error docs

Author: yutuer21

docs/source/quickstart.rst

@@ -470,7 +470,7 @@ For the Monte Carlo trajectory noise simulator, the unitary Kraus channel can be
     nmc = 10000
     random = K.implicit_randu(nmc)
     valuemc = K.mean(K.numpy(noisec_vmap(random)))
-    (0.931+0j)
+    # (0.931+0j)
 
 
 **Density Matrix Simulator:**
@@ -491,7 +491,7 @@ Density matrix simulator ``tc.DMCircuit`` simulates the noise in a full form, bu
     K = tc.set_backend("tensorflow")
     noisec_jit = K.jit(noisecircuitdm)
     valuedm = noisec_jit()
-    (0.931+0j)
+    # (0.931+0j)
 
 
 **Experiment with quantum errors:**
@@ -521,7 +521,7 @@ Readout error can be added in experiments for sampling and expectation value cal
     c = tc.Circuit(3)
     c.X(0)
     readout_error = []
-    readout_error.append([0.9, 0.75])  # readout error of qubit 0
+    readout_error.append([0.9, 0.75])  # readout error of qubit 0   p0|0=0.9, p1|1=0.75
     readout_error.append([0.4, 0.7])  # readout error of qubit 1
     readout_error.append([0.7, 0.9])  # readout error of qubit 2
     value = c.sample_expectation_ps(z=[0, 1, 2], readout_error=readout_error)
@@ -531,13 +531,12 @@ Readout error can be added in experiments for sampling and expectation value cal
         allow_state=True,
         readout_error=readout_error,
         random_generator=tc.backend.get_random_state(42),
+        format_="sample_bin"
     )
-    #[(<tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 0, 0], dtype=int32)>,
-    # <tf.Tensor: shape=(), dtype=float32, numpy=0.21000001>),
-    #(<tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 0, 0], dtype=int32)>,
-    # <tf.Tensor: shape=(), dtype=float32, numpy=0.21000001>),
-    #(<tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 0, 1], dtype=int32)>,
-    # <tf.Tensor: shape=(), dtype=float32, numpy=0.09>)]
+    # tf.Tensor(
+    # [[1 0 0]
+    # [1 0 0]
+    # [1 0 1]], shape=(3, 3), dtype=int32)
 
 
 MPS and MPO

examples/noise.py

@@ -75,7 +75,8 @@ def mitigate_readout(nqubit, circ, readout_error):
         for s in bs:
             calmatrix[int(s, 2)][i] = bs[s] / shots
 
-    key = K.get_random_state(42)
+    key, subkey = tc.backend.random_split(key)
+    key = subkey
     bs = circ.sample(
         batch=shots, allow_state=True, format_="count_dict_bin", random_generator=key
     )
@@ -226,66 +227,3 @@ def example_T2_cali():
     example_readout_mitigate()
     example_T1_cali()
     example_T2_cali()
-
-
-c = tc.Circuit(3)
-c.X(0)
-readout_error = []
-readout_error.append([0.9, 0.75])  # readout error of qubit 0
-readout_error.append([0.4, 0.7])  # readout error of qubit 1
-readout_error.append([0.7, 0.9])  # readout error of qubit 2
-value = c.sample_expectation_ps(z=[0, 1, 2], readout_error=readout_error)
-instance = c.sample(allow_state=True, readout_error=readout_error)
-instances = c.sample(
-    batch=3,
-    allow_state=True,
-    readout_error=readout_error,
-    random_generator=tc.backend.get_random_state(42),
-)
-
-c = tc.Circuit(1)
-c.x(0)
-c.thermalrelaxation(
-    0, t1=300, t2=400, time=1000, method="ByChoi", excitedstatepopulation=0
-)
-c.generaldepolarizing(0, p=0.01, num_qubits=1)
-c.phasedamping(0, gamma=0.2)
-c.amplitudedamping(0, gamma=0.25, p=0.2)
-c.reset(0)
-c.expectation_ps(z=[0])
-
-
-def noisecircuit(random):
-    c = tc.Circuit(1)
-    c.x(0)
-    c.thermalrelaxation(
-        0,
-        t1=300,
-        t2=400,
-        time=1000,
-        method="ByChoi",
-        excitedstatepopulation=0,
-        status=random,
-    )
-    return c.expectation_ps(z=[0])
-
-
-K = tc.set_backend("tensorflow")
-noisec_vmap = K.jit(K.vmap(noisecircuit, vectorized_argnums=0))
-nmc = 10000
-random = K.implicit_randu(nmc)
-valuemc = K.mean(K.numpy(noisec_vmap(random)))
-
-
-def noisecircuitdm():
-    dmc = tc.DMCircuit(1)
-    dmc.x(0)
-    dmc.thermalrelaxation(
-        0, t1=300, t2=400, time=1000, method="ByChoi", excitedstatepopulation=0
-    )
-    return dmc.expectation_ps(z=[0])
-
-
-K = tc.set_backend("tensorflow")
-noisec_jit = K.jit(noisecircuitdm)
-valuedm = noisec_jit()

examples/noise_calibration.py

@@ -2,7 +2,7 @@
 python_version = 3.8
 ignore_missing_imports = True
 strict = True
-warn_unused_ignores = True
+warn_unused_ignores = False
 disallow_untyped_calls = False
 local_partial_types = False
 implicit_reexport = True
@@ -12,6 +12,7 @@ implicit_reexport = True
 ;;only module level * works...
 ignore_errors = True
 
+
 [mypy-cirq.*]
 ignore_errors = True
 

mypy.ini

@@ -352,7 +352,7 @@ def color_svg(circuit: cirq.Circuit, *coords: Tuple[int, int]) -> Any:
     from cirq.contrib.svg import SVGCircuit
 
     svg_str = SVGCircuit(circuit)._repr_svg_()
-    DOMTree = xml.dom.minidom.parseString(svg_str)
+    DOMTree = xml.dom.minidom.parseString(svg_str)  # type: ignore
     xpos = []
     ypos = []
     for r in DOMTree.getElementsByTagName("rect"):  # [0].setAttribute("fill", "gray")

tensorcircuit/applications/utils.py

@@ -323,7 +323,8 @@ def mitigate_readout(nqubit, circ, readout_error):
         for s in bs:
             calmatrix[int(s, 2)][i] = bs[s] / shots
 
-    key = tc.backend.get_random_state(42)
+    key, subkey = tc.backend.random_split(key)
+    key = subkey
     bs = circ.sample(
         batch=shots, allow_state=True, format_="count_dict_bin", random_generator=key
     )
@@ -360,7 +361,7 @@ def test_readout_mitigate(backend):
     c.X(2)
 
     readout_error = []
-    readout_error.append([0.9, 0.75])  # readout error of qubit 0
+    readout_error.append([0.9, 0.75])  # readout error of qubit 0, p0|0=0.9, p1|1=0.75
     readout_error.append([0.4, 0.7])  # readout error of qubit 1
     readout_error.append([0.7, 0.9])  # readout error of qubit 2