Search found 429 matches
- 01 Jul 2019, 08:29
- Forum: HowTos and FAQ for TeNPy
- Topic: Some questions about the svd_theta
- Replies: 7
- Views: 8515
Re: Some questions about the svd_theta
The conversion to_ndarray discards information (namely: which index corresponds to which charges? what are the charge blocks we have?). Thus it cannot be reverted (at least not after subsequent tensordot/svd/...) and should be avoided at all. Instead you should use the functions provided by tenpy.li...
- 28 Jun 2019, 09:45
- Forum: HowTos and FAQ for TeNPy
- Topic: Possible issue with single-site TDVP
- Replies: 2
- Views: 4472
Re: Possible issue with single-site TDVP
Thanks to [mention]mpsforphysics[/mention] for fixing this!
- 28 Jun 2019, 09:41
- Forum: HowTos and FAQ for TeNPy
- Topic: norm_tol parameter for DMRG
- Replies: 2
- Views: 8401
Re: norm_tol parameter for DMRG
1) No, it doesn't. The problem is that bringing the state into canonical form during the DMRG run will screw up the environments. Thus, the `norm_tol` is only checking if the final state returned by DMRG is in canonical form. It tries to ensure the canonical form by performing a few more environment...
- 28 Jun 2019, 09:25
- Forum: HowTos and FAQ for TeNPy
- Topic: DMRG sweep problems
- Replies: 5
- Views: 6477
Re: DMRG sweep problems
This jumping sure looks very wrong and strange. Any chance you could provide a simple example code where this happens? Do you expect a (nearly) degenerate ground state in this case? Than it might just be jumping around between different solutions. It might help to use 'chi_list' to gradually increas...
- 28 Jun 2019, 08:48
- Forum: HowTos and FAQ for TeNPy
- Topic: Some questions about the svd_theta
- Replies: 7
- Views: 8515
Re: Some questions about the svd_theta
Hi Qicheng, how exactly do you want to extract the correlation length from the B? For a finite system, this is a somewhat ill-defined question, because you have no (guaranteed) periodicity. You might want to look at the correlation functions directly and fit an exponential to that. For an infinite s...
- 28 May 2019, 20:07
- Forum: HowTos and FAQ for TeNPy
- Topic: periodic conditions
- Replies: 7
- Views: 6523
Re: periodic conditions
Exactly as in the example you posted: just specify an array/list as "strength" in add_coupling. In fact, you don't even need to define your own model, if you're happy with the XXZ Chain /SpinChain with alternating strength: from tenpy.models.xxz_chain import XXZChain model_params = { 'bc_M...
- 28 May 2019, 08:34
- Forum: HowTos and FAQ for TeNPy
- Topic: periodic conditions
- Replies: 7
- Views: 6523
Re: periodic conditions
Welcome! The first argument of add_coupling is the strenght of the coupling. It can be a single value (if the strength is uniform all over the chain/lattice), but also a numpy array or something convertible a numpy array (which is the case here). The different values just indicate that the strength ...
- 15 May 2019, 13:47
- Forum: Releases
- Topic: Release v0.4.0
- Replies: 0
- Views: 19392
Release v0.4.0
Version 0.4.0 has been released. Before updating , please read the release notes . It is now supported to install TeNPy with pip via pip install --upgrade physics-tenpy # for 'stable' versions I'd recommend an installation with pip if you do not intend to modify the source files of TeNPy at any poin...
- 07 May 2019, 13:28
- Forum: HowTos and FAQ for TeNPy
- Topic: add_coupling in SpinModel
- Replies: 4
- Views: 4622
Re: add_coupling in SpinModel
These operators do not commute here because they are acting on the same site. \sigma_i and \tau_i certianly do commute, which is obvious if you don't think in the grouped-site picture. In other terms, your hamiltonian is \begin{align} H &= J \sum_{<i,j>} (\sigma^x_i \sigma^x_j + \sigma^y_i \sig...
- 06 May 2019, 13:52
- Forum: HowTos and FAQ for TeNPy
- Topic: add_coupling in SpinModel
- Replies: 4
- Views: 4622
Re: add_coupling in SpinModel
Writing this with Hermitian conjugates, I get: J_x S^x_i S^x_j + J_y S^y_i S^y_j = \left( \frac{J_x + J_y}{4} \right)(S^+_i S^-_j + (S^+_j S^-_i)^\dagger) + \left( \frac{J_x - J_y}{4} \right)(S^+_i S^+_j + (S^+_j S^+_i)^\dagger) Sorry, but I disagree. Using h.c. it reads: J_x S^x_i S^x_j + J_y S^y_...
- 03 May 2019, 14:54
- Forum: HowTos and FAQ for TeNPy
- Topic: How to get the data of NPC arrays
- Replies: 1
- Views: 2869
Re: How to get the data of NPC arrays
The _data attribute of an tenpy.linalg.np_conserved.Array is a list with individual blocks of the tensor. Even without charges, there can be subblocks defined. this is the case for an MPO to exploit the sparseness of an MPO - if you write the Matrix, there are usually lot's of zeros, e.g. in your ca...
- 29 Apr 2019, 16:14
- Forum: HowTos and FAQ for TeNPy
- Topic: Cython compilation error
- Replies: 5
- Views: 6922
- 29 Apr 2019, 13:54
- Forum: HowTos and FAQ for TeNPy
- Topic: Cython compilation error
- Replies: 5
- Views: 6922
Re: Cython compilation error
Did you do the
Or in other words, do you have a working C++ compiler?
sudo apt-get install build-essential
?Or in other words, do you have a working C++ compiler?
- 29 Apr 2019, 09:27
- Forum: HowTos and FAQ for TeNPy
- Topic: Cython compilation error
- Replies: 5
- Views: 6922
Re: Cython compilation error
This looks like a linking error. What OS are you using? Can you compile the first minimal example from http://docs.cython.org/en/latest/src/quickstart/build.html? Another minimal example with numpy: save this code as "a.pyx". cimport numpy as cnp import numpy as np cnp.import_array() def m...
- 23 Apr 2019, 08:47
- Forum: Implementations
- Topic: Triangular Lattice
- Replies: 4
- Views: 16725
Re: Triangular Lattice
Implemented
- 19 Apr 2019, 09:34
- Forum: HowTos and FAQ for TeNPy
- Topic: Memory saving options in dmrg
- Replies: 2
- Views: 3510
Re: Memory saving options in dmrg
unfortunately, this is currently not implemented in TeNPy :( What you need to do is to write a custom tenpy.networks.mpo.MPOEnvironment which stores the tensors to disk instead of keeping them in the _LP and _RP lists. It should suffice to overwrite the get_LP, get_RP, set_LP, set_RP , del_LP, del_R...
- 18 Apr 2019, 15:55
- Forum: HowTos and FAQ for TeNPy
- Topic: Interpenetrating Lattices
- Replies: 2
- Views: 3136
Re: Interpenetrating Lattices
Currently, there is nothing to directly support this in TeNPy. What you need to do is implement your own lattice (as a subclass of tenpy.models.lattice.Lattice ). Example: import numpy as np from tenpy.models import lattice from tenpy.networks import site class MyLattice(lattice.Lattice): def __init...
- 18 Apr 2019, 13:02
- Forum: Implementations
- Topic: Triangular Lattice
- Replies: 4
- Views: 16725
Re: Triangular Lattice
Agreed. The Triangular lattice is basically just a simple square lattice with one of the basis vectors rotated by 30 degrees towards the other. I'd suggest to use basis = np.array([[0.5 *np.sqrt(3), 0.5], # first basis vector [0., 1.]]) # second basis vector: y-direction If you quickly write down th...
- 17 Apr 2019, 14:21
- Forum: HowTos and FAQ for TeNPy
- Topic: Performing TEBD for NNN interactions
- Replies: 1
- Views: 2895
Re: Performing TEBD for NNN interactions
Currently, the swapping for TEBD is not supported, although it should not be too difficult to implement, following the way you have outlined. There are a few things to be careful about, though: You need to adjust the existing model code to get the exponentials of the NNN terms. avoid onsite terms ap...
- 17 Apr 2019, 13:43
- Forum: HowTos and FAQ for TeNPy
- Topic: Suggestions for computing entanglement eigenvectors
- Replies: 2
- Views: 3056
Re: Suggestions for computing entanglement eigenvectors
What exactly do you mean by computing the entanglement eigenvectors? The eigenvectors of which matrix? For a finite system, I could imagine to look at individual Schmidt vectors (=singular vectors) on the left or right of a given cut in the form of an MPS. You can obtain them by just the part of the...
- 17 Apr 2019, 13:35
- Forum: HowTos and FAQ for TeNPy
- Topic: correlation length and charge sector
- Replies: 1
- Views: 2622
Re: correlation length and charge sector
Good question, thanks for pointing that out. The dominant eigenvector with eigenvalue 1 should always be in 0 charge sector: in canonical form the dominant eigenvector is just the identity, which has no charge. But I agree that it is not clear a priori (at least not to me) in which sector the next t...
- 28 Mar 2019, 11:07
- Forum: HowTos and FAQ for TeNPy
- Topic: TF Ising Magnetization issues
- Replies: 2
- Views: 4127
Re: TF Ising Magnetization issues
Short answer : Try measuring correlation functions, or expectation values of |M| or M^2 instead of M=\sum_i X_i ;) Reason : You try to observe spontaneous symmetry breaking. By definition, spontaneous symmetry meaking means that you have a degenerate ground state (in the thermodynamic limit): the s...
- 22 Mar 2019, 10:02
- Forum: HowTos and FAQ for TeNPy
- Topic: How to implement boundary pinning field in iDMRG appropriately?
- Replies: 2
- Views: 3554
Re: How to implement boundary pinning field in iDMRG appropriately?
In iDMRG, the iMPS unit cell is the central part of a growing environment on the left and right. The idea of the Engine.init_env() is to re-use the environment (and state) from a previous run. If the state has a sufficiently large correlation length, the environmnet "pins" DMRG to find the...
- 14 Mar 2019, 15:10
- Forum: Other News
- Topic: Serious bug in models
- Replies: 0
- Views: 53846
Serious bug in models
Another serious bug, this time in the models.
The problem is/was that adding the hermitian conjugate with was not done correctly.
Further details at issue #23.
If you have implemented your own model, check that you do it correctly in your case
The problem is/was that adding the hermitian conjugate with was not done correctly.
Further details at issue #23.
If you have implemented your own model, check that you do it correctly in your case
- 13 Mar 2019, 13:54
- Forum: Other News
- Topic: Serious bug in npc.inner
- Replies: 0
- Views: 19238
Serious bug in npc.inner
I found a serious bug in npc.inner . This bug could result in wrong expecation values and Lanczos/DMRG giving completely wrong results. Luckily, the bug was only on the github master branch for two weeks (since March 02), so I hope it didn't cause too many problems yet. In case you did a "git p...