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Bring back ml_classical_shadows demo (#1214)
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This reverts the deletion of "Machine learning for quantum many-body
problems" tutorial as a non-executable demo compatible with the latest
version of PennyLane.

[sc-68239]

---------

Co-authored-by: Ivana Kurečić <[email protected]>
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obliviateandsurrender and ikurecic authored Sep 13, 2024
1 parent 8b2a166 commit 180b9f1
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66 changes: 66 additions & 0 deletions demonstrations/ml_classical_shadows.metadata.json
Original file line number Diff line number Diff line change
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{
"title": "Machine learning for quantum many-body problems",
"authors": [
{
"username": "whatsis"
}
],
"dateOfPublication": "2022-05-02T00:00:00+00:00",
"dateOfLastModification": "2024-09-05T00:00:00+00:00",
"categories": [
"Quantum Machine Learning"
],
"tags": [],
"previewImages": [
{
"type": "thumbnail",
"uri": "_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_machine_learning_quantum_manybody_problems.png"
},
{
"type": "large_thumbnail",
"uri": "_static/demo_thumbnails/large_demo_thumbnails/thumbnail_large_machine_learning_quantum_manybody_problems.png"
}
],
"seoDescription": "Learn how to apply machine learning to quantum many-body problems by using classical shadow formalism and ML to predict the ground-state properties of the 2D antiferromagnetic Heisenberg model.",
"doi": "",
"canonicalURL": "/qml/demos/ml_classical_shadows",
"references": [
{
"id": "preskill",
"type": "article",
"title": "Provably efficient machine learning for quantum many-body problems",
"authors": "H. Y. Huang, R. Kueng, G. Torlai, V. V. Albert, J. Preskill",
"year": "2021",
"journal": "",
"url": "https://arxiv.org/abs/2106.12627"
},
{
"id": "neurtangkernel",
"type": "article",
"title": "Neural tangent kernel: Convergence and generalization in neural networks",
"authors": "A. Jacot, F. Gabriel, and C. Hongler",
"year": "2018",
"journal": "",
"url": "https://proceedings.neurips.cc/paper/2018/file/5a4be1fa34e62bb8a6ec6b91d2462f5a-Paper.pdf"
}
],
"basedOnPapers": ["10.48550/arXiv.2106.12627"],
"referencedByPapers": [],
"relatedContent": [
{
"type": "demonstration",
"id": "tutorial_classical_shadows",
"weight": 1.0
},
{
"type": "demonstration",
"id": "tutorial_kernel_based_training",
"weight": 1.0
},
{
"type": "demonstration",
"id": "tutorial_kernels_module",
"weight": 1.0
}
]
}
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