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24 lines
516 B
Python
24 lines
516 B
Python
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from hydrogen import *
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from qmc_stats import *
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norm_gauss = 1./(2.*np.pi)**(1.5)
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def gaussian(r):
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return norm_gauss * np.exp(-np.dot(r,r)*0.5)
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def MonteCarlo(a,nmax):
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E = 0.
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N = 0.
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for istep in range(nmax):
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r = np.random.normal(loc=0., scale=1.0, size=(3))
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w = psi(a,r)
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w = w*w / gaussian(r)
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N += w
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E += w * e_loc(a,r)
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return E/N
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a = 0.9
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nmax = 100000
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X = [MonteCarlo(a,nmax) for i in range(30)]
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E, deltaE = ave_error(X)
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print(f"E = {E} +/- {deltaE}")
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