Merge pull request #21 from calculquebec/release

Release v0.4.0

README.md

@@ -36,7 +36,7 @@ pip install -e .
 
 Pennylane and other Python dependencies will be installed automatically during the installation process.
 
-The plugin will also take care of installing Julia and the required Julia packages, such as Snowflurry, PythonCall during the first run. Some notes on that matter are provided below.
+The plugin will also take care of installing Julia and the required Julia packages, such as Snowflurry and PythonCall during the first run. Some notes on that matter are provided below.
 
 If you wish to disable this behaviour, you can edit the julia_env.py file and set the value of the variable `IS_USER_CONFIGURED` to `TRUE`:
 
@@ -81,7 +81,7 @@ dev_def = qml.device("snowflurry.qubit", wires=1, shots=50)
 Example if you have an API key from Anyon Systems:
 
 ```py
-dev_def = qml.device("snowflurry.qubit", wires=1, shots=50, host="example.anyonsys.com", user="test_user",access_token="not_a_real_access_token")
+dev_def = qml.device("snowflurry.qubit", wires=1, shots=50, host="example.anyonsys.com", user="test_user",access_token="not_a_real_access_token", realm="realm_name")
 ```
 
 ## State of the project and known issues
@@ -91,3 +91,5 @@ This plugin is still very early in its development and aims to provide a basic i
 ### Future plans
 
 - Add a test suite to ensure the plugin works as expected.
+- Integrate a compiler to optimize the circuits.
+- Add device that allows for communication with MonarQ directly through its API.

pennylane_snowflurry/_version.py

@@ -17,4 +17,4 @@
 """
 
 
-__version__ = "0.3.0"
+__version__ = "0.4.0"

pennylane_snowflurry/julia_setup.py

@@ -6,7 +6,7 @@
 # Required packages for the Julia environment
 REQUIRED_PACKAGES = [
     PkgSpec(
-        name="Snowflurry", uuid="7bd9edc1-4fdc-40a1-a0f6-da58fb4f45ec", version="0.3"
+        name="Snowflurry", uuid="7bd9edc1-4fdc-40a1-a0f6-da58fb4f45ec", version="0.4"
     ),
 ]
 

pennylane_snowflurry/measurements/__init__.py

@@ -0,0 +1,6 @@
+from .measurement_strategy import MeasurementStrategy
+from .counts import Counts
+from .sample import Sample
+from .probabilities import Probabilities
+from .state import State
+from .expectation_value import ExpectationValue

pennylane_snowflurry/measurements/counts.py

@@ -0,0 +1,26 @@
+from .measurement_strategy import MeasurementStrategy
+from collections import Counter
+
+
+class Counts(MeasurementStrategy):
+
+    def __init__(self):
+        super().__init__()
+
+    def measure(self, converter, mp, shots):
+        if self.Snowflurry.currentClient is None:
+            converter.remove_readouts()
+            converter.apply_readouts(mp.obs)
+            shots_results = self.Snowflurry.simulate_shots(self.Snowflurry.sf_circuit, shots)
+            result = dict(Counter(shots_results))
+            return result
+        else:  # if we have a client, we use the real machine
+            converter.apply_readouts(mp.obs)
+            qpu = self.Snowflurry.AnyonYamaskaQPU(
+                self.Snowflurry.currentClient, self.Snowflurry.seval("project_id")
+            )
+            shots_results, time = self.Snowflurry.transpile_and_run_job(
+                qpu, self.Snowflurry.sf_circuit, shots
+            )
+            result = dict(Counter(shots_results))
+            return result

pennylane_snowflurry/measurements/expectation_value.py

@@ -0,0 +1,26 @@
+from .measurement_strategy import MeasurementStrategy
+import pennylane as qml
+from juliacall import convert
+import numpy as np
+
+
+class ExpectationValue(MeasurementStrategy):
+
+    def __init__(self):
+        super().__init__()
+
+    def measure(self, converter, mp, shots):
+        # FIXME : this measurement does work when the number of qubits measured is not equal to the number of qubits
+        #  in the circuit
+        # Requires some processing to work with larger matrices
+        converter.remove_readouts()
+        self.Snowflurry.result_state = self.Snowflurry.simulate(self.Snowflurry.sf_circuit)
+        if mp.obs is not None and mp.obs.has_matrix:
+            print(mp.obs)
+            observable_matrix = qml.matrix(mp.obs)
+            print(observable_matrix)
+            expected_value = self.Snowflurry.expected_value(
+                self.Snowflurry.DenseOperator(convert(self.Snowflurry.Matrix, observable_matrix)),
+                self.Snowflurry.result_state
+            )
+            return np.real(expected_value)

pennylane_snowflurry/measurements/measurement_strategy.py

@@ -0,0 +1,11 @@
+from abc import ABC, abstractmethod
+
+
+class MeasurementStrategy:
+
+    def __init__(self):
+        from pennylane_snowflurry.pennylane_converter import Snowflurry
+        self.Snowflurry = Snowflurry
+
+    def measure(self, converter, mp, shots):
+        pass

pennylane_snowflurry/measurements/probabilities.py

@@ -0,0 +1,19 @@
+from .measurement_strategy import MeasurementStrategy
+from juliacall import convert
+
+
+class Probabilities(MeasurementStrategy):
+
+    def __init__(self):
+        super().__init__()
+
+    def measure(self, converter, mp, shots):
+        converter.remove_readouts()
+        wires_list = mp.wires.tolist()
+        if len(wires_list) == 0:
+            return self.Snowflurry.get_measurement_probabilities(self.Snowflurry.sf_circuit)
+        else:
+            return self.Snowflurry.get_measurement_probabilities(
+                self.Snowflurry.sf_circuit,
+                convert(self.Snowflurry.Vector, [i + 1 for i in wires_list])
+            )

pennylane_snowflurry/measurements/sample.py

@@ -0,0 +1,27 @@
+from .measurement_strategy import MeasurementStrategy
+import numpy as np
+
+
+class Sample(MeasurementStrategy):
+
+    def __init__(self):
+        super().__init__()
+
+    def measure(self, converter, mp, shots):
+        if self.Snowflurry.currentClient is None:
+            converter.remove_readouts()
+            converter.apply_readouts(mp.obs)
+            shots_results = self.Snowflurry.simulate_shots(self.Snowflurry.sf_circuit, shots)
+            return np.asarray(shots_results).astype(int)
+        else:
+            converter.apply_readouts(mp.obs)
+            qpu = self.Snowflurry.AnyonYamaskaQPU(
+                self.Snowflurry.currentClient, self.Snowflurry.seval("project_id")
+            )
+            shots_results, time = self.Snowflurry.transpile_and_run_job(
+                qpu, self.Snowflurry.sf_circuit, shots,
+            )
+            return np.repeat(
+                [int(key) for key in shots_results.keys()],
+                [value for value in shots_results.values()],
+            )

pennylane_snowflurry/measurements/state.py

@@ -0,0 +1,16 @@
+from .measurement_strategy import MeasurementStrategy
+
+import numpy as np
+
+
+class State(MeasurementStrategy):
+
+    def __init__(self):
+        super().__init__()
+
+    def measure(self, converter, mp, shots):
+        converter.remove_readouts()
+        self.Snowflurry.result_state = self.Snowflurry.simulate(self.Snowflurry.sf_circuit)
+        # Convert the final state from pyjulia to a NumPy array
+        final_state_np = np.array([element for element in self.Snowflurry.result_state])
+        return final_state_np