') = j dto-sr 4 to,R)t
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493both sides of the equality byT(P
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495Comparing this kernel to the tra
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497expected score is put into the f
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499The constant A follows from the
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SOlform isQ(x,|x,E)8(x)Q E(E)1 cx(x
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In all the approximations above, th
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505let us determine explicitly the
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507factor in a flight is(w 2 ) = J
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509where, according to Equation (7.
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40. Lux, I., On Geometrical Splitti
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514 Monte Carlo Particle Transport
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516 Monte Carlo Particle Transport