I think that it is fairly a good proposal.
However, the only problems are that we may not be familiar with the 
physics, or quantum computation, 
or we may not have clear roadmap whether the algorithm is significantly 
necessary for the module,
However, if you already have self-motivated knowledge and practice about 
the topic, 
some people may be able to guide to complete your work with with general 
python programming or general mathematical background.

On Thursday, March 21, 2024 at 1:57:36 PM UTC+1 [email protected] wrote:

> Title: Pauli class implementation for Hamiltonain decomposition.
>
> *Idea*: 
> In 2023, Reggio et al <http://arxiv.org/pdf/2305.11847.pdf>, used xz code 
> for determining the commutation of the given two Pauli string, P1, P2. I 
> found that we can construct more efficient implementation of Pauli group 
> structure with two integer tuple, xz code including the next things.
> - Fast commuting determination.
> - Pauli matrix algebra of 2^n dimension as n length binary representation 
> of integer.
> - Matrix-xz code transformation.
>
> The matrix-xz code transformation is achieved through application of 
> "Tensorized 
> Pauli decomposition algorithm 
> <http://github.com/HANTLUK/PauliDecomposition>" method. They researched 
> to find decomposed coefficient location of the given Hermit matrix. I found 
> a transformation that xz code to corresponding coefficient location on the 
> matrix.
>
> *Status*: 
> I almost implemented core structure and oprations in Opttrot repository 
> <http://github.com/HYUNSEONG-KIM/OptTrot> of mine
> as a prototype.
> It was written in C at first, but python version also exists.
> Matrix-xz code transformation routine is remained.
>
> *Involved Software*
> Tensorized Pauli decomposition algorithm paper code
>
> *Difficulty*
> Intermediate
>
> *Prerequisite Knowledge*
> Linear algebra,
> Binary operation,
> Basic group theory,
>
> *Project Length*
> 175 hours
>

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