VQE-LD tutorial#1771
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Hi @ericoteixeira thanks for opening this PR. It looks like you have included your Python virtual environment. Could you please delete this from the PR? In addition, do you have a notebook or python script for the VQE-LD demo? |
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Hi @josh146,
I just removed the environment and updated the PR.
With respect to a python script, I attached a file.
Best Regards
On 7 May 2026, at 12:11, Josh Izaac ***@***.***> wrote:
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(PennyLaneAI/demos#1771)
<#1771 (comment)>
Hi @ericoteixeira <https://github.com/ericoteixeira> thanks for opening this PR. It looks like you have included your Python virtual environment. Could you please delete this from the PR?
In addition, do you have a notebook or python script for the VQE-LD demo?
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Hi PennyLane team, I would like to follow up on this PR kindly. The demo is based on our recent Journal of Computational Chemistry publication, and I would be happy to address any feedback or make any required modifications. |
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Title:
An overview of VQE-LD
Summary:
Improving ground state energy prediction by incorporating the convergence of the one-particle reduced density matrix in VQE.
Relevant references:
Amanda Marques de Lima, Erico Souza Teixeira, Eivson Darlivam Rodrigues de Aguiar Silva, Ricardo Luiz Longo. Improving Energy and Molecular Properties by Convergence of the One-Particle Reduced Density Matrix in Variational Quantum Eigensolvers (VQE). Journal of Computational Chemistry 47 (2026). https://doi.org/10.1002/jcc.70289
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?
Present a variation of VQE, now incorporating the one-particle reduced density matrix (1-RDM) in the convergence process.
AUDIENCE — Who is this for?
Chemistry researchers in quantum computing.
KEYWORDS — What words should be included in the marketing post?
Density matrix, quantum computing, variational quantum eigensolver
Which of the following types of documentation is most similar to your file?