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doc/src/Projects/2025/Project2/Project2.do.txt

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TITLE: Quantum Computing and Quantum Machine Learning
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AUTHOR: "FYS5419/9419":"https://www.uio.no/studier/emner/matnat/fys/FYS5419/index-eng.html", Quantum computing and quantum machine learning, University of Oslo, Norway
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DATE: Spring semester 2024, deaadline June 7
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DATE: Spring semester 2025, deaadline June 1
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======= Possible paths for project 2 =======
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We discuss here three paths for the second project.
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Tentative deadline June 7.
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Tentative deadline June 1.
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The report should also be styled as a scientific report. The guidelines
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The report should be styled as a scientific report. The guidelines
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we have established at
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URL:"https://github.com/CompPhysics/AdvancedMachineLearning/tree/main/doc/Projects/EvaluationGrading"
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could be useful in structuring your report. We have also added a
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lecture set by Anne Ruimy (director of EDP journals) on how to write
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effective titles and abstracts. See
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URL:"https://github.com/CompPhysics/AdvancedMachineLearning/tree/main/doc/Projects/WritingAbstracts"
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for these lectures. Finally, at
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URL:"https://github.com/CompPhysics/AdvancedMachineLearning/tree/main/doc/Projects/2023/ProjectExamples"
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you can find different examples of previous reports. See also the literature suggestions below.
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for these lectures.
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We would like to suggest three different paths (_select only one of these_). They are
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We would like to suggest four different paths (_select only one of these_). They are
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o Implementing quantum Fourier Transforms (QFTs), the phase estimation algorithm and if time allows (optional Shor's algorithm).
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o Quantum Machine Learning project
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o Implementing Quantum Boltzmann machines
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o Study the solution of quantum mechanical eigenvalue problems with systems from atomic/molecular physics and quantum chemistry using adaptive QPE
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o Other ideas?
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These projects are described here.
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===== Alternative one, QFTs =====
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=== Project 2 g): These part is optional ===
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=== Project 2 g): This part is optional ===
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If you have time and would to explore Shor's algorithm for factoring, sections 6.5 and 6.6 of Hundt contain an in depth discussion on how to implement this famous algorithm.
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For an implementation, see URL:"https://helda.helsinki.fi/server/api/core/bitstreams/eeadc874-f41c-4795-9149-2cd9a3bfe10d/content". You should restrict the studies here to some few qubits.
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===== Alternative four, Adaptive VQE =====
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In this alterantive we study the solution of quantum mechanical
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eigenvalue problems with possible systems from atomic/molecular physics and
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quantum chemistry using the adaptive VPE method.
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This project can be seen as an extension of project 1 and could contain the following research elements
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o Extend and generalize the Lipkin model to more than $N=4$ particles.
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o Test different initialization of the qubits for the Lipkin model
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o Implement the adaptive VQE and compare with the VQE from project 1, see for example Keran Chen's master thesis at URL:"https://www.duo.uio.no/handle/10852/114006" or at URL:"https://github.com/CompPhysics/QuantumComputingMachineLearning/blob/gh-pages/doc/Projects/2025/Project2/Literature/KeranMScthesis.pdf". See also the article by Grimsley *et al.,* at URL:"https://www.nature.com/articles/s41467-019-10988-2"
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o Extend eventually your codes to include more general Hamiltonians. Here you would need to implement the so-called Jordan-Wigner transformation (Notes will be added).
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o Feel free to suggest additional topics.
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===== Literature =====
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The following articles and books (with codes) are relevant here:

doc/src/Projects/2025/Project2/make.sh

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cp $name.tex ${name}.tex
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# Publish
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dest=../../../../Projects/2024
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dest=../../../../Projects/2025
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if [ ! -d $dest/$name ]; then
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mkdir $dest/$name
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mkdir $dest/$name/pdf

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