Merge pull request #111 from qtzhuang/zqt

Add some pre-build circuit templates and tests

quafu/algorithms/embedding/angle.py

@@ -0,0 +1,57 @@
+# (C) Copyright 2023 Beijing Academy of Quantum Information Sciences
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Angel Embedding in Quantum Data embedding"""
+from quafu.circuits import QuantumCircuit
+import quafu.elements.element_gates as qeg
+import numpy as np
+
+ROT = {"X": qeg.RXGate, "Y": qeg.RYGate, "Z": qeg.RZGate}
+
+class AngleEmbedding:
+    def __init__(self, features, num_qubits: int, rotation="X"):
+        """
+        Args:
+            features(np.array): The data to be embedded
+            num_qubits(int): the number of qubit
+            rotation(str): type of rotations used
+        """
+        if rotation not in ROT:
+            raise ValueError(f"Rotation option {rotation} not recognized.")
+
+        shape = np.shape(features)[-1:]
+        n_features = shape[0]
+        if n_features != num_qubits:
+            raise ValueError(
+                "The length of Features must match num_qubits"
+            )
+        self.features = features
+        self.num_qubits = num_qubits
+        self.op = ROT[rotation]
+
+        """Build the embedding circuit and get the gate_list"""
+        self.gate_list = self._build()
+
+    def _build(self):
+        gate_list = []
+        for i in range(self.num_qubits):
+            gate = self.op(pos=i, paras=self.features[i])
+            gate_list.append(gate)
+        return gate_list
+
+    def __iter__(self):
+        return iter(self.gate_list)
+
+    def __getitem__(self, index):
+        return self.gate_list[index]

quafu/algorithms/layers/basic_entangle.py

@@ -0,0 +1,80 @@
+# (C) Copyright 2023 Beijing Academy of Quantum Information Sciences
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Layers consisting of one-parameter single-qubit rotations on each qubit, followed by a closed chain or ring of CNOT gates"""
+from quafu.circuits import QuantumCircuit
+import quafu.elements.element_gates as qeg
+import numpy as np
+
+ROT = {"X": qeg.RXGate, "Y": qeg.RYGate, "Z": qeg.RZGate}
+
+class BasicEntangleLayers:
+    def __init__(self, weights, num_qubits, rotation="X"):
+        """
+        Args:
+            weights(array): Each weight is used as a parameter for the rotation
+            num_qubits(int): the number of qubit
+            rotation(str): one-parameter single-qubit gate to use
+        """
+        weights = np.asarray(weights)
+        """convert weights to numpy array if weights is list otherwise keep unchanged"""
+        shape = np.shape(weights)
+
+        ##TODO(qtzhuang): If weights are batched, i.e. dim>3, additional processing is required
+        if weights.ndim > 2:
+            raise ValueError(
+                f"Weights tensor must be 2-dimensional "
+            )
+
+        if not (len(shape) == 3 or len(shape) == 2):  # 3 is when batching, 2 is no batching
+            raise ValueError(
+                f"Weights tensor must be 2-dimensional "
+                f"or 3-dimensional if batching; got shape {shape}"
+            )
+
+        if shape[-1] != num_qubits:
+            # index with -1 since we may or may not have batching in first dimension
+            raise ValueError(
+                f"Weights tensor must have last dimension of length {num_qubits}; got {shape[-1]}"
+            )
+        self.weights = weights
+        self.num_qubits = num_qubits
+        self.op = ROT[rotation]
+
+        """Build the quantum basic_entangle layer and get the gate_list"""
+        self.gate_list = self._build()
+
+    def _build(self):
+        repeat = np.shape(self.weights)[-2]
+        gate_list = []
+        for layer in range(repeat):
+            for i in range(self.num_qubits):
+                gate = self.op(pos=i, paras=self.weights[layer][i])
+                gate_list.append(gate)
+
+            # if num_qubits equals two, it just need to apply CNOT one time
+            if self.num_qubits == 2:
+                gate_list.append(qeg.CXGate(0,1))
+
+            elif self.num_qubits > 2:
+                for i in range(self.num_qubits):
+                    gate_list.append(qeg.CXGate(i,(i+1)%self.num_qubits))
+
+        return gate_list
+
+    def __iter__(self):
+        return iter(self.gate_list)
+
+    def __getitem__(self, index):
+        return self.gate_list[index]

quafu/circuits/quantum_circuit.py

@@ -105,6 +105,11 @@ def gates(self):
     @gates.setter
     def gates(self, gates:list):
         self._gates = gates
+
+    #TODO(qtzhuang): add_gates is just a temporary call function to add gate from gate_list
+    def add_gates(self, gates: list):
+        for gate in gates:
+            self.add_gate(gate)
 
     def add_gate(self, gate: QuantumGate):
         pos = np.array(gate.pos)

tests/quafu/algorithms/angle_test.py

@@ -0,0 +1,32 @@
+# (C) Copyright 2023 Beijing Academy of Quantum Information Sciences
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from quafu.circuits import QuantumCircuit
+import quafu.elements.element_gates as qeg
+from quafu.algorithms.embedding.angle import AngleEmbedding
+import numpy as np
+
+
+class TestAngleEmbedding:
+     """Example of angle embedding"""
+
+    def test_build(self):
+        num_qubits = 4
+        qc = QuantumCircuit(num_qubits)
+        feature = np.array([[6,-12.5,11.15,7],[8,9.5,-11,-5],[5,0.5,8,-7]])
+        for i in range(4):
+            qc.add_gate(qeg.HGate(pos=i))
+        for i in range(len(feature)):
+            qc.add_gates(AngleEmbedding(features=feature[i], num_qubits=num_qubits,rotation='Y'))
+        qc.draw_circuit(width=num_qubits)

tests/quafu/algorithms/basic_entangle_test.py

@@ -0,0 +1,43 @@
+# (C) Copyright 2023 Beijing Academy of Quantum Information Sciences
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from quafu.circuits import QuantumCircuit
+import quafu.elements.element_gates as qeg
+from quafu.algorithms.layers.basic_entangle import BasicEntangleLayers
+import numpy as np
+
+class TestBasicEntangleLayers:
+    """Example of building basic_entangle layer"""
+    def test_build(self):
+        num_qubits = 3
+        qc = QuantumCircuit(num_qubits)
+        weights = np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]])
+        # weights = np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
+        # weights = np.array([[0.1, 0.2], [0.3, 0.4]])
+        qc.add_gates(BasicEntangleLayers(weights=weights, num_qubits=num_qubits,rotation='Y'))
+        qc.draw_circuit(width=num_qubits)
+
+        ##TODO(): if weights are as follows, it need additional processing.
+                # weights = np.array([
+        #     [
+        #         [1, 2, 3, 4],
+        #         [5, 6, 7, 8],
+        #         [9, 10, 11, 12]
+        #     ],
+        #     [
+        #         [13, 14, 15, 16],
+        #         [17, 18, 19, 20],
+        #         [21, 22, 23, 24]
+        #     ]
+        # ])