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updating docs
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scarrazza committed Mar 1, 2024
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2 changes: 2 additions & 0 deletions doc/source/api-reference/qibo.rst
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Expand Up @@ -2366,6 +2366,8 @@ variable.
:members:
:member-order: bysource

.. _Clifford:

Clifford Simulation
^^^^^^^^^^^^^^^^^^^

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4 changes: 2 additions & 2 deletions doc/source/getting-started/backends.rst
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Expand Up @@ -34,12 +34,12 @@ Simulation backends
We provide multiple simulation backends for Qibo, which are automatically loaded
if the corresponding packages are installed, following the hierarchy below:

* :ref:`installing-numpy`: a lightweight quantum simulator shipped with the :ref:`installing-qibo` base package. Use this simulator if your CPU architecture is not supported by the other backends. Please note that the simulation performance is quite poor in comparison to other backends.
* :ref:`installing-qibojit`: an efficient simulation backend for CPU, GPU and multi-GPU based on just-in-time (JIT) compiled custom operators. Install this package if you need to simulate quantum circuits with large number of qubits or complex quantum algorithms which may benefit from computing parallelism.
* `qibotn <https://qibo.science/qibotn/stable/>`_: an interface to Tensor Networks simulation algorithms designed for GPUs and multi-node CPUs. This backend makes possible scaling quantum circuit simulation to a larger number of qubits.
* :ref:`installing-numpy`: a lightweight quantum simulator shipped with the :ref:`installing-qibo` base package. Use this simulator if your CPU architecture is not supported by the other backends. Please note that the simulation performance is quite poor in comparison to other backends.
* :ref:`installing-tensorflow`: a pure TensorFlow implementation for quantum simulation which provides access to gradient descent optimization and the possibility to implement classical and quantum architectures together. This backend is not optimized for memory and speed, use :ref:`installing-qibojit` instead.
* :ref:`installing-pytorch`: a pure PyTorch implementation for quantum simulation which provides access to gradient descent optimization and the possibility to implement classical and quantum architectures together. This backend is not optimized for memory and speed, use :ref:`installing-qibojit` instead.

* :ref:`clifford <Clifford>`: a specialized backend for the simulation of quantum circuits with Clifford gates. This backend uses :ref:`installing-qibojit` and/or :ref:`installing-numpy`.

The default backend that is used is the first available from the above list.
The user can switch to a different using the ``qibo.set_backend`` method
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