def observe(total, cmdargs):
if total < 3:
print(" ".join(str(x) for x in cmdargs))
raise ValueError('Missing arguments')
inputname = cmdargs[1]
observname = cmdargs[2]
outputname = "dataObserve.hdf5"
if total == 4:
outputname = cmdargs[3]
# ---------------------------------------------------------------
para = Parameter(inputname)
Lat = Lattice(para)
ob = Observ(Lat)
print(Lat.Model)
dof = Dofs("SpinHalf") # default spin-1/2
if Lat.Model == "AKLT":
dof = Dofs("SpinOne")
# ------- Read dataSpec file -------
rfile = h5py.File('dataSpec.hdf5', 'r')
evalset = rfile["3.Eigen"]["Eigen Values"]
evecset = rfile["3.Eigen"]["Wavefunctions"]
# extract eigen value and eigen vector from HDF5 rfile
print(dof.hilbsize ** Lat.Nsite)
evals = np.zeros(para.Nstates, dtype=float)
evecs = np.zeros((dof.hilbsize ** Lat.Nsite, para.Nstates), dtype=complex)
evalset.read_direct(evals)
evecset.read_direct(evecs)
rfile.close()
# ------- Calculate spin response S(\omega) & write to HDF5---------
if observname == "spin_response":
print("Calculating S(omega)...")
tic = time.perf_counter()
SpinRes = ob.SpRe(evals, evecs, dof.type)
toc = time.perf_counter()
print(f"time = {toc-tic:0.4f} sec")
wfile = h5py.File(outputname, 'a')
if "Spin Response" in list(wfile.keys()):
wfile.__delitem__("Spin Response") # over write if existed
wfile.create_dataset("Spin Response", data=SpinRes)
wfile["Spin Response"].attrs["time"] = toc - tic
wfile.close()
# ------- Calculate spin conductivity & write to HDF5---------
elif observname == "spin_cond":
pass
# ------- Calculate energy conductivity & write to HDF5---------
elif observname == "energy_cond":
pass
# ------- Calculate Single-Magnon DOS & write to HDF5---------
elif observname == "singlemagnon":
print("Calculating Single-Magnon DOS...")
tic = time.perf_counter()
SMag = ob.SingleMagnon(evals, evecs, dof.type)
toc = time.perf_counter()
print(f"time = {toc-tic:0.4f} sec")
wfile = h5py.File(outputname, 'a')
if "Single-Magnon DOS" in list(wfile.keys()):
wfile.__delitem__("Single-Magnon DOS") # over write if existed
wfile.create_dataset("Single-Magnon DOS", data=SMag)
wfile["Single-Magnon DOS"].attrs["time"] = toc - tic
wfile.close()
# ------- Calculate SzSz DOS & write to HDF5---------
elif observname == "szsz":
print("Calculating SzSz spectrum...")
tic = time.perf_counter()
SZSZ = ob.SzSz(evals, evecs, dof.type)
toc = time.perf_counter()
print(f"time = {toc-tic:0.4f} sec")
wfile = h5py.File(outputname, 'a')
if "SzSz" in list(wfile.keys()):
wfile.__delitem__("SzSz") # over write if existed
wfile.create_dataset("SzSz", data=SZSZ)
wfile["SzSz"].attrs["time"] = toc - tic
wfile.close()
# ------- Calculate SpSm DOS & write to HDF5---------
elif observname == "spsm":
print("Calculating SpSm spectrum...")
tic = time.perf_counter()
SPSM = ob.SpSm(evals, evecs, dof.type)
toc = time.perf_counter()
print(f"time = {toc - tic:0.4f} sec")
wfile = h5py.File(outputname, 'a')
if "SpSm" in list(wfile.keys()):
wfile.__delitem__("SpSm") # over write if existed
wfile.create_dataset("SpSm", data=SPSM)
wfile["SpSm"].attrs["time"] = toc - tic
wfile.close()
# ------- Calculate energy current of TFIM & write to HDF5---------
elif observname == "ecurrent1":
site = 2
if para.Model != "TFIM":
raise ValueError("ecurrent1 is designed for TFIM exclusively")
print("Calculating energy current of TFIM...")
tic = time.perf_counter()
mEcurr = ob.ecurrent1(evals, evecs, site)
toc = time.perf_counter()
print(f"time = {toc - tic:0.4f} sec")
print("Current at site=", site, "is ", mEcurr)
else:
raise ValueError("Observable not supported yet")
2000: (2.5312e3, 0.284779, None),
2300: (2.5312e3, 0.284779, None),
2600: (2.5312e3, 0.284779, None),
}
param.z3 = MultiFreqImpType()
param.z3.rlc_s = {
1700: (0.1, 4.2e-3, None),
2000: (0.1, 4.2e-3, None),
2300: (0.1, 4.2e-3, None),
2600: (0.1, 4.2e-3, None),
}
param.zc = MultiFreqImpType()
param.zc.rlc_s = {
1700: (None, None, 2.35e-3),
2000: (None, None, 2.35e-3),
2300: (None, None, 2.35e-3),
2600: (None, None, 2.35e-3),
}
param.n = {
1700: 13.5,
2000: 13.5,
2300: 12,
2600: 12,
}
Parameter.param_dict_to_pkl(param_dict)
pass
def main(total, cmdargs):
if total != 2:
print(" ".join(str(x) for x in cmdargs))
raise ValueError('Missing arguments')
inputname = cmdargs[1]
sys.stdout = Logger() # for exporting the logfile
# ----------------------- Build and Diagonalize ---------------------------------
para = Parameter(inputname) # import parameters from input.inp
Lat = Lattice(para) # Build lattice
ob = Observ(Lat) # initialize observables
tic = time.perf_counter()
Hamil = Hamiltonian(Lat) # Build Hamiltonian
ham = Hamil.Ham # Hamiltonian as sparse matrix
toc = time.perf_counter()
print(f"Hamiltonian construction time = {toc - tic:0.4f} sec")
tic = time.perf_counter()
evals, evecs = primme.eigsh(ham, para.Nstates, tol=1e-12, which='SA')
evals, evecs = sort(evals, evecs)
toc = time.perf_counter()
evals = np.round(evals, 10)
print("\n-----------Beg of Eigen Values-----------\n", *evals, sep='\n')
print("\n-----------End of Eigen Values-----------")
print(f"Diagonalization time = {toc - tic:0.4f} sec \n\n")
# -------------- Entanglement properties of GS -----------
if para.Option is not None:
if "EE" in para.Option:
EntS, Entvec = ob.EntSpec(
evecs[:, 0]) # Entanglement spectrum and vector
EntS = np.round(EntS, decimals=10)
EntS_log = np.zeros(len(EntS))
for i in range(len(EntS)):
if EntS[i] <= 0:
EntS_log[i] = 0
else:
EntS_log[i] = math.log(EntS[i])
EE = -np.around(np.dot(EntS, EntS_log), decimals=8)
print("Entanglement Spectrum=\n", EntS)
print("Entanglement Entropy=", EE)
# ------------------------ Ascii Ostream for EE--------
file = open("entspec.dat", "w")
# For a U-scan of Bose-Hubbard model
if para.Model == "Bose_Hubbard":
for i in range(EntS.size):
file.write(str(abs(para.U)) + " " + str(EntS[i]))
file.write("\n")
else:
for i in range(EntS.size):
file.write(str(abs(para.Hx)) + " " + str(EntS[i]))
file.write("\n")
# ------------------------ Hdf5 Ostream (Big Data Storage) ------------------------------
# ------------------------ Hdf5 Ostream (Big Data Storage) ------------------------------
# ------------------------ Hdf5 Ostream (Big Data Storage) ------------------------------
tic = time.perf_counter()
file = h5py.File('dataSpec.hdf5', 'w')
file.attrs["LLX"] = para.LLX
file.attrs["LLY"] = para.LLY
file.attrs["IsPeriodicX"] = para.IsPeriodicX
file.attrs["IsPeriodicY"] = para.IsPeriodicY
file.attrs["Kx"] = para.Kxx
file.attrs["Ky"] = para.Kyy
file.attrs["Kz"] = para.Kzz
file.attrs["Hx"] = para.Hz
file.attrs["Hy"] = para.Hy
file.attrs["Hz"] = para.Hz
file.attrs["#States2Keep"] = para.Nstates
file.attrs["Model"] = para.Model
file.attrs["Nsites"] = Lat.Nsite
LatGrp = file.create_group("1.Lattice")
LatGrp.create_dataset("Mesh", data=Lat.mesh_)
LatGrp.create_dataset("Nearest Neighbors", data=Lat.nn_)
ConnGrp = file.create_group("2.Connectors")
if para.Model == "Heisenberg_Square" or para.Model == "Kitaev":
ConnGrp.create_dataset("KxxGraph", data=Hamil.KxxGraph_)
ConnGrp.create_dataset("KyyGraph", data=Hamil.KyyGraph_)
ConnGrp.create_dataset("KzzGraph", data=Hamil.KzzGraph_)
elif para.Model == "AKLT":
ConnGrp.create_dataset("Kxx1Graph", data=Hamil.Kxx1Graph_)
ConnGrp.create_dataset("Kyy1Graph", data=Hamil.Kyy1Graph_)
ConnGrp.create_dataset("Kzz1Graph", data=Hamil.Kzz1Graph_)
ConnGrp.create_dataset("Kxx2Graph", data=Hamil.Kxx2Graph_)
ConnGrp.create_dataset("Kyy2Graph", data=Hamil.Kyy2Graph_)
ConnGrp.create_dataset("Kzz2Graph", data=Hamil.Kzz2Graph_)
elif para.Model == "Bose_Hubbard":
ConnGrp.create_dataset("tGraph", data=Hamil.tGraph_)
EigGrp = file.create_group("3.Eigen")
EigGrp.create_dataset("Eigen Values", data=evals)
EigGrp.create_dataset("Wavefunctions", data=evecs)
if para.Option is not None:
if "EE" in para.Option:
EigGrp = file.create_group("4.Entanglment")
EigGrp.create_dataset("ES", data=EntS)
EigGrp.create_dataset("ESlog", data=EntS_log)
EigGrp.create_dataset("EE", data=EE)
file.close()
toc = time.perf_counter()
print(f"\nHDF5 time = {toc - tic:0.4f} sec")