Hi,
I am receiving NaN values when trying to create vibronic samples. The data I am using matches literature, so I don’t believe it is that. I have a suspicion it is due to there being zeros in my Li and Lf arrays. As I understand it, these are simply the cartesian coordinates for the normal modes. I have tried creating samples using different methods, but always receive the NaN error. If anyone could provide an explanation on how to solve this that would be appreciated.
import numpy as np
import strawberryfields as sf
from strawberryfields import ops
from strawberryfields.apps import qchem, data, plot
from strawberryfields.apps.qchem.vibronic import energies
from strawberryfields.apps.plot import spectrum
import matplotlib.pyplot as plt
ri, m, wi, Li = qchem.read_gamess(r"C:\ethenefreq.txt")
rf, mf, wff, Lf = qchem.read_gamess(r"C:\s1freq.txt")
wi = wi[6:] # ground state frequencies
wf = np.array([668.18, 675.79, 892.93, 900.56, 950.70, 1298.70, 1300.89, 1517.26, 2845.94, 2846.25, 2856.70, 2914.49]) # excited state frequencies
m = np.repeat(m, 3)
# Remove the first 6 arrays
Li = Li[6:]
# Reshape the array into a (18, 12) array
Li = np.reshape(Li, (18, 12))
# Remove the first 6 arrays
Lf = Lf[6:]
# Reshape the array into a (18, 12) array
Lf = np.reshape(Lf, (18, 12))
# Flatten the array
ri = ri.flatten()
# Flatten the array
rf = rf.flatten()
# Compute displacement vector and Duschinsky matrix
Ud, delta = qchem.duschinsky(Li, Lf, ri, rf, wf, m)
# map this information to GBS parameters
_, U1, r, U2, alpha = qchem.vibronic.gbs_params(wi, wf, Ud, delta)
# Generate Duschisnky matrix
plt.imshow(abs(Ud), cmap="Greens")
plt.colorbar()
plt.xlabel("Mode index")
plt.ylabel("Mode index")
plt.tight_layout()
plt.show()
# Number of modes
n_modes = len(wi)
# number of samples
nr_samples = 20000
# Generate samples and energies using qchem functions
s = qchem.vibronic.sample(t, U1, r, U2, alpha, nr_samples)
e = qchem.vibronic.energies(s, wi, wf)
plot.spectrum(e, xmin=-1000, xmax=8000)
ethenefreq.txt (60.7 KB)
s1freq.txt (60.1 KB)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[15], line 58
56 qchem.vibronic.VibronicTransition(U1, r, U2, alpha) | q
57 sf.ops.MeasureFock() | q
---> 58 samples = eng.run(gbs, shots=n_samples).samples.tolist()
60 n_mean = np.mean(samples, axis=0)
File ~\anaconda3\Lib\site-packages\strawberryfields\engine.py:570, in LocalEngine.run(self, program, args, compile_options, **kwargs)
565 if c.op.measurement_deps and eng_run_options["shots"] > 1:
566 raise NotImplementedError(
567 "Feed-forwarding of measurements cannot be used together with multiple shots."
568 )
--> 570 return super()._run(
571 program_lst, args=args, compile_options=compile_options, **eng_run_options
572 )
File ~\anaconda3\Lib\site-packages\strawberryfields\engine.py:306, in BaseEngine._run(self, program, args, compile_options, **kwargs)
303 p.bind_params(args)
304 p.lock()
--> 306 _, self.samples, self.samples_dict = self._run_program(p, **kwargs)
307 self.run_progs.append(p)
309 if isinstance(p, TDMProgram) and received_rolled:
File ~\anaconda3\Lib\site-packages\strawberryfields\engine.py:430, in LocalEngine._run_program(self, prog, **kwargs)
427 for cmd in prog.circuit:
428 try:
429 # try to apply it to the backend and, if op is a measurement, store it in values
--> 430 val = cmd.op.apply(cmd.reg, self.backend, **kwargs)
431 if val is not None:
432 for i, r in enumerate(cmd.reg):
File ~\anaconda3\Lib\site-packages\strawberryfields\ops.py:325, in Measurement.apply(self, reg, backend, **kwargs)
322 if _shots is None:
323 return None
--> 325 values = super().apply(reg, backend, **kwargs)
327 # store the results in the register reference objects
328 for v, r in zip(np.transpose(values), reg):
File ~\anaconda3\Lib\site-packages\strawberryfields\ops.py:228, in Operation.apply(self, reg, backend, **kwargs)
226 temp = [rr.ind for rr in reg]
227 # call the child class specialized _apply method
--> 228 return self._apply(temp, backend, **kwargs)
File ~\anaconda3\Lib\site-packages\strawberryfields\ops.py:1179, in MeasureFock._apply(self, reg, backend, shots, **kwargs)
1178 def _apply(self, reg, backend, shots=1, **kwargs):
-> 1179 samples = backend.measure_fock(reg, shots=shots, select=self.select, **kwargs)
1181 if isinstance(samples, list):
1182 samples = np.array(samples)
File ~\anaconda3\Lib\site-packages\strawberryfields\backends\gaussianbackend\backend.py:233, in GaussianBackend.measure_fock(self, modes, shots, select, **kwargs)
231 # check we are sampling from a gaussian state with zero mean
232 if allclose(mu, zeros_like(mu)):
--> 233 samples = hafnian_sample_state(reduced_cov, shots)
234 else:
235 samples = hafnian_sample_state(reduced_cov, shots, mean=reduced_mean)
File ~\anaconda3\Lib\site-packages\thewalrus\samples.py:361, in hafnian_sample_state(cov, samples, mean, hbar, cutoff, max_photons, parallel)
358 return np.vstack(results)
360 params = [cov, samples, mean, hbar, cutoff, max_photons]
--> 361 return _hafnian_sample(params)
File ~\anaconda3\Lib\site-packages\thewalrus\samples.py:311, in _hafnian_sample(args)
308 j = 0
310 while j < samples:
--> 311 result = generate_hafnian_sample(
312 cov, mean=mean, hbar=hbar, cutoff=cutoff, max_photons=max_photons
313 )
315 if result != -1:
316 # if result == -1, then you never get anything beyond cutoff
317 samples_array.append(result)
File ~\anaconda3\Lib\site-packages\thewalrus\samples.py:250, in generate_hafnian_sample(cov, mean, hbar, cutoff, max_photons)
247 norm_probs = probs.sum()
248 probs /= norm_probs
--> 250 det_outcome_i = np.random.choice(det_outcomes, p=probs)
251 det_pattern[mode] = det_outcome_i
253 if det_pattern[order_inv][-1] == cutoff:
File mtrand.pyx:954, in numpy.random.mtrand.RandomState.choice()
ValueError: probabilities contain NaN
Thanks 
Reece