Fix some doc typos (#721)

Merges #667 and
#693 but fixes that they edited
the generated docs instead of the source.

---------

Co-authored-by: Yotam Vaknin <tomirendo@gmail.com>
Co-authored-by: nickdgardner <36652026+nickdgardner@users.noreply.github.com>

Author: 3 people

dev/gen_stim_stub_file.py

@@ -18,7 +18,7 @@ def main():
         version = "v" + version
     print(f'''
 """Stim {version}: a fast quantum stabilizer circuit library."""
-# (This a stubs file describing the classes and methods in stim.)
+# (This is a stubs file describing the classes and methods in stim.)
 from __future__ import annotations
 from typing import overload, TYPE_CHECKING, List, Dict, Tuple, Any, Union, Iterable, Optional
 if TYPE_CHECKING:

doc/python_api_reference_vDev.md

@@ -1538,7 +1538,7 @@ def detector_error_model(
             error mechanisms). When set to true, the probabilities of the disjoint
             cases are instead assumed to be independent probabilities. For example,
             a `PAULI_CHANNEL_1(0.1, 0.2, 0.0)` becomes equivalent to an
-            `X_ERROR(0.1)` followed by a `Z_ERROR(0.2)`. This assumption is an
+            `X_ERROR(0.1)` followed by a `Y_ERROR(0.2)`. This assumption is an
             approximation, but it is a good approximation for small probabilities.
 
             This argument can also be set to a probability between 0 and 1, setting
@@ -2385,7 +2385,7 @@ def likeliest_error_sat_problem(
         wcnf = WCNF(from_string="p wcnf 1 2 3\n3 -1 0\n3 1 0\n")
 
         with RC2(wcnf) as rc2:
-        print(rc2.compute())  
+        print(rc2.compute())
         print(rc2.cost)
 
     Much faster solvers are available online. For example, you can download
@@ -2772,7 +2772,7 @@ def shortest_error_sat_problem(
         wcnf = WCNF(from_string="p wcnf 1 2 3\n3 -1 0\n3 1 0\n")
 
         with RC2(wcnf) as rc2:
-        print(rc2.compute())  
+        print(rc2.compute())
         print(rc2.cost)
 
     Much faster solvers are available online. For example, you can download

doc/stim.pyi

@@ -1,5 +1,5 @@
 """Stim (Development Version): a fast quantum stabilizer circuit library."""
-# (This a stubs file describing the classes and methods in stim.)
+# (This is a stubs file describing the classes and methods in stim.)
 from __future__ import annotations
 from typing import overload, TYPE_CHECKING, List, Dict, Tuple, Any, Union, Iterable, Optional
 if TYPE_CHECKING:
@@ -958,7 +958,7 @@ class Circuit:
                 error mechanisms). When set to true, the probabilities of the disjoint
                 cases are instead assumed to be independent probabilities. For example,
                 a `PAULI_CHANNEL_1(0.1, 0.2, 0.0)` becomes equivalent to an
-                `X_ERROR(0.1)` followed by a `Z_ERROR(0.2)`. This assumption is an
+                `X_ERROR(0.1)` followed by a `Y_ERROR(0.2)`. This assumption is an
                 approximation, but it is a good approximation for small probabilities.
 
                 This argument can also be set to a probability between 0 and 1, setting

glue/python/src/stim/__init__.pyi

@@ -1,5 +1,5 @@
 """Stim (Development Version): a fast quantum stabilizer circuit library."""
-# (This a stubs file describing the classes and methods in stim.)
+# (This is a stubs file describing the classes and methods in stim.)
 from __future__ import annotations
 from typing import overload, TYPE_CHECKING, List, Dict, Tuple, Any, Union, Iterable, Optional
 if TYPE_CHECKING:
@@ -958,7 +958,7 @@ class Circuit:
                 error mechanisms). When set to true, the probabilities of the disjoint
                 cases are instead assumed to be independent probabilities. For example,
                 a `PAULI_CHANNEL_1(0.1, 0.2, 0.0)` becomes equivalent to an
-                `X_ERROR(0.1)` followed by a `Z_ERROR(0.2)`. This assumption is an
+                `X_ERROR(0.1)` followed by a `Y_ERROR(0.2)`. This assumption is an
                 approximation, but it is a good approximation for small probabilities.
 
                 This argument can also be set to a probability between 0 and 1, setting

src/stim/circuit/circuit.pybind.cc

@@ -1704,7 +1704,7 @@ void stim_pybind::pybind_circuit_methods(pybind11::module &, pybind11::class_<Ci
                     error mechanisms). When set to true, the probabilities of the disjoint
                     cases are instead assumed to be independent probabilities. For example,
                     a `PAULI_CHANNEL_1(0.1, 0.2, 0.0)` becomes equivalent to an
-                    `X_ERROR(0.1)` followed by a `Z_ERROR(0.2)`. This assumption is an
+                    `X_ERROR(0.1)` followed by a `Y_ERROR(0.2)`. This assumption is an
                     approximation, but it is a good approximation for small probabilities.
 
                     This argument can also be set to a probability between 0 and 1, setting
@@ -2091,7 +2091,7 @@ void stim_pybind::pybind_circuit_methods(pybind11::module &, pybind11::class_<Ci
                 wcnf = WCNF(from_string="p wcnf 1 2 3\n3 -1 0\n3 1 0\n")
 
                 with RC2(wcnf) as rc2:
-                print(rc2.compute())  
+                print(rc2.compute())
                 print(rc2.cost)
 
             Much faster solvers are available online. For example, you can download
@@ -2166,7 +2166,7 @@ void stim_pybind::pybind_circuit_methods(pybind11::module &, pybind11::class_<Ci
                 wcnf = WCNF(from_string="p wcnf 1 2 3\n3 -1 0\n3 1 0\n")
 
                 with RC2(wcnf) as rc2:
-                print(rc2.compute())  
+                print(rc2.compute())
                 print(rc2.cost)
 
             Much faster solvers are available online. For example, you can download