10 real*8 delta, s0, Z, Y1, eta1, B
11 parameter( delta = 0.00308, s0=5.38**2, z = delta*35.45,
12 * y1 =0.0317, eta1 = 0.458, b = delta*0.308)
15 real*8 roots(np), mb(np)
16 data ( roots(i), i= 1 , np )/
17 1 1.0705 , 1.1016 , 1.1256 ,
18 2 1.1501 , 1.1625 , 1.1878 , 1.2049 ,
19 3 1.2179 , 1.2355 , 1.2534 , 1.2715 ,
20 4 1.2898 , 1.3179 , 1.3274 , 1.3369 ,
21 5 1.3660 , 1.3758 , 1.4158 , 1.4570 ,
22 6 1.4887 , 1.5431 , 1.5823 , 1.6167 ,
23 7 1.6518 , 1.6877 , 1.7121 , 1.7306 ,
24 8 1.7556 , 1.7873 , 1.8460 , 1.9133 ,
25 9 1.9761 , 2.0046 , 2.0778 , 2.1769 ,
26 a 2.2563 , 2.3981 , 2.5672 , 2.7187 ,
27 b 2.9208 , 3.1718 , 3.4692 , 3.7809 ,
28 c 4.1801 , 4.6049 , 5.1094 , 5.8132 ,
29 d 6.6377 , 7.6611 , 8.7165 , 9.7759 ,
30 e 11.243 , 13.070 , 15.468 , 17.917 ,
31 f 20.239 , 23.360 , 26.865 , 32.956 ,
32 g 39.995 , 52.520 , 68.968 , 93.871 ,
33 h 116.40 , 151.76 , 199.28
35 data ( mb(i), i= 1 , np )/
36 1 0.34130
e-01, 0.79199
e-01, 0.11944 ,
37 2 0.25327 , 0.33197 , 0.45290 , 0.52636 ,
38 3 0.56460 , 0.51589 , 0.43072 , 0.32208 ,
39 4 0.25321 , 0.20721 , 0.18008 , 0.16455 ,
40 5 0.18372 , 0.20513 , 0.22674 , 0.25316 ,
41 6 0.27704 , 0.25313 , 0.22670 , 0.21133 ,
42 7 0.22442 , 0.23831 , 0.21130 , 0.19308 ,
43 8 0.17642 , 0.16282 , 0.15958 , 0.16280 ,
44 9 0.16117 , 0.15483 , 0.14725 , 0.14288 ,
45 a 0.14003 , 0.13451 , 0.13316 , 0.13050 ,
46 b 0.12789 , 0.12533 , 0.12657 , 0.12529 ,
47 c 0.12278 , 0.12154 , 0.12030 , 0.11907 ,
48 d 0.11904 , 0.11901 , 0.11779 , 0.11777 ,
49 e 0.11774 , 0.11537 , 0.11418 , 0.11530 ,
50 f 0.11879 , 0.12116 , 0.12235 , 0.12478 ,
51 g 0.12726 , 0.13108 , 0.13501 , 0.14186 ,
52 h 0.14468 , 0.15357 , 0.15977
62 if( rts .lt. 1.08)
then 64 elseif(rts .lt. 15.)
then 68 xs = z + b*log(s/s0)**2 + y1*(1./s)**eta1
100 subroutine cgppi0(egl10, xs)
106 real*8 xs1(107), xs2(100), xs3(109), xs4(92)
108 real*8 e11/2.2328224/, e12/3.2981243/, eps/1./
109 real*8 e21/2.3053560/, e22/3.2981243/
110 real*8 e31/2.6146288/, e32/3.7040262/
111 real*8 e41/2.8246450/
115 data ( xs1(i),i= 1, 72)/
116 1 0.0, 2.4, 5.8, 8.9, 11.6, 12.8, 13.6, 14.4,
117 2 17.2, 20.9, 25.3, 30.3, 35.9, 42.4, 48.5, 53.4,
118 3 60.9, 71.8, 85.8, 120.9, 150.4, 204.4, 224.5, 241.6,
119 4 251.3, 252.4, 248.9, 233.7, 210.9, 196.1, 186.7, 170.5,
120 5 155.6, 145.1, 140.3, 134.9, 124.5, 111.0, 100.6, 91.3,
121 6 86.8, 77.9, 66.8, 55.4, 46.5, 41.0, 40.0, 39.5,
122 7 40.0, 40.4, 40.8, 41.2, 41.6, 42.0, 42.8, 41.7,
123 8 40.3, 38.8, 37.3, 35.5, 34.2, 33.5, 32.7, 32.8,
124 9 32.4, 32.0, 31.6, 31.2, 30.6, 30.0, 29.7, 28.9/
125 data ( xs1(i),i= 73, 107)/
126 1 27.9, 26.7, 25.3, 23.4, 21.8, 20.3, 18.8, 16.8,
127 2 15.4, 14.2, 13.2, 12.3, 11.9, 11.2, 10.5, 9.8,
128 3 9.0, 8.0, 7.3, 6.8, 6.2, 5.7, 5.3, 4.8,
129 4 4.8, 4.7, 4.7, 4.7, 4.5, 4.1, 4.0, 2.5,
134 data ( xs2(i),i= 1, 72)/
135 1 0.0, 59.9, 82.4, 105.5, 127.1, 147.2, 160.8, 166.5,
136 2 175.5, 185.1, 191.6, 194.8, 197.7, 200.1, 201.8, 203.0,
137 3 203.2, 203.4, 202.3, 198.6, 195.0, 193.8, 190.1, 159.7,
138 4 152.0, 143.0, 130.8, 119.4, 109.8, 101.7, 92.2, 81.5,
139 5 73.8, 67.7, 64.9, 61.5, 58.4, 56.5, 56.5, 59.2,
140 6 62.0, 64.1, 68.6, 76.9, 84.7, 90.1, 93.4, 96.1,
141 7 97.6, 98.0, 97.3, 97.0, 96.0, 94.7, 93.0, 91.0,
142 8 88.8, 86.4, 83.6, 80.6, 78.0, 74.3, 69.7, 63.7,
143 9 58.1, 52.8, 47.4, 43.3, 41.2, 38.2, 35.0, 31.2/
144 data ( xs2(i),i= 73, 100)/
145 1 28.3, 25.7, 23.6, 22.1, 20.5, 19.1, 18.5, 17.3,
146 2 16.0, 14.6, 12.8, 11.6, 10.6, 9.8, 9.2, 8.7,
147 3 8.7, 8.7, 8.6, 8.6, 8.2, 7.5, 6.9, 6.2,
148 4 5.7, 4.6, 3.2, 1.3/
151 data ( xs3(i),i= 1, 72)/
152 1 0.0, 0.7, 3.0, 5.7, 8.9, 12.9, 16.6, 21.1,
153 2 23.0, 30.9, 44.3, 50.9, 57.5, 63.4, 67.4, 69.9,
154 3 70.7, 71.3, 72.6, 72.4, 72.4, 71.6, 70.3, 68.5,
155 4 67.4, 66.4, 65.3, 64.3, 63.3, 62.3, 61.2, 60.2,
156 5 59.1, 58.0, 56.9, 55.8, 54.8, 53.8, 52.9, 51.9,
157 6 51.0, 50.0, 49.4, 48.4, 47.4, 46.4, 45.4, 44.3,
158 7 43.2, 42.2, 40.7, 39.6, 38.5, 37.5, 36.4, 35.4,
159 8 34.4, 33.4, 32.4, 31.4, 30.4, 29.4, 28.5, 27.6,
160 9 26.7, 25.8, 24.9, 24.0, 22.3, 21.5, 20.7, 20.1/
161 data ( xs3(i),i= 73, 109)/
162 1 19.5, 19.1, 19.2, 19.3, 19.4, 19.9, 19.6, 19.7,
163 2 19.8, 20.0, 19.8, 19.7, 19.1, 18.8, 18.5, 18.3,
164 3 18.0, 17.8, 17.6, 17.1, 16.9, 16.8, 16.7, 16.9,
165 4 17.1, 17.4, 17.8, 18.2, 18.8, 19.4, 20.4, 21.1,
166 5 21.8, 22.4, 23.0, 23.5, 23.9/
171 data ( xs4(i),i= 1, 72)/
172 1 0.0, 2.6, 5.6, 8.7, 11.8, 14.9, 18.1, 21.2,
173 2 24.4, 28.2, 31.1, 34.0, 36.7, 39.2, 41.6, 43.9,
174 3 45.9, 48.0, 50.1, 52.0, 53.9, 55.6, 57.3, 58.4,
175 4 60.0, 61.6, 63.2, 64.7, 66.2, 67.6, 68.8, 70.2,
176 5 71.6, 73.0, 74.4, 75.8, 77.2, 77.9, 79.3, 80.7,
177 6 82.3, 84.0, 85.9, 87.8, 89.9, 93.2, 95.4, 97.4,
178 7 99.3, 101.2, 103.0, 104.6, 106.7, 108.0, 109.2, 109.9,
179 8 110.3, 111.7, 112.0, 112.3, 111.9, 112.3, 112.3, 112.0,
180 9 111.6, 110.9, 110.1, 109.2, 108.2, 107.0, 105.7, 104.0/
181 data ( xs4(i),i= 73, 92)/
182 1 102.5, 100.9, 99.3, 97.6, 95.7, 93.9, 92.1, 90.3,
183 2 88.5, 86.1, 84.4, 82.8, 81.4, 81.1, 80.3, 79.1,
184 3 77.7, 75.9, 73.9, 71.6/
188 entry cgppip(egl10, xs)
192 entry cgppi2(egl10, xs)
196 entry cgppi3(egl10, xs)
202 if(egl10 .lt. e11)
then 204 elseif(egl10 .lt. e12)
then 205 call kintp3(xs1, 1, 107, e11, 0.01
d0, egl10, xs)
212 if(egl10 .lt. e21)
then 214 elseif(egl10 .lt. e22)
then 215 call kintp3(xs2, 1, 100, e21, 0.01
d0, egl10, xs)
222 if(egl10 .lt. e31)
then 224 elseif(egl10 .lt. e32)
then 225 call kintp3(xs3, 1, 109, e31, 0.01
d0, egl10, xs)
232 if(egl10 .lt. e41)
then 235 call kintp3(xs4, 1, 92, e41, 0.01
d0, egl10, xs)
integer npitbl real *nx parameter(n=101, npitbl=46, nx=n-1) real *8 uconst
dE dx *! Nuc Int sampling table e
subroutine cgppi0(egl10, xs)
subroutine kpolintplogxyfe(xa, xstep, ya, ystep, nt, m, logxy, x, y, error)
block data cblkEvhnp ! currently usable models data RegMdls ad *special data *Cekaon d0
dE dx *! Nuc Int sampling table d
dE dx *! Nuc Int sampling table h
dE dx *! Nuc Int sampling table g
subroutine kintp3(f, intv, n, x1, h, x, ans)
subroutine cgpxs1(Eg, xs)
dE dx *! Nuc Int sampling table f
dE dx *! Nuc Int sampling table c