renamed function 'eval' to 'dense_vector_tn_qu'

src/qibotn/eval_qu.py

@@ -0,0 +1,49 @@
+import numpy as np
+import quimb.tensor as qtn
+from qibo.models import Circuit as QiboCircuit
+
+
+def from_qibo(circuit: QiboCircuit, is_mps: False, psi0=None, method='svd',
+              cutoff=1e-6, cutoff_mode='abs'):
+    nqubits = circuit.nqubits
+    gate_opt = {}
+    if is_mps:
+        tncirc = qtn.CircuitMPS(nqubits, psi0=psi0)
+        gate_opt["method"] = method
+        gate_opt["cutoff"] = cutoff
+        gate_opt["cutoff_mode"] = cutoff_mode
+    else:
+        tncirc = qtn.Circuit(nqubits, psi0=psi0)
+
+    for gate in circuit.queue:
+        tncirc.apply_gate(
+            gate.name,
+            *gate.parameters,
+            *gate.qubits,
+            parametrize=False if is_mps else (len(gate.parameters) > 0),
+            **gate_opt
+        )
+
+    return tncirc
+
+
+def init_state_tn(nqubits, init_state_sv):
+    dims = tuple(2 * np.ones(nqubits, dtype=int))
+
+    return qtn.tensor_1d.MatrixProductState.from_dense(init_state_sv, dims)
+
+
+def dense_vector_tn_qu(qasm: str, init_state, is_mps, backend="numpy"):
+    """Evaluate QASM with Quimb
+
+    backend (quimb): numpy, cupy, jax. Passed to ``opt_einsum``.
+
+    """
+    circuit = QiboCircuit.from_qasm(qasm)
+    if init_state is not None:
+        init_state = init_state_tn(circuit.nqubits, init_state)
+    circ_quimb = from_qibo(circuit, is_mps, psi0=init_state)
+    interim = circ_quimb.psi.full_simplify(seq="DRC")
+    amplitudes = interim.to_dense(backend=backend).flatten()
+
+    return amplitudes