TeNPy Forum

See https://github.com/tenpy/tenpy/pull/495 for functions that export tenpy objects (MPS or Hamitlonians from a model) to full matrix representations.

I assume you mean the Bose Hubbard model?
In what state do you want to take the expectation value?
If you want it in the groundstate, you can take an MPS psi resulting from DMRG and use
psi.expectation_value('N'), which gives you the particle number on every single site.

tenpy, with charge conservation has a basis order that might be surprising. See e.g. the warning in Site So I assume that you are writing down H_sp in an incompatible basis (probably you use {|up>, |down>}, and if you use charge conservation, tenpy will use {|down>, |up>}). Have a look at model.lat....

Confirmed that the workaround above works for my quick test.
For the fix see https://github.com/tenpy/tenpy/pull/481

Hi, Looks like this is bug in the consistency_check ecosystem, specifically for IrregularLattices. TeNPy tries to warn users if the lattice has too large N_sites_per_ring. This check causes an error, because N_sites_per_ring is None for the IrregularLattice. I will push a fix soon. In the meantime y...

Hi bart, just FYI that this will be resolved in the next version of tenpy, developed at https://github.com/tenpy/cyten. There, we consider this permutation in ``Tensor.to_numpy()`` such that it behaves as expected, i.e. such that ``.combine_legs(...).to_numpy()`` is equivalent to ``.to_numpy().resha...

At first glance, I do not see why this code should raise such an error.
Please make sure you are using an up to date version of tenpy.
If the problem persists, please open an issue on github with a minimal code example that reproduces the bug, and include the full error message.

For Array_to_ndarray, the low hanging fruits are to operate on numpy arrays instead of python lists. I probably would initialize a final_array of correct length (sum of the ``block.size`` for all blocks) and dtype, then in the loop set elements of the final_array to the block (keep somecounter varia...

Hi, This can not be done out of the box. TEBD will also be difficult, since your gates are not nearest neighbour (even if H_i are NN on their subsystem, they are NNN on the full system). You could force TEBD by grouping sites to a nearest neighbour model. I would go for MPO time evolution though. Yo...

Yes, you can have a look at the operator in the site In [3]: import tenpy as tp In [4]: site = tp.FermionSite(filling=0.5) In [5]: site.dN Out[5]: <npc.Array shape=(2, 2) labels=['p', 'p*']> In [6]: site.dN.to_ndarray() Out[6]: array([[-0.5, 0. ], [ 0. , 0.5]]) In[7]: # The basis is { |empty> , |ful...

Hi,
Yes it turns out those examples are not yet updated for v1.0.
They should run with v0.99.
Working on a fix in https://github.com/tenpy/tenpy/pull/400.
Thanks for posting!