AmpForm
AmpForm is a Python library of spin formalisms and dynamics with which you can automatically formulate symbolic amplitude models for Partial Wave Analysis. The resulting amplitude models are formulated with SymPy (a Computer Algebra System). This not only makes it easy to inspect and visualize the resulting amplitude models, but also means the amplitude models can be used as templates for faster computational back-ends (see TensorWaves)!
Visit ampform.rtfd.io for several usage examples. For an overview of upcoming releases and planned functionality, see here.
Available features
- Automatic amplitude model building
Convert state transition graphs from QRules to an amplitude model that is mathematically expressed with SymPy and can be converted to any backend (see TensorWaves). - Spin formalisms
- Helicity formalism
- Canonical formalism
- Spin alignment
for generic, multi-body decays that feature different decay topologies. See also
ampform-dpd!
- Dynamics
- Relativistic Breit–Wigner, optionally with form factors and/or energy-dependent width
- Symbolic K-matrix for an arbitrary number of poles and channels
- Symbolic P-vector for an arbitrary number of poles and channels
- Chew–Mandelstam dispersion integral for a correct treatment of analyticity in the presence of thresholds.
Contribute
See CONTRIBUTING.md
Metadata
Release files for ampform 0.16.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ampform-0.16.1.tar.gz | 484.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ampform-0.16.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 573.6 kB
Release files / ampform-0.16.1.tar.gz
| Download URL | ampform-0.16.1.tar.gz |
|---|---|
| Size | 484.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
202077e8816adc5716a75df7b7e8db28fcfff1229e02badd19ce12897ee4637f
|
|
BLAKE2b-256 checksum How to use checksums |
9244d41ae41c51ea936de9244134076c89209213de93f5c04443a69631f51fac
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logRelease files / ampform-0.16.1-py3-none-any.whl
| Download URL | ampform-0.16.1-py3-none-any.whl |
|---|---|
| Size | 89.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0e9723fe22512b3aeb1e8720d486b5d5282905499dafc77be0006b5512132e56
|
|
BLAKE2b-256 checksum How to use checksums |
7781fd3c2c4bacdf14844ad1653f6a5386355feeac6a58c20a9508d7868bc330
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency log
