[docs] Update the link to Python wheels

docs/sphinx/using/backends/simulators.rst

@@ -156,7 +156,7 @@ To execute a program on the multi-node multi-GPU NVIDIA target, use the followin
     .. note::
 
       If you installed CUDA-Q via :code:`pip`, you will need to install the necessary MPI dependencies separately;
-      please follow the instructions for installing dependencies in the `Project Description <https://pypi.org/project/cuda-quantum/#description>`__.
+      please follow the instructions for installing dependencies in the `Project Description <https://pypi.org/project/cudaq/#description>`__.
 
     In addition to using MPI in the simulator, you can use it in your application code by installing `mpi4py <https://mpi4py.readthedocs.io/>`__, and 
     invoking the program with the command

docs/sphinx/using/install/data_center_install.rst

@@ -356,7 +356,7 @@ copy the built `.whl` file to the host system, and install it using `pip`; e.g.
 .. TODO: update pypi links throughout the docs
 
 To install the necessary CUDA and MPI dependencies for some of the components, 
-you can either follow the instructions on `PyPI.org <https://pypi.org/project/cuda-quantum/>`__, 
+you can either follow the instructions on `PyPI.org <https://pypi.org/project/cudaq/>`__, 
 replacing `pip install cudaq` with the command above, or you can follow the
 instructions in the remaining sections of this document to customize and better
 optimize them for your host system.

docs/sphinx/using/install/local_installation.rst

@@ -183,8 +183,8 @@ please take a look at the section on :ref:`Development with VS Code <singularity
 Python wheels
 ++++++++++++++++++++++++++++++++++++
 
-CUDA-Q Python wheels are available on `PyPI.org <https://pypi.org/project/cuda-quantum>`__. 
-Installation instructions can be found in the `project description <https://pypi.org/project/cuda-quantum/#description>`__.
+CUDA-Q Python wheels are available on `PyPI.org <https://pypi.org/project/cudaq/>`__. 
+Installation instructions can be found in the `project description <https://pypi.org/project/cudaq/#description>`__.
 For more information about available versions and documentation,
 see :doc:`../../releases`.
 
@@ -218,7 +218,7 @@ Pre-built binaries
 Starting with the 0.6.0 release, we provide pre-built binaries for using 
 CUDA-Q with C++. Support for using CUDA-Q with Python can be installed 
 side-by-side with the pre-built binaries for C++ by following the instructions on 
-`PyPI.org <https://pypi.org/project/cuda-quantum>`__.
+`PyPI.org <https://pypi.org/project/cudaq/>`__.
 The pre-built binaries work across a range of Linux operating systems listed 
 under :ref:`dependencies-and-compatibility`. 
 
@@ -659,7 +659,7 @@ certain CUDA libraries separately to take advantage of these.
 Installation via PyPI
 ++++++++++++++++++++++++++++++++++++
 
-If you installed CUDA-Q via `PyPI <https://pypi.org/project/cuda-quantum>`__, please follow the installation instructions there to install the necessary CUDA dependencies.
+If you installed CUDA-Q via `PyPI <https://pypi.org/project/cudaq/>`__, please follow the installation instructions there to install the necessary CUDA dependencies.
 
 Installation In Container Images
 ++++++++++++++++++++++++++++++++++++

docs/sphinx/using/quick_start.rst

@@ -20,7 +20,7 @@ Install CUDA-Q
 .. tab:: Python
 
    To develop CUDA-Q applications using Python, 
-   please follow the instructions for `installing CUDA-Q <https://pypi.org/project/cuda-quantum/>`_ from PyPI. 
+   please follow the instructions for `installing CUDA-Q <https://pypi.org/project/cudaq/>`_ from PyPI. 
    If you have an NVIDIA GPU, make sure to also follow the instructions for enabling GPU-acceleration.
 
    .. include:: ../../../python/README.md