quimb is an easy but fast python library for quantum information and many-body calculations, including with tensor networks. The code is hosted on github, do please submit any issues or pull requests there. It is also thoroughly unit-tested and the tests might be the best place to look for detailed documentation.
The core quimb module:
Uses straight numpy and scipy.sparse matrices as quantum objects
Makes it easy to construct operators in large tensor spaces (e.g. 2D lattices)
Uses efficient methods to compute various quantities including entanglement measures
Has many built-in states and operators, including those based on fast, parallel random number generation
Can perform evolutions with several methods, computing quantities on the fly
Has an optional slepc4py interface for easy distributed (MPI) linear algebra. This can massively increase the performance when seeking, for example, mid-spectrum eigenstates
The tensor network submodule quimb.tensor:
Uses a geometry free representation of tensor networks
Uses opt_einsum to find efficient contraction orders for hundreds or thousands of tensors
Can perform those contractions on various backends, including with a GPU
Can plot any network, color-coded, with bond size represented
Can treat any network as a scipy LinearOperator, allowing many decompositions
Can perform DMRG1, DMRG2 and DMRGX, in matrix product state language
Has tools to efficiently address periodic problems (transfer matrix compression and pseudo-orthogonalization)
Can perform MPS time evolutions with TEBD
The full documentation can be found at: http://quimb.readthedocs.io/en/latest/. Contributions of any sort are very welcome - please see the contributing guide.
1 maintainer
Release files for quimb 1.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| quimb-1.1.2.tar.gz | 174.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| quimb-1.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 345.6 kB
Release files / quimb-1.1.2.tar.gz
| Download URL | quimb-1.1.2.tar.gz |
|---|---|
| Size | 174.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5a64882ea636662eff3aee13d5497a5d03d8d3076cd9660848a107e6726f9ca2
|
|
BLAKE2b-256 checksum How to use checksums |
b7c3d92cf007a36bdb7873edc0af5b1c148e064802649a82e31005244b19371c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.6
|
Release files / quimb-1.1.2-py3-none-any.whl
| Download URL | quimb-1.1.2-py3-none-any.whl |
|---|---|
| Size | 171.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a1c756d30fd7f5d9500a26cc13f9af4f93a90888639f1bb9578415d0e9ef00b6
|
|
BLAKE2b-256 checksum How to use checksums |
70d9f0174eecc1c0312909cbb046f3eba11385b3f158e1afa14fb7d7c0b468a2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.6
|
