Reorganized Backends Docs Page

docs/sphinx/using/backends/backends.rst

@@ -1,41 +1,23 @@
+*************************
 CUDA-Q Backends
-**********************
+*************************
+The CUDA-Q platform has is a powerful tool with many different backends for running hybrid quatum applications and other simulations.  This page will help you understand what backends are availible and what the best choices are for your purpose. 
 
-.. toctree::
-   :caption: Backend Targets
-   :maxdepth: 1
+The figure below groups the backends into five categories, and described the general purpose for each.  See the following sections for a breakdown of the backends included in each section.
 
-      Simulation <simulators.rst>
-      Quantum Hardware <hardware.rst>
-      NVIDIA Quantum Cloud <nvqc.rst>
-      Multi-Processor Platforms <platform.rst>
+.. image:: backends.png
+   :width: 1000
 
-**The following is a comprehensive list of the available targets in CUDA-Q:**
+Click on the links below for each catagory to learn more about the backends it contains.  the list below also covers all of the backends availible in CUDA-Q.
 
-* :ref:`anyon <anyon-backend>`
-* :ref:`braket <braket-backend>`
-* :ref:`density-matrix-cpu <default-simulator>`
-* :ref:`fermioniq <fermioniq-backend>`
-* :ref:`infleqtion <infleqtion-backend>`
-* :ref:`ionq <ionq-backend>`
-* :ref:`iqm <iqm-backend>`
-* :ref:`nvidia <nvidia-backend>`
-* :ref:`nvidia-fp64 <nvidia-fp64-backend>`
-* :ref:`nvidia-mgpu <nvidia-mgpu-backend>`
-* :ref:`nvidia-mqpu <mqpu-platform>`
-* :ref:`nvidia-mqpu-fp64 <mqpu-platform>`
-* :doc:`nvqc <nvqc>`
-* :ref:`oqc <oqc-backend>`
-* :ref:`orca <orca-backend>`
-* :ref:`qpp-cpu <qpp-cpu-backend>`
-* :ref:`quantinuum <quantinuum-backend>`
-* :ref:`quera <quera-backend>`
-* :ref:`remote-mqpu <mqpu-platform>`
-* :ref:`stim <stim-backend>`
-* :ref:`tensornet <tensor-backends>`
-* :ref:`tensornet-mps <tensor-backends>`
+.. toctree::
+   :maxdepth: 3
+
+        Circuit Simulation <simulators.rst>
+        Quantum Hardware (QPUs) <hardware.rst>
 
-.. deprecated:: 0.8
-   The `nvidia-fp64`, `nvidia-mgpu`, `nvidia-mqpu`, and `nvidia-mqpu-fp64` targets can be
-   enabled as extensions of the unified `nvidia` target (see `nvidia` :ref:`target documentation <nvidia-backend>`).
-   These target names might be removed in a future release.
+.. toctree::
+   :maxdepth: 1
+
+        Dynamics (dynamics) <dynamics.rst>
+        NVIDIA Quantum Cloud (nvqc) <nvqc.rst>

docs/sphinx/using/backends/dynamics.rst

@@ -1,5 +1,5 @@
-CUDA-Q Dynamics 
-*********************************
+Dynamics Simulation (dynamics)
++++++++++++++++++++++++++++++++
 
 CUDA-Q enables the design, simulation and execution of quantum dynamics via 
 the ``evolve`` API. Specifically, this API allows us to solve the time evolution 
@@ -8,7 +8,7 @@ backend target, which is based on the cuQuantum library, optimized for performan
 on NVIDIA GPU.
 
 Quick Start
-+++++++++++
+^^^^^^^^^^^^
 
 In the example below, we demonstrate a simple time evolution simulation workflow comprising of the 
 following steps:
@@ -86,7 +86,7 @@ observable. Hence, we convert them into sequences for plotting purposes.
 
 
 Operator
-+++++++++++
+^^^^^^^^^^
 
 .. _operators:
 
@@ -157,7 +157,7 @@ The latter is specified by the dimension map that is provided to the `cudaq.evol
 
 
 Time-Dependent Dynamics
-++++++++++++++++++++++++
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 .. _time_dependent:
 
@@ -219,7 +219,7 @@ the desired value for each parameter:
         :end-before: [End Schedule2]
 
 Numerical Integrators
-++++++++++++++++++++++
+^^^^^^^^^^^^^^^^^^^^^^^^
 
 .. _integrators:
 
@@ -272,4 +272,4 @@ backend target.
     If the output is a '`None`' string, it indicates that your Torch installation does not support CUDA.
     In this case, you need to install a CUDA-enabled Torch package via other mechanisms, e.g., building Torch from source or
     using their Docker images.
-
+