def run_inf_trotter(N, h, st, dt, init_wf=None):
trotter_st = st
trotter_dt = dt
decay_rate = 1
mod = models.TransIsing1D(N, h, pbc=True)
if init_wf == None:
wf = nqs.brbm_nqs(N, N)
wf.W[:N, :] = .1 * np.eye(N, dtype=complex)
else:
wf = init_wf
meanS = []
stdS = []
print("Applying Trotter Evolution...")
for k in range(trotter_st):
print(k)
if True: #k%5==0:#True:#k==trotter_st-1:
print("Measuring SigmaX...")
M = {'E': 0, 'E2': 0}
S = sampler.metropolis(wf=wf)
S.afterSweep = lambda S: measure_sigmax(M, mod, S)
S.run(nsweeps=5000, output=False)
print(M['E'], np.sqrt(M['E2'] - M['E']**2))
meanS.append(M['E'][0, 0])
stdS.append(np.sqrt(M['E2'] - M['E']**2)[0, 0])
tao = trotter_dt * (decay_rate**(k / trotter_st))
mod.applyTrotterStep(wf, tao, inf=True)
return mod, wf, meanS, stdS
def run_inf_trotter(N, h, st, dt, init_wf=None):
trotter_st = st
trotter_dt = dt
decay_rate = 1
mod = models.TransIsing1D(N, h, pbc=True)
if init_wf == None:
wf = nqs.brbm_nqs(N, N)
#wf.W = .1*np.random.rand(N,N).astype(complex)
wf.W[:N, :] = .1 * np.eye(N, dtype=complex)
# for k in range(N):
# wf.W[N+k,k] = .2
# for k in range(N-1):
# wf.W[N+k,k+1] = .2
else:
wf = init_wf
meanE = []
stdE = []
print("Applying Trotter Evolution...")
for k in range(trotter_st):
# print('a', wf.nh)
# wf.rmVisibleInt()
# print('b', wf.nh)
# wf.rmHiddenNodes(keep=4*N)
print(k)
if k % 5 == 0: #True:#k==trotter_st-1:
print("Measuring Energy...")
M = {'E': 0, 'E2': 0, 'C': 0}
S = sampler.metropolis(wf=wf)
S.afterSweep = lambda S: measure(M, mod, S)
S.run(nsweeps=1000, output=False)
print(M['E'], np.sqrt(M['E2'] - M['E']**2))
meanE.append(M['E'][0, 0])
stdE.append(np.sqrt(M['E2'] - M['E']**2)[0, 0])
tao = trotter_dt * (decay_rate**(k / trotter_st))
mod.applyTrotterStep(wf, -1j * tao, inf=True)
return mod, wf, meanE, stdE
def run_real(N, h, st, dt):
mod = models.TransIsing1D(N, h, pbc=True)
H = mod.buildFullH()
A = np.eye(2**N, dtype=complex) - 1j * dt * H #- (dt**2)*H.dot(H)/2
psi = np.ones((2**N, 1), dtype=complex) / (2**(N / 2))
SX = []
for k in range(st):
print(k)
if k % 5 == 0:
print('measuring sx')
SX.append(sigmax(psi))
psi = A.dot(psi)
return SX
def run_trotter(N, h, st, dt, init_wf=None):
trotter_st = st
trotter_dt = dt
decay_rate = 1
mod = models.TransIsing1D(N, h, pbc=True)
if init_wf == None:
wf = nqs.bbm_nqs(N, 0)
else:
wf = init_wf
meanE = []
stdE = []
print("Applying Trotter Evolution...")
for k in range(trotter_st):
tao = trotter_dt * (decay_rate**(k / trotter_st))
mod.applyTrotterStep(wf, -1j * tao, renorm=True)
wf.rmHiddenNodes(keep=2 * N)
# wf.W = wf.W/np.max(wf.W)
print(k)
if True: #k%50==0:#k==trotter_st-1:
print("Measuring Energy...")
M = {'E': 0, 'E2': 0, 'C': 0}
S = sampler.metropolis(wf=wf.asRBM())
S.afterSweep = lambda S: measure(M, mod, S)
S.run(nsweeps=1000, output=False)
print(M['E'], np.sqrt(M['E2'] - M['E']**2))
meanE.append(M['E'][0, 0])
stdE.append(np.sqrt(M['E2'] - M['E']**2)[0, 0])
return mod, wf, meanE, stdE
def run_inf_trotter2(N, h, st, dt, init_wf=None):
trotter_st = st
trotter_dt = dt
decay_rate = 1
mod = models.TransIsing1D(N, h, pbc=True)
if init_wf == None:
wf = nqs.brbm_nqs(N, 0)
else:
wf = init_wf
meanE = []
stdE = []
print("Applying Trotter Evolution...")
for k in range(trotter_st):
# wf.rmHiddenNodes(keep=4*N)
print(k)
if True: #k==trotter_st-1:
print("Measuring SigmaX...")
M = {'E': 0, 'E2': 0, 'C': 0}
S = sampler.metropolis(wf=wf)
S.afterSweep = lambda S: measure_sigmax(M, mod, S)
S.run(nsweeps=1000, output=False)
print(M['E'], np.sqrt(M['E2'] - M['E']**2))
meanE.append(M['E'][0, 0])
stdE.append(np.sqrt(M['E2'] - M['E']**2)[0, 0])
tao = trotter_dt * (decay_rate**(k / trotter_st))
mod.applyTrotterStep(wf, tao, inf=True, hidden_crz=True)
return mod, wf, meanE, stdE
import numpy as np import nqs import models import sampler import optimize #wf = nqs.ti_brbm_nqs(nv=10,nf=1) wf = nqs.brbm_nqs(nv=10, nh=10) wf.setRandomParams() TI = models.TransIsing1D(nspins=10, hfield=.1) S = sampler.metropolis(wf=wf) O = optimize.energy_GD(S, TI)
import nqs
import models
import sampler
E = []
def measure(M,TI,S):
e = TI.localEnergy(S.wf,S.st)
# v = S.wf.varGradient(S.st)
M['E'] = M['E'] + (e-M['E'])/S.sweeps
E.append(e[0][0])
# ga = v['a'] * e
# gb = v['b'] * e
# gW = v['W'] * e
#
# M['ga'] = M['ga'] + (ga-M['ga'])/S.sweeps
# M['gb'] = M['gb'] + (gb-M['gb'])/S.sweeps
# M['gW'] = M['gW'] + (gW-M['gW'])/S.sweeps
wf = nqs.brbm_nqs.load_file('./carleo_code/Nqs/Ground/Ising1d_40_1_2.wf')
TI = models.TransIsing1D(nspins=40,hfield=1,pbc=False)
M = {'E':0,'ga':0,'gb':0,'gW':0}
S = sampler.metropolis(wf=wf)
S.afterSweep = lambda S: measure(M,TI,S)
S.run(nsweeps=3000,thermfactor=.1,output=True)