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QCBM Tutorial (#1053)
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**Title:**
Quantum Circuit Born Machines
**Summary:**
Introduces the ideas of Quantum Circuit Born Machines (QCBMs) along with
its gradient-based training. Applies QCBM to learn bars and stripes and
two peaks dataset.
**Relevant references:**

[Differentiable Learning of Quantum Circuit Born
Machine](https://arxiv.org/abs/1804.04168)

**Possible Drawbacks:**

**Related GitHub Issues:**

----
If you are writing a demonstration, please answer these questions to
facilitate the marketing process.

* GOALS — Why are we working on this now?: The purpose is to use
PennyLane to implement a popular algorithm in unsupervised generative
modelling based on the paper "Differentiable Learning of Quantum Circuit
Born Machine".

* AUDIENCE — Who is this for?: The demo provides a gentle introduction
to QCBMs, making it suitable for beginners. It also targets individuals
interested in generative modelling with quantum algorithms.

* KEYWORDS — What words should be included in the marketing post?: QCBM,
QML, MMD, Gradient-based Optimization

* Which of the following types of documentation is most similar to your
file?
(more details
[here](https://www.notion.so/xanaduai/Different-kinds-of-documentation-69200645fe59442991c71f9e7d8a77f8))
    
- [ ] Tutorial
- [x] Demo
- [ ] How-to

---------

Co-authored-by: Guillermo Alonso-Linaje <[email protected]>
Co-authored-by: Alvaro Ballon <[email protected]>
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3 people authored May 22, 2024
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4 changes: 4 additions & 0 deletions _static/authors/gopal_ramesh_dahale.txt
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.. bio:: Gopal Ramesh Dahale
:photo: ../_static/authors/gopal_ramesh_dahale.jpeg

Gopal is a quantum research software engineer at Qkrishi and a Qiskit advocate interested in applications of quantum computing in machine learning, chemistry and combinatorial optimization problems.
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96 changes: 96 additions & 0 deletions demonstrations/tutorial_qcbm.metadata.json
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"categories": ["Quantum Machine Learning"],
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"authors": "Benedetti, Marcello and Garcia-Pintos, Delfina and Nam, Yunseong and Perdomo-Ortiz, Alejandro",
"year": "2018",
"journal": "npj Quantum Information",
"doi": "10.1038/s41534-019-0157-8"
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"title": "Expressive power of parametrized quantum circuits",
"authors": "Du, Yuxuan and Hsieh, Min-Hsiu and Liu, Tongliang and Tao, Dacheng",
"year": "2020",
"publisher": "American Physical Society",
"journal": "Phys. Rev. Res.",
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