Computational Physics - M Jensen Episode 1 Part 7 docx

Computational Physics - M. Jensen Episode 1 Part 7 docx

Computational Physics - M. Jensen Episode 1 Part 7 docx

... interval [0 ,10 0] with using the Gauss-Legendre method. 1 1.305 3.334 2 6 .74 7 7. 473 3 16 .030 10 .954 4 28.330 13 .463 5 42.556 14 .77 6 6 57. 444 14 .77 6 7 71 . 670 13 .463 8 83. 970 10 .954 9 93.253 7. 473 10 98.695 ... different methods as functions of the num- ber of mesh points . Trapez Simpson Gauss-Legendre 10 1. 8 210 20 1. 214 025 0 .14 60448 20 0. 912 678 0.60...
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Computational Physics - M. Jensen Episode 1 Part 1 ppsx

Computational Physics - M. Jensen Episode 1 Part 1 ppsx

... . 319 17 .1. 1 The histogram method . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 17 .1. 2 Multi-histogram method . . . . . . . . . . . . . . . . . . . . . . . . . . 319 17 .2 Renormalization ... several good 1 With Fortran we will consistently mean Fortran 90/95. There are no programming examples in Fortran 77 in this text. COMPUTATIONAL PHYSICS M. Hjorth -Jensen D...
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Computational Physics - M. Jensen Episode 1 Part 2 pot

Computational Physics - M. Jensen Episode 1 Part 2 pot

... 0.93 576 230E -1 3 -0 .3066 811 1E-04 10 0 40.000000 0.42483543E - 17 -0 . 316 57 319 E+ 01 1 27 50.000000 0 .19 2 874 98E- 21 0 .11 072 933E+05 15 5 60.000000 0. 875 6 510 8E-26 -0 .33 516 811 E+09 18 2 70 .000000 0.3 975 4497E-30 -0 .32 979 605E +14 ... 0.4 874 60E-08 72 30.0 0.93 576 2E -1 3 -0 .34 213 4E-04 10 0 40.0 0.424835E - 17 -0 .2 210 33E+ 01 1 27 5...
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Computational Physics - M. Jensen Episode 1 Part 3 doc

Computational Physics - M. Jensen Episode 1 Part 3 doc

... mechanical prob- lems from both atomic physics and nuclear physics. In atomic and nuclear physics the single- particle degrees are represented by quantum numbers such orbital angular momentum, total angular ... 12 7 . sigma1 =SQRT( ( sumsq2 sum xbar ) / 1 26.) ! second method to ev aluat e the st andard d e vi a tio n sumsq2 =0. DO i =1 , 12 7 sumsq2=sumsq2 +(x ( i ) xbar ) 2 EN...
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Computational Physics - M. Jensen Episode 1 Part 4 pdf

Computational Physics - M. Jensen Episode 1 Part 4 pdf

... 1. 000834 1. 000008 1. 000000 1. 000000 1. 010 303 1. 000000 1. 0 2 .72 0548 2. 71 8 304 2. 71 8 282 2. 71 8 282 2 .75 3353 2. 71 8 282 2.0 7. 395 216 7. 38 911 8 7. 3890 57 7.389056 7. 283063 7. 389056 3.0 20 .10 2280 20.08 570 4 ... 20.0855 37 20.2504 67 20.0855 37 4.0 54.643664 54.598605 54.59 815 5 54.59 815 1 54. 71 1 78 9 54.59 815 0 5.0 14 8.536 878 14 8. 414 396 14...
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Computational Physics - M. Jensen Episode 1 Part 5 pptx

Computational Physics - M. Jensen Episode 1 Part 5 pptx

... pointers this means that matr is pointer-to-a-pointer-to-an-integer which we can write matr. Furthermore matr is a-pointer-to-a-pointer of five integers. This interpretation is important when ... Programming details In the following discussion, matrices are always two-dimensional arrays while vectors are one- dimensional arrays. Many programming problems arise from improper treatment of ... so...
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Computational Physics - M. Jensen Episode 1 Part 6 doc

Computational Physics - M. Jensen Episode 1 Part 6 doc

... divided difference of order as (7 .15 ) meaning that the corresponding coefficient is given by (7 .16 ) With these definitions we see that Eq. (7. 7) can be rewritten as (7 . 17 ) If we replace in Eq. (7 .15 ) with , that ... slight modifications) steps and the other on more adaptive steps, namely so-called Gaussian quadrature methods. Both main methods encompass a plethora of approximati...
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Computational Physics - M. Jensen Episode 1 Part 8 pdf

Computational Physics - M. Jensen Episode 1 Part 8 pdf

... 999 10 30 993 0. 3-0 .4 939 960 10 23 9 37 0. 4-0 .5 10 38 10 01 1002 992 0. 5-0 .6 10 37 10 47 10 09 10 09 0. 6-0 .7 10 05 989 10 03 989 0. 7- 0 .8 986 962 985 954 0. 8-0 .9 10 00 10 27 10 09 10 23 0. 9 -1 .0 9 91 1 015 9 61 1026 0.49 97 ... 1. 59064E-02 10 00 7. 83486E- 01 5 .14 102E-03 10 000 7. 85488E- 01 1.60 311 E-03 10 0000 7. 85009E- 01 5.0...
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Computational Physics - M. Jensen Episode 1 Part 9 pptx

Computational Physics - M. Jensen Episode 1 Part 9 pptx

... rewriting (9 .10 9) since (9 .11 0) Perform then a Monte Carlo sampling for (9 .11 1) with , 9.5. IMPROVED MONTE CARLO INTEGRATION 15 3 where is a random number in the interval [0 ,1] . The algorithm for the ... (&idum ) sq rt2 ; } fx=gaussian_MC ( x ) ; int_mc += fx ; sum_sigma += fx fx ; } 16 4 CHAPTER 10 . RANDOM WALKS AND THE METROPOLIS ALGORITHM This mimicks the way a real system...
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Computational Physics - M. Jensen Episode 2 Part 7 pot

Computational Physics - M. Jensen Episode 2 Part 7 pot

... eigenvalues until Eq. (15 .23) is satisfied. 14 .9. PHYSICS PROJECT: STUDIES OF NEUTRON STARS 2 91 Quantity Units MeVfm MeVfm fm MeVc Kg= MeVc 1 Kg = MeVc m MeV c 19 7. 3 27 MeVfm list here the units ... matrix (16 .42) we can reformulate again the problem as a matrix-vector multiplication (16 .43) meaning that we can rewrite the problem as (16 .44) If does not depend on time , w...
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