refactor: added function for converting qibo circuit to quimb circuit directly. modified expectation making use of it. added new test script.

examples/quimb_intro/test.py

@@ -0,0 +1,50 @@
+import numpy as np
+import jax
+from qibo.backends import construct_backend
+from qibo import Circuit, gates, hamiltonians
+from qibo.symbols import Z, X, Y
+
+# construct qibotn backend
+quimb_backend = construct_backend(backend="qibotn", platform="quimb")
+
+quimb_backend.setup_backend_specifics(
+    qimb_backend="jax", 
+    optimizer='auto-hq'
+    )
+
+quimb_backend.configure_tn_simulation(
+    max_bond_dimension=10
+)
+
+
+# define Hamiltonian
+form = 0.5 * Z(0) * Z(1) +- 1.5 *  X(0) * Z(2) + Z(3)
+hamiltonian = hamiltonians.SymbolicHamiltonian(form)
+
+
+# define circuit
+def build_circuit(nqubits, nlayers):
+    """Construct a Qibo parametric quantum circuit."""
+    circ = Circuit(nqubits)
+    for _ in range(nlayers):
+        for q in range(nqubits):
+            circ.add(gates.RY(q=q, theta=0.))
+            circ.add(gates.RZ(q=q, theta=0.))
+        [circ.add(gates.CNOT(q%nqubits, (q+1)%nqubits) for q in range(nqubits))]
+    circ.add(gates.M(*range(nqubits)))
+    return circ
+
+nqubits = 4
+circuit = build_circuit(nqubits=nqubits, nlayers=3)
+
+
+def f(params):
+    circuit.set_parameters(params)
+    return quimb_backend.expectation(
+        circuit=circuit,
+        observable=hamiltonian,
+    )
+
+parameters = np.random.uniform(-np.pi, np.pi, size=len(circuit.get_parameters()))
+print(f(parameters))
+print(jax.value_and_grad(f)(parameters))