Qiskit · ElePT · Mar 13, 2025 · Mar 5, 2025 · Mar 11, 2025 · Mar 11, 2025
diff --git a/test/terra/primitives/test_estimator.py b/test/terra/primitives/test_estimator.py
@@ -322,7 +322,7 @@ def test_result_order(self):
         qc2.ry(np.pi / 2 * param, 0)
         qc2.measure_all()
 
-        estimator = Estimator(approximation=True)
+        estimator = Estimator(approximation=True, skip_transpilation=True)
         When combined with the approximation option, we get the expectation values as follows: 
         * shots is None and approximation=False: Return an expectation value with sampling-noise w/ 
           warning. 
         * shots is int and approximation=False: Return an expectation value with sampling-noise. 
         * shots is None and approximation=True: Return an exact expectation value. 
         * shots is int and approximation=True: Return expectation value with sampling-noise using a 
           normal distribution approximation. 
         When combined with the approximation option, we get the expectation values as follows: 
  
         * shots is None and approximation=False: Return an expectation value with sampling-noise w/ 
           warning. 
         * shots is int and approximation=False: Return an expectation value with sampling-noise. 
         * shots is None and approximation=True: Return an exact expectation value. 
         * shots is int and approximation=True: Return expectation value with sampling-noise using a 
           normal distribution approximation. 
         job = estimator.run([qc1, qc2, qc1, qc1, qc2], ["Z"] * 5, [[], [1], [], [], [1]])
         result = job.result()
         np.testing.assert_allclose(result.values, [1, 0, 1, 1, 0], atol=1e-10)