Skip to content

Fix: Correctly apply the phase in quilwaveforms #1408

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
notmgsk merged 4 commits into from
Nov 19, 2021
Merged

Fix: Correctly apply the phase in quilwaveforms #1408

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
2e3a7c4
Update quilwaveforms to correctly apply the phase
bramathon Nov 17, 2021
0523823
Merge branch 'rc' into patch-2
dbanty Nov 18, 2021
cad1f00
Update CHANGELOG.md
bramathon Nov 19, 2021
94afa8e
Merge branch 'rc' into patch-2
bramathon Nov 19, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions CHANGELOG.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@ Changelog

- Allow `np.ndarray` when writing QAM memory. Disallow non-integer and non-float types.
- Fix typo where `qc.compiler.calibration_program` should be `qc.compiler.get_calibration_program()`.
- Fixed typo where `scale` was being used as the `phase` in generation of several waveforms.

[v3.0.0](https://github.com/rigetti/pyquil/releases/tag/v3.0.0)
------------------------------------------------------------------------------------
Expand Down
10 changes: 5 additions & 5 deletions pyquil/quiltwaveforms.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -141,7 +141,7 @@ def samples(self, rate: float) -> np.ndarray:
ts = np.arange(self.num_samples(rate), dtype=np.complex128) / rate
sigma = 0.5 * self.fwhm / np.sqrt(2.0 * np.log(2.0))
iqs = np.exp(-0.5 * (ts - self.t0) ** 2 / sigma ** 2)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.scale, detuning=self.detuning)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.phase, detuning=self.detuning)


@waveform("drag_gaussian")
Expand Down Expand Up @@ -193,7 +193,7 @@ def samples(self, rate: float) -> np.ndarray:
env = np.exp(-0.5 * (ts - self.t0) ** 2 / sigma ** 2)
env_der = (self.alpha * (1.0 / (2 * np.pi * self.anh * sigma ** 2))) * (ts - self.t0) * env
iqs = env + 1.0j * env_der
return _update_envelope(iqs, rate, scale=self.scale, phase=self.scale, detuning=self.detuning)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.phase, detuning=self.detuning)


@waveform("hrm_gaussian")
Expand Down Expand Up @@ -263,7 +263,7 @@ def samples(self, rate: float) -> np.ndarray:
* (self.second_order_hrm_coeff * (exponent_of_t - 1) - 1)
)
iqs = env + 1.0j * env_der
return _update_envelope(iqs, rate, scale=self.scale, phase=self.scale, detuning=self.detuning)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.phase, detuning=self.detuning)


@waveform("erf_square")
Expand Down Expand Up @@ -313,7 +313,7 @@ def samples(self, rate: float) -> np.ndarray:
zeros_left = np.zeros(int(np.ceil(self.pad_left * rate)), dtype=np.complex128)
zeros_right = np.zeros(int(np.ceil(self.pad_right * rate)), dtype=np.complex128)
iqs = np.concatenate((zeros_left, vals, zeros_right))
return _update_envelope(iqs, rate, scale=self.scale, phase=self.scale, detuning=self.detuning)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.phase, detuning=self.detuning)


@waveform("boxcar_kernel")
Expand All @@ -340,4 +340,4 @@ def __str__(self) -> str:
def samples(self, rate: float) -> np.ndarray:
n = self.num_samples(rate)
iqs = np.full(n, 1.0 / n, dtype=np.complex128)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.scale, detuning=self.detuning)
return _update_envelope(iqs, rate, scale=self.scale, phase=self.phase, detuning=self.detuning)