NVIDIA · melody-ren · Aug 17, 2026 · Jul 31, 2026 · Jul 31, 2026 · Jul 31, 2026
diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
@@ -94,6 +94,7 @@ jobs:
         uses: actions/checkout@v4
         with:
           set-safe-directory: true
+          lfs: true
 
       # ========================================================================
       # CUDA Quantum build

diff --git a/docs/sphinx/_static/cudaq_override.css b/docs/sphinx/_static/cudaq_override.css
@@ -25,3 +25,9 @@ max-width: 1240px !important;
 code.code span.pre, code.cpp span.pre, code.docutils span.pre{
     color: darkgreen;
 }
+
+/* Render the general index in a single column instead of the theme's multi-column layout */
+table.genindextable td {
+    display: block;
+    width: 100% !important;
+}
diff --git a/docs/sphinx/api/qec/chromobius_api.rst b/docs/sphinx/api/qec/chromobius_api.rst
@@ -1,7 +1,7 @@
 .. class:: chromobius
 
     A decoder for color codes built on the open-source
-    `Chromobius <https://github.com/quantumlib/chromobius>`_ Mobius decoder.
+    `Chromobius <https://github.com/quantumlib/chromobius>`_ Möbius decoder.
     Unlike the matrix-based decoders, Chromobius is *detector-error-model native*:
     it is constructed directly from Stim detector-error-model (DEM) text and
     predicts logical observable flips directly.

diff --git a/docs/sphinx/api/qec/cpp_api.rst b/docs/sphinx/api/qec/cpp_api.rst
@@ -116,8 +116,10 @@ Chromobius Decoder
 
 .. include:: chromobius_api.rst
 
-Real-Time Decoding
-==================
+.. _cpp_realtime_decoding_api:
+
+Realtime Decoding
+=================
 
 .. include:: cpp_realtime_decoding_api.rst
 

diff --git a/docs/sphinx/api/qec/cpp_realtime_decoding_api.rst b/docs/sphinx/api/qec/cpp_realtime_decoding_api.rst
@@ -1,7 +1,4 @@
-.. _cpp_realtime_decoding_api:
-
-
-The Real-Time Decoding API enables low-latency error correction on quantum hardware by allowing CUDA-Q quantum kernels to interact with decoders during circuit execution. This API is designed for use cases where corrections must be calculated and applied within qubit coherence times.
+The Realtime Decoding API enables low-latency error correction on quantum hardware by allowing CUDA-Q quantum kernels to interact with decoders during circuit execution. This API is designed for use cases where corrections must be calculated and applied within qubit coherence times.
 
 The real-time decoding system supports simulation environments for local testing and hardware integration (e.g., on
 `Quantinuum's Helios QPU
@@ -47,7 +44,7 @@ The configuration API enables setting up decoders before circuit execution. Deco
 Helper Functions
 ----------------
 
-Real-time decoding requires converting matrices to sparse format for efficient decoder configuration. The following utility functions are essential:
+Realtime decoding requires converting matrices to sparse format for efficient decoder configuration. The following utility functions are essential:
 
 - :cpp:func:`cudaq::qec::pcm_to_sparse_vec` for converting a dense PCM to a sparse PCM.
 - :cpp:func:`cudaq::qec::pcm_from_sparse_vec` for converting a sparse PCM to a dense PCM.

diff --git a/docs/sphinx/api/qec/python_api.rst b/docs/sphinx/api/qec/python_api.rst
@@ -77,6 +77,23 @@ Decoder Interfaces
 
 .. autofunction:: cudaq_qec.get_decoder
 
+.. note::
+   **scipy.sparse interop** — :func:`cudaq_qec.get_decoder` and
+   :class:`cudaq_qec.Decoder` accept a ``scipy.sparse`` matrix (CSR, CSC,
+   COO, or any other ``scipy.sparse`` format) as the parity-check matrix
+   ``H``.  This is the preferred form for large PCMs because no dense
+   ``rows x cols`` allocation is made — the matrix is normalised to CSR
+   internally.  Dense NumPy ``uint8`` arrays remain supported.
+   The PCM utilities :func:`cudaq_qec.reorder_pcm_columns`,
+   :func:`cudaq_qec.shuffle_pcm_columns`, and
+   :func:`cudaq_qec.pcm_to_sparse_vec` also accept SciPy sparse matrices
+   without creating a dense ``cudaqx::tensor``. Reordering and shuffling a
+   sparse input returns a ``scipy.sparse.csc_matrix``; a dense input continues
+   to return a NumPy array.
+
+   ``scipy`` is an optional dependency; if it is not installed, pass a dense
+   NumPy array instead.
+
 Built-in Decoders
 =================
 
@@ -120,8 +137,10 @@ Chromobius Decoder
 
 .. include:: chromobius_api.rst
 
-Real-Time Decoding
-==================
+.. _python_realtime_decoding_api:
+
+Realtime Decoding
+=================
 
 .. include:: python_realtime_decoding_api.rst
 
@@ -133,6 +152,23 @@ Common
 .. autofunction:: cudaq_qec.x_sample_memory_circuit
 .. autofunction:: cudaq_qec.z_sample_memory_circuit
 
+.. _syndrome_measurement_layout:
+
+.. note::
+   **Syndrome measurement layout** — ``sample_memory_circuit`` returns a tuple
+   ``(syndromes, data)``. The ``syndromes`` tensor has shape
+   ``(num_shots, num_detectors)`` with columns laid out as ``[ B  S  S  …  S  B ]``:
+
+   - ``B`` (boundary block) = ``code.get_num_z_stabilizers()`` for Z-basis
+     preparations (``prep0``/``prep1``), or ``code.get_num_x_stabilizers()`` for
+     X-basis preparations (``prepp``/``prepm``).
+   - ``S`` (inter-round block) = ``num_z_stabilizers + num_x_stabilizers``
+     detectors per round transition (``num_rounds - 1`` blocks total).
+   - Total: ``num_detectors = 2*B + (num_rounds - 1)*S``.
+
+   The ``data`` tensor has shape ``(num_shots, block_size)`` and holds the final
+   data-qubit measurements used to verify logical-state preservation.
+
 .. autofunction:: cudaq_qec.sample_code_capacity
 
 .. _dem_sampling_python_api:

diff --git a/docs/sphinx/api/qec/python_realtime_decoding_api.rst b/docs/sphinx/api/qec/python_realtime_decoding_api.rst
@@ -1,7 +1,4 @@
-.. _python_realtime_decoding_api:
-
-
-The Real-Time Decoding API enables low-latency error correction on quantum hardware by allowing CUDA-Q quantum kernels to interact with decoders during circuit execution. This API is designed for use cases where corrections must be calculated and applied within qubit coherence times.
+The Realtime Decoding API enables low-latency error correction on quantum hardware by allowing CUDA-Q quantum kernels to interact with decoders during circuit execution. This API is designed for use cases where corrections must be calculated and applied within qubit coherence times.
 
 The real-time decoding system supports simulation environments for local testing and hardware integration (e.g., on
 `Quantinuum's Helios QPU
@@ -180,7 +177,7 @@ Configuration Functions
 Helper Functions
 ----------------
 
-Real-time decoding requires converting matrices to sparse format for efficient decoder configuration. The following utility functions are essential:
+Realtime decoding requires converting matrices to sparse format for efficient decoder configuration. The following utility functions are essential:
 
 .. py:function:: cudaq_qec.pcm_to_sparse_vec(pcm)
 

diff --git a/docs/sphinx/api/qec/tensor_network_decoder_api.rst b/docs/sphinx/api/qec/tensor_network_decoder_api.rst
@@ -13,11 +13,10 @@
     decoder. Use `pip install cudaq-qec[tensor-network-decoder]` in order to use
     this decoder.
 
-    The Tensor Network Decoder has the same GPU support as the `Quantum Low-Density Parity-Check Decoder <https://nvidia.github.io/cudaqx/components/qec/introduction.html#quantum-low-density-parity-check-decoder>`__.
+    The Tensor Network Decoder has the same GPU support as the :ref:`Quantum Low-Density Parity-Check Decoder <qldpc_decoder>`.
     However, if you are using the V100 GPU (SM70), you will need to pin your
     cuTensor version to 2.2 by running `pip install cutensor_cu12==2.2`. Note
-    that this GPU will not be supported by the Tensor Network Decoder when
-    CUDA-Q 0.5.0 is released.
+    that this GPU is not supported by the Tensor Network Decoder.
 
     .. note::
       It is recommended to create decoders using the `cudaq_qec` plugin API: