Update docs and guard for tensor network decoder (#241)

Signed-off-by: Melody Ren <[email protected]>
Signed-off-by: melody-ren <[email protected]>
Co-authored-by: Ben Howe <[email protected]>

Author: melody-ren

docs/sphinx/api/qec/tensor_network_decoder_api.rst

@@ -6,7 +6,7 @@
 
     The decoder supports both single-syndrome and batch decoding, and can run on CPU or GPU (using cuTensorNet if available).
 
-    The Tensor Network Decoder is a Python-only implementation. C++ APIs are not available for this decoder.
+    The Tensor Network Decoder is a Python-only implementation and it requires Python 3.11 or higher. C++ APIs are not available for this decoder.
 
 
     .. note::

docs/sphinx/components/qec/introduction.rst

@@ -807,7 +807,7 @@ Usage:
 
 .. tab:: C++
 
-    The ``tensor_network_decoder`` is a Python-only implementation. C++ APIs are not available for this decoder.
+    The ``tensor_network_decoder`` is a Python-only implementation and it requires Python 3.11 or higher. C++ APIs are not available for this decoder.
 
 Output:
 

docs/sphinx/examples/qec/python/tensor_network_decoder.py

@@ -9,7 +9,9 @@
 # Check Python version
 # Remove this check once the pipeline advances to Python 3.11
 if sys.version_info < (3, 11):
-    print("Skipping tensor network decoder example")
+    print(
+        "Warning: The tensor network decoder requires Python 3.11 or higher. Exiting..."
+    )
     sys.exit(0)
 
 # [Begin Documentation]
@@ -31,6 +33,13 @@
 import cudaq_qec as qec
 import numpy as np
 
+import platform
+if platform.machine().lower() in ("arm64", "aarch64"):
+    print(
+        "Warning: stim is not supported on manylinux ARM64/aarch64. Skipping this example..."
+    )
+    sys.exit(0)
+
 import stim
 
 from beliefmatching.belief_matching import detector_error_model_to_check_matrices

docs/sphinx/examples_rst/qec/decoders.rst

@@ -90,7 +90,7 @@ check matrices (PCMs) and test syndromes to exercise a decoder.
 
 .. [#f1] [BCGMRY] Sergey Bravyi, Andrew Cross, Jay Gambetta, Dmitri Maslov, Patrick Rall, Theodore Yoder, High-threshold and low-overhead fault-tolerant quantum memory https://arxiv.org/abs/2308.07915
 
-Exact Maximum Likelihood Decoding with NVIDIA Tensor Networks Decoder
+Exact Maximum Likelihood Decoding with NVIDIA Tensor Network Decoder
 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 
 
@@ -99,7 +99,7 @@ CUDA-Q QEC library. The library follows the CUDA-Q decoder Python interface, nam
 At this time, we only support the Python interface for the decoder, which is
 available at :class:`cudaq_qec.plugins.decoders.tensor_network_decoder.TensorNetworkDecoder`.
 As documented in the API sections :ref:`tensor_network_decoder_api_python`, there are many configuration options
-that can be passed to the constructor.
+that can be passed to the constructor. The decoder requires Python 3.11 or higher.
 
 In the following example, we show how to use the `TensorNetworkDecoder` class from the `cudaq_qec` library to decode a circuit-level noise problem derived from a Stim surface code circuit.