diff --git a/poetry.lock b/poetry.lock
index ba6c7d79e..bab5c8fe7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,13 +2,13 @@
[[package]]
name = "absl-py"
-version = "1.4.0"
+version = "2.0.0"
description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
optional = true
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+python-versions = ">=3.7"
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@@ -116,6 +116,24 @@ files = [
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wheel = ">=0.23.0,<1.0"
+[[package]]
+name = "attrs"
+version = "23.1.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.7"
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+[package.extras]
+cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
+dev = ["attrs[docs,tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+
[[package]]
name = "babel"
version = "2.12.1"
@@ -338,59 +356,72 @@ test = ["flake8 (==3.7.8)", "hypothesis (==3.55.3)"]
[[package]]
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+ {file = "Pillow-10.0.1.tar.gz", hash = "sha256:d72967b06be9300fed5cfbc8b5bafceec48bf7cdc7dab66b1d2549035287191d"},
]
[package.extras]
@@ -2167,13 +2177,13 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-co
[[package]]
name = "plotly"
-version = "5.16.1"
+version = "5.17.0"
description = "An open-source, interactive data visualization library for Python"
optional = false
python-versions = ">=3.6"
files = [
- {file = "plotly-5.16.1-py2.py3-none-any.whl", hash = "sha256:19cc34f339acd4e624177806c14df22f388f23fb70658b03aad959a0e650a0dc"},
- {file = "plotly-5.16.1.tar.gz", hash = "sha256:295ac25edeb18c893abb71dcadcea075b78fd6fdf07cee4217a4e1009667925b"},
+ {file = "plotly-5.17.0-py2.py3-none-any.whl", hash = "sha256:7c84cdf11da162423da957bb093287134f2d6f170eb9a74f1459f825892247c3"},
+ {file = "plotly-5.17.0.tar.gz", hash = "sha256:290d796bf7bab87aad184fe24b86096234c4c95dcca6ecbca02d02bdf17d3d97"},
]
[package.dependencies]
@@ -3443,28 +3453,28 @@ telegram = ["requests"]
[[package]]
name = "traitlets"
-version = "5.9.0"
+version = "5.10.0"
description = "Traitlets Python configuration system"
optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
files = [
- {file = "traitlets-5.9.0-py3-none-any.whl", hash = "sha256:9e6ec080259b9a5940c797d58b613b5e31441c2257b87c2e795c5228ae80d2d8"},
- {file = "traitlets-5.9.0.tar.gz", hash = "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"},
+ {file = "traitlets-5.10.0-py3-none-any.whl", hash = "sha256:417745a96681fbb358e723d5346a547521f36e9bd0d50ba7ab368fff5d67aa54"},
+ {file = "traitlets-5.10.0.tar.gz", hash = "sha256:f584ea209240466e66e91f3c81aa7d004ba4cf794990b0c775938a1544217cd1"},
]
[package.extras]
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.5.1)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
[[package]]
name = "typing-extensions"
-version = "4.7.1"
-description = "Backported and Experimental Type Hints for Python 3.7+"
+version = "4.8.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
files = [
- {file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"},
- {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
+ {file = "typing_extensions-4.8.0-py3-none-any.whl", hash = "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0"},
+ {file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"},
]
[[package]]
@@ -3548,14 +3558,21 @@ test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
[[package]]
name = "wmctrl"
-version = "0.4"
+version = "0.5"
description = "A tool to programmatically control windows inside X"
optional = false
-python-versions = "*"
+python-versions = ">=2.7"
files = [
- {file = "wmctrl-0.4.tar.gz", hash = "sha256:66cbff72b0ca06a22ec3883ac3a4d7c41078bdae4fb7310f52951769b10e14e0"},
+ {file = "wmctrl-0.5-py2.py3-none-any.whl", hash = "sha256:ae695c1863a314c899e7cf113f07c0da02a394b968c4772e1936219d9234ddd7"},
+ {file = "wmctrl-0.5.tar.gz", hash = "sha256:7839a36b6fe9e2d6fd22304e5dc372dbced2116ba41283ea938b2da57f53e962"},
]
+[package.dependencies]
+attrs = "*"
+
+[package.extras]
+test = ["pytest"]
+
[[package]]
name = "wrapt"
version = "1.14.1"
@@ -3631,17 +3648,17 @@ files = [
[[package]]
name = "zipp"
-version = "3.16.2"
+version = "3.17.0"
description = "Backport of pathlib-compatible object wrapper for zip files"
optional = false
python-versions = ">=3.8"
files = [
- {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
- {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
+ {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
+ {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
]
[package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
[extras]
diff --git a/src/qibocal/protocols/characterization/two_qubit_interaction/chevron.py b/src/qibocal/protocols/characterization/two_qubit_interaction/chevron.py
index b77f6000f..26e2b38f8 100644
--- a/src/qibocal/protocols/characterization/two_qubit_interaction/chevron.py
+++ b/src/qibocal/protocols/characterization/two_qubit_interaction/chevron.py
@@ -9,12 +9,15 @@
from qibolab import AcquisitionType, AveragingMode, ExecutionParameters
from qibolab.platform import Platform
from qibolab.pulses import PulseSequence
-from qibolab.qubits import QubitId
+from qibolab.qubits import QubitPairId
from qibolab.sweeper import Parameter, Sweeper, SweeperType
+from scipy.optimize import curve_fit
from qibocal.auto.operation import Data, Parameters, Qubits, Results, Routine
-from .utils import order_pair
+from .utils import fit_flux_amplitude, order_pair
+
+COLORAXIS = ["coloraxis2", "coloraxis1"]
@dataclass
@@ -37,6 +40,8 @@ class ChevronParameters(Parameters):
"""Time delay between flux pulses and readout."""
nshots: Optional[int] = None
"""Number of shots per point."""
+ relaxation_time: Optional[int] = None
+ """Relaxation time [ns]"""
parking: bool = True
"""Wether to park non interacting qubits or not."""
@@ -45,9 +50,19 @@ class ChevronParameters(Parameters):
class ChevronResults(Results):
"""CzFluxTime outputs when fitting will be done."""
+ amplitude: dict[QubitPairId, float]
+ """CZ angle."""
+ duration: dict[QubitPairId, int]
+ """Virtual Z phase correction."""
+
ChevronType = np.dtype(
- [("amp", np.float64), ("length", np.float64), ("prob", np.float64)]
+ [
+ ("amp", np.float64),
+ ("length", np.float64),
+ ("prob_high", np.float64),
+ ("prob_low", np.float64),
+ ]
)
"""Custom dtype for Chevron."""
@@ -56,26 +71,18 @@ class ChevronResults(Results):
class ChevronData(Data):
"""Chevron acquisition outputs."""
- data: dict[tuple[QubitId, QubitId, QubitId], npt.NDArray[ChevronType]] = field(
- default_factory=dict
- )
+ data: dict[QubitPairId, npt.NDArray[ChevronType]] = field(default_factory=dict)
- def register_qubit(self, low_qubit, high_qubit, qubit, length, amp, prob):
+ def register_qubit(self, low_qubit, high_qubit, length, amp, prob_low, prob_high):
"""Store output for single qubit."""
size = len(length) * len(amp)
amplitude, duration = np.meshgrid(amp, length)
ar = np.empty(size, dtype=ChevronType)
ar["length"] = duration.ravel()
ar["amp"] = amplitude.ravel()
- ar["prob"] = prob.ravel()
- self.data[low_qubit, high_qubit, qubit] = np.rec.array(ar)
-
- def __getitem__(self, pair):
- return {
- index: value
- for index, value in self.data.items()
- if set(pair).issubset(index)
- }
+ ar["prob_low"] = prob_low.ravel()
+ ar["prob_high"] = prob_high.ravel()
+ self.data[low_qubit, high_qubit] = np.rec.array(ar)
def _aquisition(
@@ -168,63 +175,136 @@ def _aquisition(
sweeper_duration,
sweeper_amplitude,
)
- for qubit in ordered_pair:
- result = results[qubit]
- prob = result.magnitude
- data.register_qubit(
- ordered_pair[0],
- ordered_pair[1],
- qubit,
- delta_duration_range,
- delta_amplitude_range,
- prob,
- )
+ data.register_qubit(
+ ordered_pair[0],
+ ordered_pair[1],
+ delta_duration_range,
+ delta_amplitude_range,
+ results[ordered_pair[0]].magnitude,
+ results[ordered_pair[1]].magnitude,
+ )
return data
+# fitting function for single row in chevron plot (rabi-like curve)
+def cos(x, omega, phase, amplitude, offset):
+ return amplitude * np.cos(x * omega + phase) + offset
+
+
+def _fit(data: ChevronData) -> ChevronResults:
+ durations = {}
+ amplitudes = {}
+ for pair in data.data:
+ pair_amplitude = []
+ pair_duration = []
+ amps = np.unique(data[pair].amp)
+ times = np.unique(data[pair].length)
+
+ for qubit in pair:
+ msr = data[pair].prob_low if pair[0] == qubit else data[pair].prob_high
+ msr_matrix = msr.reshape(len(times), len(amps)).T
+
+ # guess amplitude computing FFT
+ amplitude, index, delta = fit_flux_amplitude(msr_matrix, amps, times)
+ # estimate duration by rabi curve at amplitude previously estimated
+ y = msr_matrix[index, :].ravel()
+
+ popt, _ = curve_fit(cos, times, y, p0=[delta, 0, np.mean(y), np.mean(y)])
+
+ # duration can be estimated as the period of the oscillation
+ duration = 1 / (popt[0] / 2 / np.pi)
+ pair_amplitude.append(amplitude)
+ pair_duration.append(duration)
+
+ amplitudes[pair] = np.mean(pair_amplitude)
+ durations[pair] = int(np.mean(duration))
+
+ return ChevronResults(amplitude=amplitudes, duration=durations)
+
+
def _plot(data: ChevronData, fit: ChevronResults, qubit):
"""Plot the experiment result for a single pair."""
- colouraxis = ["coloraxis", "coloraxis2"]
+
+ # reverse qubit order if not found in data
+ if qubit not in data.data:
+ qubit = (qubit[1], qubit[0])
+
pair_data = data[qubit]
- # order qubits
- qubits = next(iter(pair_data))[:2]
fig = make_subplots(
rows=1,
cols=2,
subplot_titles=(
- f"Qubit {qubits[0]} - Low Frequency",
- f"Qubit {qubits[1]} - High Frequency",
+ f"Qubit {qubit[0]} - Low Frequency",
+ f"Qubit {qubit[1]} - High Frequency",
),
)
- fit_report = None
- for target, control, measure in pair_data:
- fig.add_trace(
- go.Heatmap(
- x=pair_data[target, control, measure].length,
- y=pair_data[target, control, measure].amp,
- z=pair_data[target, control, measure].prob,
- coloraxis=colouraxis[0 if measure == qubits[0] else 1],
- ),
- row=1,
- col=1 if measure == qubits[0] else 2,
- )
+ fitting_report = None
+
+ fig.add_trace(
+ go.Heatmap(
+ x=pair_data.length,
+ y=pair_data.amp,
+ z=pair_data.prob_low,
+ coloraxis=COLORAXIS[0],
+ ),
+ row=1,
+ col=1,
+ )
- fig.update_layout(
- xaxis_title="Duration [ns]",
- xaxis2_title="Duration [ns]",
- yaxis_title="Amplitude [dimensionless]",
- legend_title="States",
- )
- fig.update_layout(
- coloraxis={"colorscale": "Oryel", "colorbar": {"x": -0.15}},
- coloraxis2={"colorscale": "Darkmint", "colorbar": {"x": 1.15}},
- )
- return [fig], fit_report
+ fig.add_trace(
+ go.Heatmap(
+ x=pair_data.length,
+ y=pair_data.amp,
+ z=pair_data.prob_high,
+ coloraxis=COLORAXIS[1],
+ ),
+ row=1,
+ col=2,
+ )
+ for measured_qubit in qubit:
+ if fit is not None:
+ fig.add_trace(
+ go.Scatter(
+ x=[
+ fit.duration[qubit],
+ ],
+ y=[
+ fit.amplitude[qubit],
+ ],
+ mode="markers",
+ marker=dict(
+ size=8,
+ color="black",
+ symbol="cross",
+ ),
+ name="CZ estimate",
+ showlegend=True if measured_qubit == qubit[0] else False,
+ legendgroup="Voltage",
+ ),
+ row=1,
+ col=1 if measured_qubit == qubit[0] else 2,
+ )
-def _fit(data: ChevronData) -> ChevronResults:
- return ChevronResults()
+ fig.update_layout(
+ xaxis_title="Duration [ns]",
+ xaxis2_title="Duration [ns]",
+ yaxis_title="Amplitude [dimensionless]",
+ legend=dict(orientation="h"),
+ )
+ fig.update_layout(
+ coloraxis={"colorscale": "Oryel", "colorbar": {"x": 1.15}},
+ coloraxis2={"colorscale": "Darkmint", "colorbar": {"x": -0.15}},
+ )
+
+ if fit is not None:
+ reports = []
+ reports.append(f"{qubit[1]} | CZ amplitude: {fit.amplitude[qubit]:.4f}
")
+ reports.append(f"{qubit[1]} | CZ duration: {fit.duration[qubit]}
")
+ fitting_report = "".join(list(dict.fromkeys(reports)))
+
+ return [fig], fitting_report
chevron = Routine(_aquisition, _fit, _plot)
diff --git a/src/qibocal/protocols/characterization/two_qubit_interaction/cz_virtualz.py b/src/qibocal/protocols/characterization/two_qubit_interaction/cz_virtualz.py
index 6c5d69389..e46eb22b6 100644
--- a/src/qibocal/protocols/characterization/two_qubit_interaction/cz_virtualz.py
+++ b/src/qibocal/protocols/characterization/two_qubit_interaction/cz_virtualz.py
@@ -247,9 +247,7 @@ def _fit(
virtual_phase = {}
cz_angle = {}
for pair in pairs:
- pair_data = data[pair]
- qubits = next(iter(pair_data))[:2]
- virtual_phase[qubits] = {}
+ virtual_phase[pair] = {}
for target, control, setup in data[pair]:
target_data = data[pair][target, control, setup].target
pguess = [
@@ -261,7 +259,7 @@ def _fit(
try:
popt, _ = curve_fit(
fit_function,
- np.array(data.thetas) + data.vphases[qubits][target],
+ np.array(data.thetas) + data.vphases[pair][target],
target_data,
p0=pguess,
bounds=((0, 0, 0), (2.5, 2.5, 2 * np.pi)),
@@ -280,7 +278,7 @@ def _fit(
fitted_parameters[target_q, control_q, "X"][2]
- fitted_parameters[target_q, control_q, "I"][2]
)
- virtual_phase[qubits][target_q] = fitted_parameters[
+ virtual_phase[pair][target_q] = -fitted_parameters[
target_q, control_q, "I"
][2]
@@ -358,9 +356,11 @@ def _plot(data: CZVirtualZData, fit: CZVirtualZResults, qubit):
col=1 if fig == fig1 else 2,
)
- reports.append(f"{target} | CZ angle: {fit.cz_angle[target, control]}
")
reports.append(
- f"{target} | Virtual Z phase: { - fit.virtual_phase[qubits][target]}
"
+ f"{target} | CZ angle: {fit.cz_angle[target, control]:.4f}
"
+ )
+ reports.append(
+ f"{target} | Virtual Z phase: {fit.virtual_phase[qubit][target]:.4f}
"
)
fitting_report = "".join(list(dict.fromkeys(reports)))
diff --git a/src/qibocal/protocols/characterization/two_qubit_interaction/utils.py b/src/qibocal/protocols/characterization/two_qubit_interaction/utils.py
index a0e6f2ddd..41912bd89 100644
--- a/src/qibocal/protocols/characterization/two_qubit_interaction/utils.py
+++ b/src/qibocal/protocols/characterization/two_qubit_interaction/utils.py
@@ -1,4 +1,11 @@
+from statistics import median_high
+
+import numpy as np
from qibolab.qubits import Qubit, QubitId
+from scipy.signal import find_peaks
+
+RANDOM_HIGH_VALUE = 1e6
+"""High value to avoid None when computing FFT."""
def order_pair(pair: list[QubitId, QubitId], qubits: dict[QubitId, Qubit]) -> tuple:
@@ -6,3 +13,55 @@ def order_pair(pair: list[QubitId, QubitId], qubits: dict[QubitId, Qubit]) -> tu
if qubits[pair[0]].drive_frequency > qubits[pair[1]].drive_frequency:
return pair[1], pair[0]
return pair[0], pair[1]
+
+
+def fit_flux_amplitude(matrix, amps, times):
+ """Estimate amplitude for CZ gate.
+
+
+ Given the pattern of a chevron plot (see for example Fig. 2 here
+ https://arxiv.org/pdf/1907.04818.pdf). This function estimates
+ the CZ amplitude by finding the amplitude which gives the highest
+ oscillation period. In case there are multiple values with the same
+ period, given the symmetry, the median value is chosen.
+ The FFT also gives a first estimate for the duration of the CZ gate.
+
+ Args:
+ matrix (np.ndarray): msr matrix
+ amps (np.ndarray): amplitudes swept
+ times (np.ndarray): duration swept
+
+ Returns:
+ amplitude (float): estimated amplitude
+ index (int): amplitude index
+ delta (float): omega for estimated amplitude
+ """
+
+ size_amp = len(amps)
+ time_step = times[1] - times[0]
+ fs = []
+ for i in range(size_amp):
+ y = matrix[i, :]
+ ft = np.fft.rfft(y) / len(y)
+ mags = abs(ft)[1:]
+ local_maxima = find_peaks(mags, height=0)
+ peak_heights = local_maxima[1]["peak_heights"]
+ # Select the frequency with the highest peak
+ index = (
+ int(local_maxima[0][np.argmax(peak_heights)] + 1)
+ if len(local_maxima[0]) > 0
+ else None
+ )
+
+ sampling_freq = 1 / time_step
+ values = np.arange(int(len(y) / 2))
+ period = len(y) / sampling_freq
+ frequencies = values / period
+ f = frequencies[index] if index is not None else RANDOM_HIGH_VALUE
+ fs.append(2 * np.pi * f)
+
+ low_freq_interval = np.where(fs == np.min(fs))
+ amplitude = median_high(amps[low_freq_interval])
+ index = int(np.where(np.unique(amps) == amplitude)[0])
+ delta = np.min(fs)
+ return amplitude, index, delta