[minor] added example with tq-direct cuquantum integration

examples/cuquantum/tq_cuquantum_integration_example.py

@@ -0,0 +1,94 @@
+"""
+i
+MIT License
+
+Copyright (c) 2020-present TorchQuantum Authors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+
+from cuquantum import contract
+from cuquantum import CircuitToEinsum
+import torchquantum as tq
+from torchquantum.measurement import expval_joint_analytical
+import cupy as cp
+
+def expval_joint_analytical_cuquantum(qdev, observable):
+    """Computes the expectation value of a joint observable using cuquantum.
+
+    Args:
+        qdev (QuantumDevice): Quantum device to compute the expectation value on.
+        observable (str): Joint observable to compute the expectation value of.
+
+    Returns:
+        float: The expectation value of the joint observable.
+    """
+    op_history = qdev.op_history
+    myconverter = CircuitToEinsum(qdev, dtype='complex128', backend=cp)
+    expression, operands = myconverter.expectation(observable, lightcone=True)
+    expec = contract(expression, *operands)
+    return expec
+
+
+if __name__ == '__main__':
+
+    ops = [
+        {'name': 'u3', 'wires': 0, 'trainable': True},
+        {'name': 'u3', 'wires': 1, 'trainable': True},
+        {'name': 'cx', 'wires': [0, 1]},
+        {'name': 'cx', 'wires': [1, 0]},
+        {'name': 'u3', 'wires': 0, 'trainable': True},
+        {'name': 'u3', 'wires': 1, 'trainable': True},
+        {'name': 'cx', 'wires': [0, 1]},
+        {'name': 'cx', 'wires': [1, 0]},
+    ]
+
+    qmodule = tq.QuantumModule.from_op_history(ops)
+
+    qdev = tq.QuantumDevice(n_wires=2, bsz=1, record_op=True)
+
+    qmodule(qdev)
+
+    op_history = qdev.op_history
+
+    print(qdev.op_history)
+
+    myconverter = CircuitToEinsum(qdev, dtype='complex128', backend=cp)
+    pauli_string = 'IX'
+    expression, operands = myconverter.expectation(pauli_string, lightcone=True)
+    expec = contract(expression, *operands)
+    print(f'expectation value for {pauli_string}: {expec}')
+
+    print(f"torchquantum expval: {expval_joint_analytical(qdev, pauli_string)}")
+    print(expval_joint_analytical_cuquantum(qdev, pauli_string))
+
+
+    # # expectation value from reduced density matrix
+    # qubits = myconverter.qubits
+    # where = qubits[1:5]
+    # rdm_expression, rdm_operands = myconverter.reduced_density_matrix(where, lightcone=True)
+    # rdm = contract(rdm_expression, *rdm_operands)
+
+    # pauli_x = cp.asarray([[0,1],[1,0]], dtype=myconverter.dtype)
+    # pauli_z = cp.asarray([[1,0],[0,-1]], dtype=myconverter.dtype)
+    # expec_from_rdm = cp.einsum('abcdABCD,aA,bB,cC,dD->', rdm, pauli_x, pauli_x, pauli_z, pauli_z)
+
+
+    # print(f"is expectation value in agreement?", cp.allclose(expec, expec_from_rdm))
+