... ofthe most studied cases in statistical physics and discussions of simulations of phase transitions. 11 .1 Phase transitions in magnetic systems 11 .1. 1 Theoretical background The model we will employ ... spin [ j +1] ; } 10 .4. THE METROPOLIS ALGORITHM AND DETAILED BALANCE 18 1 Figure 10 .5: Probability distribution for one walker after 10 , 10 0 and 10 00 steps. 10 .5. PHYSICS...
Ngày tải lên: 07/08/2014, 12:22
... with nm eV nm [eV] 86 42 0 -2 -4 -6 -8 0 -1 0 -2 0 -3 0 -4 0 -5 0 -6 0 Figure 12 .5: Plot of for =0 .1 and 0.4 nm. Units along the -axis are . The straight line is the binding energy of the hydrogen atom, eV. respect ... original matrix. After a series of such transformations, we end with a set of diagonal matrix elements (13 .18 ) and off-diagonal matrix element...
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Computational Physics - M. Jensen Episode 2 Part 2 doc
... MODELS 2 01 11. 3.3 Thermalization in preparation 11 .4 Other spin models 11 .4 .1 Potts model 11 .4.2 XY-model 11 .5 Physics project: simulation of the Ising model In this project we will use the Metropolis ... to recompile the program when larger systems are considered. 11 .2 .1 Program for the two-dimensional Ising Model programs/chap 11/ program1.cpp / Program to solve the two d...
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Computational Physics - M. Jensen Episode 2 Part 3 pps
... 2.32782E+00 4.82475E-03 7.00000E- 01 1.23264E+00 9.82479E- 01 3 .13 445E-03 8.00000E- 01 1.08007E+00 3.44857E- 01 1.85703E-03 9.00000E- 01 1. 011 11E+00 7.24827E-02 8. 513 68E-04 1. 00000E-00 1. 00000E+00 0.00000E+00 ... 0.00000E+00 1. 10000E+00 1. 02621E+00 5.95 716 E-02 7. 718 26E-04 1. 20000E+00 1. 08667E+00 2.23389E- 01 1.49462E-03 1. 30000E+00 1. 1 716 8E+00 4.78446E- 01 2...
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Computational Physics - M. Jensen Episode 2 Part 5 pdf
... is large. 14 .3 .1 Improvements to Euler’s algorithm, higher-order methods The most obvious improvements to Euler’s and Euler-Cromer’s algorithms, avoiding in addition the need for computing a ... In the previous physics project on bound states in momentum space, we obtained the SE in momentum space by Eq. (13 .48). was the relative momentum between the two particles. A partial wave expan...
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Computational Physics - M. Jensen Episode 2 Part 6 pptx
... Four different methods have been used to solve the equations, Euler’s method from Eq. (14 .17 ), the half-step method, Euler-Richardson’s method in Eqs. (14 .32 )-( 14 .33) and finally the fourth-order Runge-Kutta ... 0]) ; yout [1] = yin [ 1 ] +1. 0 / 6 .0 ( k1 [1] +2 k2 [1] +2 k3 [1] + k4 [ 1] ) ; } 280 CHAPTER 14 . DIFFERENTIAL EQUATIONS void pendelum : : e ule r ( ) { / / using simp...
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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 7.327 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 , we ne...
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Computational Physics - M. Jensen Episode 2 Part 8 docx
... transition 17 .1. 1 The histogram method 17 .1. 2 Multi-histogram method 17 .2 Renormalization group approach 319 324 CHAPTER 19 . DIFFUSION MONTE CARLO METHODS This derivation shares many formal similarities with ... however, the importance sampled DMC method of Eq. (19 .10 ) must be trans- formed into a form suitable for Monte Carlo integration. The transformation is more complex than...
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Computational Physics - M. Jensen Episode 2 Part 9 pdf
... and M. J. Paez, Computational Physics (Wiley, 19 97). [7] E.W. Schmid, G. Spitz and W. Lösch, Theoretische Physik mit dem Personal Computer, (Springer, 19 87). [8] J .M. Thijssen, Computational Physics, ... Simulation Methods: Applica- tions to Physical Systems, (Addison-Wesley, 19 96). [11 ] M. Metcalf and J. Reid, The F90 Programming Language, (Oxford University Press, 19 96)....
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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 ... 18 7 11 .1. 1 Theoretical background . . . . . . . . . . . . . . . . . . . . . . . . . . 18 7 11 .1. 2 The Metropolis algorithm . . . . . . . . . . . . . . . . . . . . . . . . . 1...
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