Python port of ParametricDFT.jl: learning parametric quantum Fourier transforms via manifold optimization.
Project description
pdft
A Python port of ParametricDFT.jl: learning parametric quantum Fourier transforms via manifold optimization. The package implements a variational approach that approximates the Discrete Fourier Transform (DFT) with parameterized quantum circuits.
Status: early scaffold. The Julia package is the reference implementation; this repository will grow the Python equivalent incrementally.
Installation
Once published on PyPI:
pip install pdft
From source:
git clone https://github.com/zazabap/pdft.git
cd pdft
pip install -e ".[dev]"
Quick start
(coming soon — mirrors the make example demo in the upstream Julia
package)
Background
See the upstream notes for the theory:
License
MIT. See LICENSE. This project is a derivative port of ParametricDFT.jl (Copyright © 2025 nzy1997, MIT).
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