更新脚本

baseline_mps_expectation.py

@@ -70,6 +70,8 @@ def main():
     parser.add_argument("--exact", action="store_true")
     parser.add_argument("--exact-max-qubits", type=int, default=24)
     parser.add_argument("--preprocess", action="store_true")
+    parser.add_argument("--compile-circuit", action="store_true")
+    parser.add_argument("--track-memory", action="store_true")
     args = parser.parse_args()
     logging.getLogger("qibo.config").setLevel(logging.ERROR)
     logging.getLogger("qtealeaves").setLevel(logging.ERROR)
@@ -105,10 +107,17 @@ def main():
             cut_ratio=args.cut_ratio,
             svd_control=args.svd_control,
             tensor_module=args.tensor_module,
+            compile_circuit=args.compile_circuit,
+            track_memory=args.track_memory,
         )
         start = time.perf_counter()
         value = float(
-            backend.expectation(circuit, observable, preprocess=args.preprocess).real
+            backend.expectation(
+                circuit,
+                observable,
+                preprocess=args.preprocess,
+                compile_circuit=args.compile_circuit,
+            ).real
         )
         elapsed = time.perf_counter() - start
         abs_error = float("nan") if exact is None else abs(value - exact)

src/qibotn/backends/qmatchatea.py

@@ -40,6 +40,9 @@ class QMatchaTeaBackend(QibotnBackend, NumpyBackend):
         svd_control: str = "A",
         ini_bond_dimension: int = 1,
         tensor_module: str = "numpy",
+        compile_circuit: bool = False,
+        cache_gate_tensors: bool = True,
+        track_memory: bool = False,
     ):
         """Configure TN simulation given Quantum Matcha Tea interface.
 
@@ -78,6 +81,9 @@ class QMatchaTeaBackend(QibotnBackend, NumpyBackend):
         )
         self.ansatz = ansatz
         self.tensor_module = tensor_module
+        self.compile_circuit = compile_circuit
+        self.cache_gate_tensors = cache_gate_tensors
+        self.track_memory = track_memory
         if hasattr(self, "qmatchatea_backend"):
             self._setup_backend_specifics()
 
@@ -100,6 +106,8 @@ class QMatchaTeaBackend(QibotnBackend, NumpyBackend):
             ansatz=self.ansatz,
             tensor_module=self.tensor_module,
         )
+        self.qmatchatea_backend.cache_gate_tensors = self.cache_gate_tensors
+        self.qmatchatea_backend.track_memory = self.track_memory
 
     def execute_circuit(
         self,
@@ -199,7 +207,7 @@ class QMatchaTeaBackend(QibotnBackend, NumpyBackend):
             statevector=statevector,
         )
 
-    def expectation(self, circuit, observable, preprocess=True):
+    def expectation(self, circuit, observable, preprocess=True, compile_circuit=None):
         """Compute the expectation value of a Qibo-friendly ``observable`` on
         the Tensor Network constructed from a Qibo ``circuit``.
 
@@ -225,7 +233,11 @@ class QMatchaTeaBackend(QibotnBackend, NumpyBackend):
         observable = check_observable(observable, circuit.nqubits)
 
         # From Qibo to Qiskit
-        circuit = self._qibocirc_to_qiskitcirc(circuit, preprocess=preprocess)
+        circuit = self._qibocirc_to_qiskitcirc(
+            circuit,
+            preprocess=preprocess,
+            compile_circuit=compile_circuit,
+        )
         run_qk_params = qmatchatea.preprocessing.qk_transpilation_params(False)
 
         operators = qmatchatea.QCOperators()
@@ -245,21 +257,28 @@ class QMatchaTeaBackend(QibotnBackend, NumpyBackend):
         return np.real(results.observables["custom_hamiltonian"])
 
     def _qibocirc_to_qiskitcirc(
-        self, qibo_circuit, preprocess=True
+        self, qibo_circuit, preprocess=True, compile_circuit=None
     ) -> qiskit.QuantumCircuit:
         """Convert a Qibo Circuit into a Qiskit Circuit."""
         # Convert the circuit to QASM 2.0 to qiskit
         qasm_circuit = qibo_circuit.to_qasm()
         qiskit_circuit = qiskit.QuantumCircuit.from_qasm_str(qasm_circuit)
 
+        if compile_circuit is None:
+            compile_circuit = self.compile_circuit
+
         if not preprocess:
+            if compile_circuit:
+                qiskit_circuit = qmatchatea.tensor_compiler(qiskit_circuit)
             return qiskit_circuit
 
         # Transpile the circuit to adapt it to the linear structure of the MPS,
         # with the constraint of having only the gates basis_gates
         qiskit_circuit = qmatchatea.preprocessing.preprocess(
             qiskit_circuit,
-            qk_params=qmatchatea.preprocessing.qk_transpilation_params(),
+            qk_params=qmatchatea.preprocessing.qk_transpilation_params(
+                tensor_compiler=compile_circuit
+            ),
         )
         return qiskit_circuit