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Standard installation instruction visibility (#979)
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**Context:**
The standard (default, preferred) installation instructions in the
pennylane-lightning docs are easy to miss.
This could discourage users if they think they need to go through a more
involved installation process, ie. installing from source.

**Description of the Change:**
Added a heading for standard installation instructions.

**Benefits:**
Easier to notice the most simple/straightforward installation method for
lightning devices.

**Possible Drawbacks:**

**Related GitHub Issues:**

---------

Co-authored-by: Shuli Shu <08cnbj@gmail.com>
Co-authored-by: ringo-but-quantum <github-ringo-but-quantum@xanadu.ai>
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3 people authored Nov 20, 2024
1 parent 4c8d840 commit 9fc9633
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5 changes: 4 additions & 1 deletion .github/CHANGELOG.md
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### Documentation

* Update Lightning-Tensor installation docs and usage suggestions.
[(#979)](https://github.com/PennyLaneAI/pennylane-lightning/pull/979)

### Bug fixes

* Fix issue with adjoint-jacobian of adjoint ops.
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This release contains contributions from (in alphabetical order):

Ali Asadi, Joseph Lee, Luis Alfredo Nuñez Meneses, Andrija Paurevic, Shuli Shu, Raul Torres, Haochen Paul Wang
Ali Asadi, Joseph Lee, Anton Naim Ibrahim, Luis Alfredo Nuñez Meneses, Andrija Paurevic, Shuli Shu, Raul Torres, Haochen Paul Wang

---

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27 changes: 16 additions & 11 deletions README.rst
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Expand Up @@ -77,9 +77,10 @@ The following table summarizes the supported platforms and the primary installat
Lightning-Qubit installation
****************************

Lightning-Qubit comes pre-installed with PennyLane. Please follow our
`installation instructions <https://pennylane.ai/install/#high-performance-computing-and-gpus>`_
to install PennyLane.
Standard installation
=====================
| **Lightning-Qubit comes pre-installed with PennyLane.**
| Please follow our `installation instructions <https://pennylane.ai/install/#high-performance-computing-and-gpus>`_ to install PennyLane.
Install from source
===================
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Lightning-GPU installation
**************************

For the majority of cases, Lightning-GPU can be installed by following our installation instructions at `pennylane.ai/install <https://pennylane.ai/install/#high-performance-computing-and-gpus>`__.
Standard installation
=====================
| For the majority of cases,
| Lightning-GPU can be installed by following our installation instructions at `pennylane.ai/install <https://pennylane.ai/install/#high-performance-computing-and-gpus>`__.
Install Lightning-GPU from source
=================================
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Lightning-Kokkos installation
*****************************

On most Linux systems, Lightning-Kokkos can be installed via Spack or Docker by following our installation instructions at `pennylane.ai/install <https://pennylane.ai/install/#high-performance-computing-and-gpus>`__.
Standard installation
=====================
| On most Linux systems,
| Lightning-Kokkos can be installed via Spack or Docker by following our installation instructions at `pennylane.ai/install <https://pennylane.ai/install/#high-performance-computing-and-gpus>`__.
Install Lightning-Kokkos from source
====================================
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The SDK may be installed within the Python environment ``site-packages`` directory using ``pip`` or ``conda`` or the SDK library path appended to the ``LD_LIBRARY_PATH`` environment variable.
Please see the `cuQuantum SDK <https://developer.nvidia.com/cuquantum-sdk>`_ install guide for more information.

Lightning-Tensor and ``cutensornet-cu12`` can be installed via:

.. code-block:: bash
pip install cutensornet-cu12
pip install pennylane-lightning-tensor
Standard installation
=====================
| For the majority of cases,
| Lightning-Tensor can be installed by following our installation instructions at `pennylane.ai/install <https://pennylane.ai/install/#high-performance-computing-and-gpus>`__.
Install Lightning-Tensor from source
====================================
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2 changes: 1 addition & 1 deletion pennylane_lightning/core/_version.py
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Version number (major.minor.patch[-label])
"""

__version__ = "0.40.0-dev12"
__version__ = "0.40.0-dev13"

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