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This is the AD/AE for the paper (Optimizing Quantum Fourier Transformation (QFT) Kernels for Modern NISQ and FT Architectures)

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qft_on_regular_architectures

This is the AD/AE for the paper (Optimizing Quantum Fourier Transformation (QFT) Kernels for Modern NISQ and FT Architectures)

Part 1: Output the qubit mapping by generating the gate execution order in different architectures:

NISQ: Google Sycamore

python3 Googlesycamore_qft.py <the value of m for m*m grid>

NISQ: IBM Heavy-hex

python3 heavy_hex_qft.py <# qubits in the main row>

Fault Tolerant: Lattice sugery

python3 lattice_sugery_qft_mix.py <an even value of #units > 

Part 2: Reproduce the figure in our paper:

To get the compiled program data in three different backends, just run following three commands (one for each architecture).

NISQ: Google Sycamore

python3 our_sycamore.py

NISQ: IBM Heavy-hex

python3 python3 our_heavy-hex.py

Fault Tolerant: Lattice sugery

python3 our_lattice_surgery.py

Generate figures of different architectures (results will be saved in folder csv_data).

cd sabre
python3 sabre_qft.py "N*N"
python3 sabre_qft.py "sycamore"
python3 sabre_qft.py "heavy-hex"

To do visualization you can implement the following code.

cd ..
python3 draw_figures.py

The results will be stored in 6 pdf files (Heavyhex_Depth.pdf, Heavyhex_SWAP.pdf, Sycamore_Depth.pdf, Sycamore_SWAP.pdf, Lattice_surgery_Depth.pdf, Lattice_surgery_SWAP.pdf)

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This is the AD/AE for the paper (Optimizing Quantum Fourier Transformation (QFT) Kernels for Modern NISQ and FT Architectures)

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