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As a part of Quantum error correction review project, we explored tensor network codes (TNC). TNC has diverse nad promising use in quantum error correcting codes. It is powerful tools to design larger stabilizer codes, estimating code distance and maximum likelihood decoding.

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Tensor_Network_Codes

$\blacksquare$ Employed Tensor network framework for design and analysis of Stabilizer Quantum error correcting codes

$\blacksquare$ Constructed 11-Qubit stabilizer code via tensor contraction of the three 5-Qubit stabilizer codes

$\blacksquare$ Evaluated code distance and maximum likelihood decoding for the 11-Qubit code via the tensor technique

$\blacksquare$ Examined the impact on successful error correction capability of a tensor network if doped suitably

We used the scripts in this Julia module to generate the stabilizer codes:

https://github.com/ITensor/ITensors.jl.git

Main References:

$\star$ Local Tesor Network Codes (Terry Farrelly et al. 2022 New J. Phys. 24 043015)

$\star$ Tensor Network Codes (Phys. Rev. Lett. 127, 040507 – Published 23 July 2021)

Team Members

Manish Kumar, Q.Tech, IISc Bengaluru

Harsh Ojha, Q.Tech, IISc Bengaluru

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As a part of Quantum error correction review project, we explored tensor network codes (TNC). TNC has diverse nad promising use in quantum error correcting codes. It is powerful tools to design larger stabilizer codes, estimating code distance and maximum likelihood decoding.

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