Metadata-Version: 2.4
Name: pdft
Version: 0.2.1
Summary: Python port of ParametricDFT.jl: learning parametric quantum Fourier transforms via manifold optimization.
Project-URL: Homepage, https://github.com/zazabap/pdft
Project-URL: Issues, https://github.com/zazabap/pdft/issues
Project-URL: Upstream, https://github.com/nzy1997/ParametricDFT.jl
Author: zazabap
License: MIT License
        
        Copyright (c) 2026 zazabap
        
        Portions of this project are a Python port of ParametricDFT.jl
        (https://github.com/nzy1997/ParametricDFT.jl), Copyright (c) 2025 nzy1997,
        originally released under the MIT License.
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
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        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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License-File: LICENSE
Keywords: dft,fourier,jax,manifold-optimization,quantum,variational
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.11
Requires-Dist: jax>=0.10.0
Requires-Dist: typing-extensions>=4.5
Provides-Extra: dev
Requires-Dist: jaxtyping>=0.2; extra == 'dev'
Requires-Dist: matplotlib>=3.8; extra == 'dev'
Requires-Dist: numpy>=1.26; extra == 'dev'
Requires-Dist: pytest-cov>=4; extra == 'dev'
Requires-Dist: pytest>=7; extra == 'dev'
Requires-Dist: ruff>=0.5; extra == 'dev'
Provides-Extra: gpu
Requires-Dist: jax[cuda12]>=0.10.0; extra == 'gpu'
Provides-Extra: plot
Requires-Dist: matplotlib>=3.8; extra == 'plot'
Description-Content-Type: text/markdown

# pdft

A Python port of [ParametricDFT.jl](https://github.com/nzy1997/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:

```bash
pip install pdft
```

From source:

```bash
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:
- [`note/stepbystep.pdf`](https://github.com/nzy1997/ParametricDFT.jl/blob/main/note/stepbystep.pdf)
- [`note/main.pdf`](https://github.com/nzy1997/ParametricDFT.jl/blob/main/note/main.pdf)

## License

MIT. See [LICENSE](LICENSE). This project is a derivative port of
ParametricDFT.jl (Copyright © 2025 nzy1997, MIT).
