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metadata.json
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76 lines (76 loc) · 2.44 KB
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{
"title": "The stochastic parameter-shift rule",
"authors": [
{
"username": "co9olguy"
}
],
"executable_stable": true,
"executable_latest": true,
"dateOfPublication": "2020-05-25T00:00:00+00:00",
"dateOfLastModification": "2026-04-09T16:53:00+00:00",
"categories": [
"Optimization"
],
"tags": [],
"previewImages": [
{
"type": "thumbnail",
"uri": "/_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_stochastic_parametershift_rule.png"
}
],
"seoDescription": "Differentiate any qubit gate with the stochastic parameter-shift rule.",
"doi": "",
"references": [
{
"id": "banchi2020",
"type": "article",
"title": "Measuring Analytic Gradients of General Quantum Evolution with the Stochastic Parameter Shift Rule.",
"authors": "Leonardo Banchi and Gavin E. Crooks",
"year": "2020",
"journal": "",
"url": "https://arxiv.org/abs/2005.10299"
},
{
"id": "li2016",
"type": "article",
"title": "Hybrid Quantum-Classical Approach to Quantum Optimal Control.",
"authors": "Jun Li, Xiaodong Yang, Xinhua Peng, and Chang-Pu Sun",
"year": "2016",
"journal": "",
"url": "https://arxiv.org/abs/1608.00677"
},
{
"id": "mitarai2018",
"type": "article",
"title": "Quantum Circuit Learning",
"authors": "Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii",
"year": "2020",
"journal": "",
"url": "https://arxiv.org/abs/1803.00745"
},
{
"id": "schuld2018",
"type": "article",
"title": "Evaluating analytic gradients on quantum hardware.",
"authors": "Maria Schuld, Ville Bergholm, Christian Gogolin, Josh Izaac, and Nathan Killoran",
"year": "2019",
"journal": "",
"url": "https://arxiv.org/abs/1811.11184"
}
],
"basedOnPapers": [],
"referencedByPapers": [],
"relatedContent": [
{
"type": "demonstration",
"id": "tutorial_backprop",
"weight": 1.0
},
{
"type": "demonstration",
"id": "tutorial_general_parshift",
"weight": 1.0
}
]
}