Adding examples with noisy model

docs/sphinx/examples/python/tutorials/noise_parameters.py

@@ -0,0 +1,89 @@
+import cudaq
+import numpy as np
+
+### Hidden qubit parameters
+T1 = 1000  # nanoseconds
+T2 = 200  # nanoseconds
+detuning_rate = np.pi / 250
+
+### Define Kraus Channels
+
+
+def error_prob(t, T12):
+    error = 1 - np.exp(-t / T12)  # nanoseconds
+    return error
+
+
+def t1_kraus(t, T1):
+
+    t1_decay = error_prob(t, T1)
+    kraus_0 = np.array([[1.0, 0.0], [0.0, np.sqrt(1 - t1_decay)]],
+                       dtype=np.complex128,
+                       order='F')
+    kraus_1 = np.array([[0.0, np.sqrt(t1_decay)], [0.0, 0.0]],
+                       dtype=np.complex128,
+                       order='F')
+    kraus_op = cudaq.KrausChannel([kraus_0, kraus_1])
+    return kraus_op
+
+
+def coherent_z_kraus(angle):
+    kraus_0 = np.array(
+        [[np.exp(-1j * angle / 2), 0.0], [0.0, np.exp(1j * angle / 2)]],
+        dtype="complex128",
+        order="F")
+    kraus_op = cudaq.KrausChannel([kraus_0])
+    return kraus_op
+
+
+def t2_kraus(t, T2):
+
+    t2_decay = error_prob(t, T2)
+    kraus_0 = np.array([[1.0, 0.0], [0.0, np.sqrt(1 - t2_decay)]],
+                       dtype=np.complex128,
+                       order='F')
+    kraus_1 = np.array([[0.0, 0.0], [0.0, np.sqrt(t2_decay)]],
+                       dtype=np.complex128,
+                       order='F')
+    kraus_op = cudaq.KrausChannel([kraus_0, kraus_1])
+    return kraus_op
+
+
+### Define Noise model and gates
+
+
+def hidden_noise_model(t):
+    #initialize the noise model
+    noise_model = cudaq.NoiseModel()
+
+    ##add noise to `r1` "delay"
+    noise_model.add_channel("r1", [0], t1_kraus(t, T1))
+    noise_model.add_channel("r1", [0], t2_kraus(t, T2))
+    noise_model.add_channel("r1", [0], coherent_z_kraus(t * detuning_rate))
+
+    ##add noise to `rx`
+    noise_model.add_channel("rx", [0], t1_kraus(t, T1))
+    noise_model.add_channel("rx", [0], t2_kraus(t, T2))
+    noise_model.add_channel("rx", [0], coherent_z_kraus(t * detuning_rate))
+
+    ##add noise to `rz`
+    noise_model.add_channel("rz", [0], t1_kraus(t, T1))
+    noise_model.add_channel("rz", [0], t2_kraus(t, T2))
+    noise_model.add_channel("rz", [0], coherent_z_kraus(t * detuning_rate))
+
+    return noise_model
+
+
+## define some custom gates
+
+
+def Id(self, time, qubit) -> None:
+    self.r1(0.0, qubit)
+
+
+def custom_rx(self, time, amp, qubit):
+    ##hidden frequency
+    f = 5.3012314  #GHz
+    amp_adjust = 0.1
+    angle = 2 * np.pi * time * amp * f * amp_adjust
+    self.rx(angle, qubit)

docs/sphinx/using/tutorials.rst

@@ -16,6 +16,7 @@ Tutorials that give an in depth view of CUDA-Q and its applications in Python.
     /examples/python/tutorials/hybrid_qnns.ipynb
     /examples/python/tutorials/maximum_vertex_weight_clique.ipynb
     /examples/python/tutorials/noisy_simulations.ipynb
+    /examples/python/tutorials/noisy_examples.ipynb
     /examples/python/tutorials/readout_error_mitigation.ipynb
     /examples/python/tutorials/vqe_water_active_space.ipynb
     /examples/python/tutorials/Divisive_clustering.ipynb