mirror of
https://github.com/TREX-CoE/qmc-lttc.git
synced 2024-11-04 05:04:01 +01:00
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
from hydrogen import *
|
|
from qmc_stats import *
|
|
|
|
def MonteCarlo(a,tau,nmax):
|
|
E = 0.
|
|
N = 0.
|
|
accep_rate = 0.
|
|
sq_tau = np.sqrt(tau)
|
|
r_old = np.random.normal(loc=0., scale=1.0, size=(3))
|
|
d_old = drift(a,r_old)
|
|
d2_old = np.dot(d_old,d_old)
|
|
psi_old = psi(a,r_old)
|
|
for istep in range(nmax):
|
|
chi = np.random.normal(loc=0., scale=1.0, size=(3))
|
|
r_new = r_old + tau * d_old + sq_tau * chi
|
|
d_new = drift(a,r_new)
|
|
d2_new = np.dot(d_new,d_new)
|
|
psi_new = psi(a,r_new)
|
|
# Metropolis
|
|
prod = np.dot((d_new + d_old), (r_new - r_old))
|
|
argexpo = 0.5 * (d2_new - d2_old)*tau + prod
|
|
q = psi_new / psi_old
|
|
q = np.exp(-argexpo) * q*q
|
|
if np.random.uniform() < q:
|
|
accep_rate += 1.
|
|
r_old = r_new
|
|
d_old = d_new
|
|
d2_old = d2_new
|
|
psi_old = psi_new
|
|
N += 1.
|
|
E += e_loc(a,r_old)
|
|
return E/N, accep_rate/N
|
|
|
|
|
|
a = 0.9
|
|
nmax = 100000
|
|
tau = 1.0
|
|
X = [MonteCarlo(a,tau,nmax) for i in range(30)]
|
|
E, deltaE = ave_error([x[0] for x in X])
|
|
A, deltaA = ave_error([x[1] for x in X])
|
|
print(f"E = {E} +/- {deltaE}\nA = {A} +/- {deltaA}")
|