TeNPy Forum

Okay, I paid for the Gold membership of readthedocs to remove the ads (That's the drawback, it costs money. But I don't mind supporting ReadTheDocs with a few dollars a month, their service to the community is great :) ) I've also updated the references from within the TeNPy repository and the links...

Now I face the problem that in order to see the Ising-like phase transition I want to calculate the correlation function <\Psi_0 |T^y_i T^y_{i+r} |\Psi_0> with T^y_i= \frac{1}{2}(-i c^\dagger_{i,u}c_{i,d}+i c^\dagger_{i,d}c_{i,u}) where u and d are again the rungs of the ladder. Since the Ladder ge...

Looks good! May I ask how for an example what you calculated in the end (roughly)? It probably suffices for terms with the same operators on both sites (e.g. density-density correlations "N_i N_j"), but might not be enough for more complicated pair correlations with different operators (e....

You got it almost right. Just a single, but crucial typo in term 1.2 (which you correctly identified as the problem): In the second line (h.c. term), you have a 0 instead of a 1 in the fourth argument. This makes the Hamiltonian non-hermitian and obviously leads to problems when running DMRG (The La...

No, you got that wrong. A value of update_env=0 does not imply that you're not doing iDMRG; the DMRG engine will still grow the environments on the left and right by one unit cell in each sweep. A nonzero update_env > 0 tells the DMRG engine to do the specified number of environment_sweeps without d...

[mention]Leon[/mention], [mention]mpsforphysics[/mention] , [mention]JakobUnfried[/mention] do you have any preferences?

You need to do some postprocessing, there is currently no function for that in TeNPy. However, I agree that it would be very useful to have it. If you write the function, it would be great if you could post it here such that we can include it in TeNPy (or you just submit a pull request on github). Y...

The model is gapless in the range -1 < V < 1, so this is definitely a difficult region. As far as I know, VUMPS might indeed be better suited for that, feel free to implement it ;-) Which version of tenpy are you using? In particular, does your version include the fix of 95 (v0.5.0 or later)? The is...

By definition, a tenpy.models.model.NearestNeighborModel can only contain nearest-neighbor couplings. That is the case because it provides a representation of the hamiltonian in terms of H_bond , where each H_bond is a term involving just two neighboring sites. Hence, you can *not* make a model inhe...

Readthedocs currently includes advertisement, but we could opt-out of that.

Hi all, so far, I had hosted the documentation on https://tenpy.github.io with github pages. I have now tried to setup the documentation on https://tenpy.readthedocs.io as well, which is an awesome place hosting documentation for many, many python packages (and other stuff as well). The nice thing t...

Version 0.5.0 has been released. Before updating , please read the corresponding section in the change log , in particular the part on the backwards incompatible changes! It is now supported to install TeNPy with pip via pip install --upgrade physics-tenpy # for 'stable' versions I'd recommend an in...

Welcome! I think the problem depends on how you installed tenpy. Did you pip install physics-tenpy , or did you download the code and use inline]python setup.py install[/inline] from within the TeNPy folder, or did you simply set export PYTHONPATH=/Users/username/TeNPy" ? In the latter case, it...

If you run the code with conserve='N' , you should get a UserWarning tenpy/networks/mps.py:396: UserWarning: flat array has non-zero entries in blocks incompatible with charge B = npc.Array.from_ndarray(B, legs, dtype) The reason is that for conserve='N' , each tensor needs to have a well defined ch...

You're absolutely right, the different type of "Site" makes the difference here.
That's certainly a thing to keep in mind, so I actually added your example (slightly extended) to the documentation of from_product_state.
Do you agree that it is more clear now?

Yes, that is indeed what you want. Just for reference, here is the documentation: from_product_state . If you look at the example, one line below the state is normalized, such that it gets np.array([1/sqrt(2), -1/sqrt(2)]) . This is the negative-x state of a spin-1/2 and equivalent to the np.array([...

So, is it fine to miss S? or is it typo? That should be fine, it's just the difference between checking the absolute and the relative error. For the energy, we need to check the relative error: the energy scale can vary by quite a bit simply by rescaling your Hamiltonian. However, the entropy can n...

The all-up state is an exact eigenstate of the model and hence won't evolve in time, in particular if you use Sz-conservation (which you do in this case): the all-up state is the only state in the sector with S_{total} = L/2 . Try starting from a different state, e.g. all up but one spin down (which...

Yes, that's for sure a good idea. Indeed, I thought about it and started to implement it already a few days ago, but I'm quite busy these days (moving to UC Berkeley ), so I didn't have time to finish it. Hopefully, I can find a bit time next week - unless you volunteer to time to implement it

One alternative is to iteratively do QR decompositions (and RQ decompositions). You decompose your state as M M M M M = Q R M M M M = Q Q R M M M = ... = Q Q Q Q R and as M M M M M = M M M M R' Q' = M M M R' Q' Q' = ... = R' Q' Q' Q' Q' until your iterations converge. Then your state is in the form ...

What order (second or fourth) and timestep do you use for TEBD? Does this go away if you simply use a smaller timestep/higher order? Did you try to look at the overlap with the initial ground state returned by DMRG (as a function of time)? Converging just 3 digits in energy still a bit unprecise, ma...

Sorry, that was a bug in MPS.get_rho_segment. It should be fixed with the latest version.

In general, the parameter N_sweeps_check should not change the convergence properties - at least not much.... Let's look at what it influences: For checking the convergence, DMRG checks the average change of the energy / entropy per sweep in the last N_sweeps_check steps. The parameter update_env de...

The function entanglement_entropy_segment should accept disconnected segments, e.g. segment=[0, 2, 4, 6, 8] . However, it works only for *small* enough number of sites in your density matrix - it's exponentially expensive, because it constructs the full density matrix, tracing out the rest of the si...

Hi, indeed, the irregular lattice is still an open 77 . Sorry, there's so much stuff to do. I had to write and defend my PHD thesis, so I didn't have too much time to work on TeNPy lately. Hopefully, this will change again. ;) To make sure I understand correctly, you want a geometry like this: Boson...