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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
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In the following sections you can learn more about the key features of PennyLane:
shows how PennyLane unifies and simplifies the process of programming quantum circuits with trainable parameters.
introduces how PennyLane is used with different optimization libraries to optimize quantum circuits or hybrid computations.
outlines the various quantum circuit building blocks provided in PennyLane.
presents the different options available to measure the output of quantum circuits.
gives an overview of different larger-scale composable layers for building quantum algorithms.
details the built-in tools for optimizing and training quantum computing and quantum machine learning circuits.
provides details about how to customize PennyLane and provide credentials for quantum hardware access.
qml.state :
qml.kernels:
Step 1:
Step 2:
For Variational circuits:
