TeNPy Forum

The Warning is very relevant here: since version 0.9.0 , the `orthogonal_to` should not be an entry in the `dmrg_params`, but should be a direct keyword argument to the dmrg.run() function, i.e. somthing like dmrg.run(psi, M, dmrg_params, orthogonal_to=states) . As an alternative, you might want to ...

1) If you look at the imange of the tenpy.models.lattice.Triangular lattice, you'll see that it's 30 degrees rotatet compared to your image - that's the pi/6 offsett here. 2) If you explicitly have Jxy, Jyx etc, then these will contribute to the very same "terms" Sx_i Sy_j etc that the DMI...

Not sure if this is still relevant or solved by now, but anyways: the issue here is that the tenpy.models.lattice.Chain expects that it has a single-site unit cell only. Try using a more general lattice that allows for multiple sites in the MPS unit cell. The "correct" or recommend way in ...

As documented, the strength argumente of add_coupling can be a numpy array - for a square lattice with Lx by Ly sites, for nearest-neighbor hopping/interaction in y -direction, it could be of shape (Lx, Ly-1), or for the one in x-direction (Lx-1, Ly), respectively.

At the moment, you should use tenpy.algorithms.purification.PurificationApplyMPO for models with long range. (Or alternatively group sites and use the PurificationTEBD as you suggested.) TDVP doesn't work with purification at the moment. Really, we should refactor the purification code a bit such th...

The best idea I can come up with on the spot would be to contract Tr(rho^2) as a tensor network from left to right. There's no function for that in TeNPy ritght now, but it shouldn't be hard to implement that. Doing this is O(chi^5), though, so it's quite expensive compared to the usual O(chi^3) sca...

1) these `d` are the time steps for the time evolution that give you a second-order instead of first-order precision by canceling the error terms of O(dt^2). 2) The the new post in that topic. As I said there, it's fixed if you call psi.canonical_form() once more (at least for finite systems). Fix i...

The fix is here: PR #414

Since there was another question coming back to this: I do understand this now. The error comes from the fact that the imaginary TEBD algorithm applies non-unitary 2-site gates, which change the state and in general also singular values on other bonds. After one update sweep, we end with A S B B B B...

Indeed, there's no predefined model for that, but it shouldn't be too difficult to write a new model class for that. Basically, you want to adjust the exisiting tenpy.models.tj_model.TJModel , but use a new bosonic version of the tenpy.networks.site.SpinHalfHoleSite as the local site. Try starting t...

I'm confused. ED should give you an MPS on a finite system, possibly with PBC (?). How did you map that to the infinite system for comparison?

If you want to compare 1:1, you need to compare finite MPS on PBC to ED on PBC, as I explained above.

The finite mps in Tenpy always has open boundary conditions. In other words, in finite systems, the vL on the first tensor should be trivial of dimension 1, and so should be the vR leg of the last tensor. Closing the loop on the virtual legs with a trace is nasty for numerical simulations, since it ...

Let me be a bit more explicit: in the simple case of the Ladder, the following lines in init_couplings are equivalent: add_coupling(-t, 0, 'Cdu', 0, 'Cu', dx=1, plus_hc=True) add_coupling(-tv, 0, 'Cdu', 1, 'Cu', dx=1, plus_hc=True) add_coupling(-t, 1, 'Cdu', 1, 'Cu', dx=1, plus_hc=True) for x in ran...

Hi Fabio, whether you call add_coupling or explicitly loop over add_local_term doesn't matter for the final DMRG run, if you get the same couplings in the MPO of the hamiltonian - but with the latter, you need to iterate over the starting point of the couplings in real space, so you are responsible ...

It doesn't allow this out of the box, but you can easily write your own subclass of the TEBD Engine which just plugs in the corresponding Us. Essentially, you want to re-use the `update_step` function for the evolution (and maybe the first order suzuki trotter decomposition, depending on how you wan...

I've quickly fixed that formatting to include brackets in 9739ac3a4e26cbbfada009ec6bef6c3d7286a0a8

The subscript notation is a bit misleading here, because it suggests that it only applies to the next operator. Really, you should read those operators to be grouped like this: 1.00000 * (Cdd Cu)_0 (Cdu Cd)_1 + 1.00000 * (Cdd Cu)_1 (Cdu Cd)_2 + 1.00000 * (Cdd Cu)_2 (Cdu Cd)_3 + 1.00000 * (Cdd Cu)_3 ...

Jakob is totally right, of course. Let me just mention that it wouldn't be too hard to extend TEBD to work with this. Define a new LadderTEBDEngine, which takes the two models as input, and define 2 separate TEBD engines for them. Then overwrite: def evolve(...): # start with site order # A0 B0 A1 B...

If you need to_matrix, why don't you implement that function directly on the existing transfer matrix? To get a consistent result, all tensor which you extract *need* to be in the same canonical form, e.g. all right-canonical 'B' form. After a plain DMRG run (without a call of psi.canonical_form() i...

I guess the answer is a bit late, but for those finding this in the future: it should just work like this: In [10]: M = tenpy.FermiHubbardModel(dict(L=10, cons_Sz='Sz', cons_N='N')) In [11]: M.lat.unit_cell[0].leg.chinfo Out[11]: ChargeInfo([1, 1], ['N', '2*Sz']) In [12]: psi = tenpy.PurificationMPS...

The error comes because you try to add a term with 3 fermionic operators - this would require an open Jordan wigner string when mapping to spins, and thus be a non-local operator. More generally, you can't write physical Hamiltonians with an odd number of fermionic operators, because they violate lo...

This is equivalent to the Su-Schrieffer-Heger (SSH) chain, which has a topolgical phase with edge modes. Given that your filename starts with ssh_, I assume you're familiar with that. the XXZChan has Sz conservation by default. That means if you fix the initial state to be in a particular Sz charge ...

This reminds me of one of my first work on tensor networks, 1509.00696 - using back then new W_II method that we now have in the ExpMPOEvolution in TeNPy :-) While the Hamiltonian is symmetric under exchange of x/y, the MPS snaking through the square lattice explicitly breaks it - hopping in y-direc...

To reliably benchmark DMRG, I recommend to pin the number of sweeps by setting min_sweeps=max_sweeps to some fixed number - the total run time is just proportional to the number of sweeps, and how many sweeps it does can sometimes depend on subtle differences in convergence thresholds. Indeed, your ...

Tenpy also tries to solve the schrlödinger equation... I guess you compared to exact evolution for a non-interacting system, or exact diagonalization? TDVP does the time evolution with the effective Hamiltonian, i.e. H projected onto the local single-site/two-site MPO. If you have only bond dimensio...