naturally, a good way to start ... remember 80 % documentation and engineering and 20% coding
In the following sections you can learn more about the key features of PennyLane:
Quantum circuitsarrow-up-right shows how PennyLane unifies and simplifies the process of programming quantum circuits with trainable parameters.
Gradients and trainingarrow-up-right introduces how PennyLane is used with different optimization libraries to optimize quantum circuits or hybrid computations.
Quantum operationsarrow-up-right outlines the various quantum circuit building blocks provided in PennyLane.
Measurementsarrow-up-right presents the different options available to measure the output of quantum circuits.
Templatesarrow-up-right gives an overview of different larger-scale composable layers for building quantum algorithms.
Optimizersarrow-up-right details the built-in tools for optimizing and training quantum computing and quantum machine learning circuits.
Configurationarrow-up-right provides details about how to customize PennyLane and provide credentials for quantum hardware access.
qml.state : https://pennylane.readthedocs.io/en/stable/code/api/pennylane.state.htmlarrow-up-right
qml.kernels: https://pennylane.readthedocs.io/en/stable/code/qml_kernels.htmlarrow-up-right
Step 1: https://pennylane.readthedocs.io/en/stable/introduction/interfaces.htmlarrow-up-right
Step 2:https://pennylane.readthedocs.io/en/stable/introduction/interfaces.htmlarrow-up-right
For Variational circuits: https://pennylane.ai/qml/glossary/variational_circuit.htmlarrow-up-right
Last updated 4 years ago