#The number of walkers
nWalkersmin = 500
nWalkersmax = 2000
walkers = np.array([i + 1 for i in range(nWalkersmin, nWalkersmax)])
correctwalkers = walkers[walkers % 50 == 0]
vavg = np.zeros(correctwalkers.size)
stdvavg = np.zeros(correctwalkers.size)
count = 0
for i in range(correctwalkers.size):
thiswalker = correctwalkers[i]
H2Wfn = dmc.wavefunction(thiswalker, 'harmonic', plotting=False)
TheoreticalOmega0 = H2Wfn.getTheoreticalOmega0()
print('the theoretical frequency for H2 vibration is: ' +
str(TheoreticalOmega0) + ' cm^-1')
#Important parameters for the MC simulation
nReps = 10 #Repeat the DMC simulation 3 times
nEquilibrationSteps = 10 #Initially equilibrate the simulation with 12000 diffusion steps
nSteps = 200 #Make 2000 Diffusion steps in each simulation
#don't worry about this just yet
nDesSteps = 75
nRepsDW = 2000
import dmc1D as dmc
import numpy as np
import matplotlib.pyplot as plt
import sys
#test of Morse
#Conversion factor of atomic units of energy to wavenumber (inverse centimeters)
au2wn=219474.63
#The number of walkers
nWalkers=10000
H2Wfn=dmc.wavefunction(nWalkers,'Morse',plotting=False)
TheoreticalOmega0=H2Wfn.getTheoreticalOmega0()
print('the theoretical frequency for H2 vibration is: '+str(TheoreticalOmega0)+' cm^-1')
#Important parameters for the MC simulation
nReps=3 #Repeat the DMC simulation 3 times
nEquilibrationSteps=1200 #Initially equilibrate the simulation with 12000 diffusion steps
nSteps=2000 #Make 2000 Diffusion steps in each simulation
#don't worry about this just yet
nDesSteps=75
nRepsDW=2000
print('important parameters:')
print('Equilibrating for '+str(nEquilibrationSteps))
import dmc1D as dmc
import numpy as np
import matplotlib.pyplot as plt
import sys
#test of quartic
#Conversion factor of atomic units of energy to wavenumber (inverse centimeters)
au2wn = 219474.63
#The number of walkers
nWalkers = 10000 #was10000
H2Wfn = dmc.wavefunction(nWalkers, 'Quartic', plotting=False)
TheoreticalOmega0 = H2Wfn.getTheoreticalOmega0()
print('the theoretical frequency for H2 vibration is: ' +
str(TheoreticalOmega0) + ' cm^-1')
#Important parameters for the MC simulation
nReps = 3 #Repeat the DMC simulation 3 times
nEquilibrationSteps = 12000 #Initially equilibrate the simulation with 12000 diffusion steps
nSteps = 2000 #Make 2000 Diffusion steps in each simulation
#don't worry about this just yet
nDesSteps = 75
nRepsDW = 2000
print('Important parameters:')
print('Equilibrating for ' + str(nEquilibrationSteps))
print('The number of diffusion steps in the simulation is ' + str(nSteps))
print('The time step is ' + str(H2Wfn.dtau))
import dmc1D as dmc
import numpy as np
import matplotlib.pyplot as plt
import sys
#Conversion factor of atomic units of energy to wavenumber (inverse centimeters)
au2wn = 219474.63
#The number of walkers
nWalkers = 10000
H2Wfn = dmc.wavefunction(nWalkers, 'harmonic', plotting=False)
TheoreticalOmega0 = H2Wfn.getTheoreticalOmega0()
print('the theoretical frequency for H2 vibration is: ' +
str(TheoreticalOmega0) + ' cm^-1')
#Important parameters for the MC simulation
nReps = 3 #Repeat the DMC simulation 3 times
nEquilibrationSteps = 1200 #Initially equilibrate the simulation with 12000 diffusion steps
nSteps = 2000 #Make 2000 Diffusion steps in each simulation
#don't worry about this just yet
nDesSteps = 75
nRepsDW = 2000
print('important parameters:')
print('Equilibrating for ' + str(nEquilibrationSteps))
print('The number of diffusion steps in the simulation is ' + str(nSteps))
print('The time step is ' + str(H2Wfn.dtau))
H2Wfn.setX(H2Wfn.xcoords + 6.2)