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naturally, a good way to start ... remember 80 % documentation and engineering and 20% coding
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naturally, a good way to start ... remember 80 % documentation and engineering and 20% coding
Last updated
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In the following sections you can learn more about the key features of PennyLane:
Quantum circuits shows how PennyLane unifies and simplifies the process of programming quantum circuits with trainable parameters.
Gradients and training introduces how PennyLane is used with different optimization libraries to optimize quantum circuits or hybrid computations.
Quantum operations outlines the various quantum circuit building blocks provided in PennyLane.
Measurements presents the different options available to measure the output of quantum circuits.
Templates gives an overview of different larger-scale composable layers for building quantum algorithms.
Optimizers details the built-in tools for optimizing and training quantum computing and quantum machine learning circuits.
Configuration 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.html
qml.kernels: https://pennylane.readthedocs.io/en/stable/code/qml_kernels.html
Step 1: https://pennylane.readthedocs.io/en/stable/introduction/interfaces.html
Step 2:https://pennylane.readthedocs.io/en/stable/introduction/interfaces.html
For Variational circuits: https://pennylane.ai/qml/glossary/variational_circuit.html
