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### 🚀 The feature, motivation and pitch
As I begin working with PyTorch to simulate and optimize quantum systems, I propose to open this issue to list features that would be helpful.
Note that the…
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# Description
lambeq provides a large number of models and trainers, covering a broad range of [use cases](https://cqcl.github.io/lambeq/use-cases.html), both quantum and "classical", where the lat…
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PennyLane currently supports quantum-aware optimizers including [QNGOptimizer](https://pennylane.readthedocs.io/en/latest/code/api/pennylane.QNGOptimizer.html) and [RotosolveOptimizer](https://pennyla…
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# Abstract
We want to use the full capabilities of both Qiskit and pyTorch to develop hybrid quantum-classical machine learning algorithms (e.g. meta-learning for quantum circuits with classical neur…
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# Abstract
Let's try and explore Hybrid quantum-classical Neural Networks with PyTorch and Qiskit:
https://qiskit.org/textbook/ch-machine-learning/machine-learning-qiskit-pytorch.html
Examples:
…
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Currently, the `QuantumModel` is inheriting from a PyTorch `nn.Module`. This does not play well with the Jax backend thus it is currently not possible to use the quantum model interface with Jax.
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### Expected behavior
I apologize for reposting this issue from the forum [https://discuss.pennylane.ai/t/memory-leak-in-when-using-lighning-kokkos-device/5218](url), but this issue is a major roadbl…
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Currently, several demos are not executed when the website is deployed, for a couple of reasons:
* Execution time: `qgrnn`, `qonn`, `quantum_neural_net`
* Requires access to hardware/external se…
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### What should we add?
This issue covers adding Effective Dimension class for all PyTorch models. This would help to compare effective dimensions between the classical and quantum/hybrid models.
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### Expected behavior
When post-processing the output of a quantum circuit that returns a torch layer, the gradient of the `torch.sqrt()` function at the point '0' should be defined as 0. According…