snappy-11-tets 1.20

Database of cusped hyperbolic manifolds triangulizable by <= 11 tetrahedra

This repository stores the manifold database of a complete census of all 505352 orientable cusped hyperbolic 3-manifolds whose minimal ideal triangulations consist of 11 tetrahedra, and includes the source code for the Python module snappy_11_tets which packages them up for use in SnapPy.

The orientable cusped census of 10 tetrahedra has been merged into snappy_manifolds in its recent release of version 1.4, and now comes with SnapPy version 3.3 automatically, see SnapPy’s News page for details.

To install this package, do:

python -m pip install --upgrade snappy_11_tets

or, if you are using SageMath:

sage -pip install --upgrade snappy_11_tets

The above command should be able to automatically install the 1.4 version of snappy_manifolds, if it is not readily installed.

To use this module with SnapPy, you need to have SnapPy version 3.3.2 or later installed. You can check your SnapPy version with:

>>> import snappy
>>> snappy.__version__
'3.3.2'

If you have an older version of SnapPy, you can upgrade it with:

python -m pip install --upgrade snappy

or, if you are using SageMath:

sage -pip install --upgrade snappy

With the above setup, simply importing snappy will automatically import snappy_11_tets and make the extended census available in SnapPy. The extended census can then be accessed via SnapPy’s Manifold class. For example:

>>> m = snappy.Manifold('o11_123456')
>>> m.triangulation_isosig()
'lLALPzAMccbbegfhihjkkhhrwahhxrxhw_BbBa'

>>> m = snappy.Manifold('o11_123456(2,3)')
>>> m.triangulation_isosig()
'lLALPzAMccbbegfhihjkkhhrwahhxrxhw_BbBa(2,3)'

The iterator for all manifolds in this module, along with those in snappy_manifolds, is snappy.OrientableCuspedCensus. For example:

>>> len(snappy.OrientableCuspedCensus)
717993

>>> for M in snappy.OrientableCuspedCensus[-9:-6]: print(M, M.volume())
o11_505343(0,0) 11.0017490870299
o11_505344(0,0) 11.0075240445813
o11_505345(0,0) 11.0075240445813

>>> for M in snappy.OrientableCuspedCensus(num_cusps=2)[-3:]: print(M, M.volume(), M.num_cusps())
o11_505349(0,0)(0,0) 11.0179027639862 2
o11_505350(0,0)(0,0) 11.0232112584876 2
o11_505351(0,0)(0,0) 11.0232112584876 2

The raw source for the tables are in:

manifold_src/original_manifold_sources

stored as plain text CSV files for the potential convenience of other users. The triangulations themselves are stored in the “isosig” format of Burton, as described in the appendix to this paper with an added “decoration” suffix that describes the peripheral framing.