def run_ES(parameters, model:MODEL, utils):
n_step = parameters['n_step']
n_protocol = 2**n_step
exact_data = np.zeros((n_protocol,2), dtype=np.float64) # 15 digits precision
b2_array = lambda n10 : np.array(list(np.binary_repr(n10, width=n_step)), dtype=np.int)
st=time.time()
# ---> measuring estimated time <---
model.update_protocol(b2_array(0))
psi = model.compute_evolved_state()
model.compute_fidelity(psi_evolve=psi)
model.compute_energy(psi_evolve=psi)
print("Est. run time : \t %.3f s"%(0.5*n_protocol*(time.time()-st)))
# ---> Starting real calculation <---
st=time.time()
for p in range(n_protocol):
model.update_protocol(b2_array(p))
psi = model.compute_evolved_state()
exact_data[p] = (model.compute_fidelity(psi_evolve=psi), model.compute_energy(psi_evolve=psi))
outfile = utils.make_file_name(parameters,root=parameters['root'])
with open(outfile,'wb') as f:
pickle.dump(exact_data, f, protocol=4)
print("Total run time : \t %.3f s"%(time.time()-st))
print("\n Thank you and goodbye !")
f.close()
def main():
# Reading parameters from para.dat file
parameters = utils.read_parameter_file()
# Printing parameters for user
utils.print_parameters(parameters)
# Defining Hamiltonian
H = HAMILTONIAN(**parameters)
# Defines the model, and precomputes evolution matrices given set of states
model = MODEL(H, parameters)
L = 6
T = 0.1
n_step = 28
param = {'L' : L, 'T': T, 'n_step': n_step}
file_name = make_file_name(param, root= "/projectnb/fheating/SGD/ES/dynamicQL/SA/ES/data/")
with open(file_name, 'rb') as f:
fidelities=pickle.load(f)
nfid=fidelities.shape[0]
fid_and_energy=np.empty((nfid,2),dtype=np.float)
for i,f in zip(range(nfid),fidelity):
if i%10000 == 0: print(i)
model.update_protocol(b2_array(i, w = 28))
psi = model.compute_evolved_state()
fid_and_energy[i][0]=model.compute_fidelity(psi_evolve = psi)
fid_and_energy[i][1]=model.compute_energy(psi_evolve = psi)
print(fid_and_energy[0],'\t',f)
break
with open("ES_L-06_T-0.500_n_step-28-test.pkl", ‘wb’) as f:
fidelities=pickle.dump(fid_and_energy,f, protocol=4)
