SpinHalfFermionSite
full name: tenpy.networks.site.SpinHalfFermionSite
parent module:
tenpy.networks.sitetype: class
Inheritance Diagram

Methods
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Add one on-site operators. |
Change the charges of the site (in place). |
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Convert charge values to Jordan-Wigner parity. |
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Load instance from a HDF5 file. |
Return the hermitian conjugate of a given operator. |
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Return operator of given name. |
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Multiply operator names together. |
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Multiply local operators (possibly given by their names) together. |
Whether an (composite) onsite operator is fermionic and needs a Jordan-Wigner string. |
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Remove an added operator. |
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Rename an added operator. |
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Export self into a HDF5 file. |
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Sort the |
Return index of a basis state from its label. |
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Same as |
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Sanity check, raises ValueErrors, if something is wrong. |
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Check whether 'name' labels a valid onsite-operator. |
Class Attributes and Properties
Dimension of the local Hilbert space. |
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Dictionary of on-site operators for iteration. |
- class tenpy.networks.site.SpinHalfFermionSite(cons_N='N', cons_Sz='Sz', filling=1.0)[source]
Bases:
SiteCreate a
Sitefor spinful (spin-1/2) fermions.- Local states are:
empty(vacuum),up(one spin-up electron),down(one spin-down electron), andfull(both electrons)
Local operators can be built from creation operators.
Warning
Using the Jordan-Wigner string (
JW) in the correct way is crucial to get correct results, otherwise you just describe hardcore bosons!operator
description
IdIdentity \(\mathbb{1}\)
JWSign for the Jordan-Wigner string \((-1)^{n_{\uparrow}+n_{\downarrow}}\)
JWuPartial sign for the Jordan-Wigner string \((-1)^{n_{\uparrow}}\)
JWdPartial sign for the Jordan-Wigner string \((-1)^{n_{\downarrow}}\)
CuAnnihilation operator spin-up \(c_{\uparrow}\) (up to ‘JW’-string on sites left of it).
CduCreation operator spin-up \(c^\dagger_{\uparrow}\) (up to ‘JW’-string on sites left of it).
CdAnnihilation operator spin-down \(c_{\downarrow}\) (up to ‘JW’-string on sites left of it). Includes
JWusuch that it anti-commutes onsite withCu, Cdu.CddCreation operator spin-down \(c^\dagger_{\downarrow}\) (up to ‘JW’-string on sites left of it). Includes
JWusuch that it anti-commutes onsite withCu, Cdu.NuNumber operator \(n_{\uparrow}= c^\dagger_{\uparrow} c_{\uparrow}\)
NdNumber operator \(n_{\downarrow}= c^\dagger_{\downarrow} c_{\downarrow}\)
NuNdDotted number operators \(n_{\uparrow} n_{\downarrow}\)
NtotTotal number operator \(n_t= n_{\uparrow} + n_{\downarrow}\)
dNTotal number operator compared to the filling \(\Delta n = n_t-filling\)
Sx, Sy, SzSpin operators \(S^{x,y,z}\), in particular \(S^z = \frac{1}{2}( n_\uparrow - n_\downarrow )\)
Sp, SmSpin flips \(S^{\pm} = S^{x} \pm i S^{y}\), e.g. \(S^{+} = c^\dagger_\uparrow c_\downarrow\)
The spin operators are defined as \(S^\gamma = (c^\dagger_{\uparrow}, c^\dagger_{\downarrow}) \sigma^\gamma (c_{\uparrow}, c_{\downarrow})^T\), where \(\sigma^\gamma\) are spin-1/2 matrices (i.e. half the pauli matrices).
cons_N
cons_Sz
qmod
excluded onsite operators
'N''Sz'[1, 1]
Sx, Sy'N''parity'[1, 4]
–
'N'None[1]
–
'parity''Sz'[2, 1]
Sx, Sy'parity''parity'[2, 4]
–
'parity'None[2]
–
None'Sz'[1]
Sx, SyNone'parity'[4]
–
NoneNone[]
–
- Parameters:
cons_N (
'N' | 'parity' | None) – Whether particle number is conserved, c.f. table above.cons_Sz (
'Sz' | 'parity' | None) – Whether spin is conserved, c.f. table above.filling (float) – Average filling. Used to define
dN.
- cons_N
Whether particle number is conserved, c.f. table above.
- Type:
'N' | 'parity' | None
- cons_Sz
Whether spin is conserved, c.f. table above.
- Type:
'Sz' | 'parity' | None
- add_op(name, op, need_JW=False, hc=None, permute_dense=None)[source]
Add one on-site operators.
- Parameters:
name (str) – A valid python variable name, used to label the operator. The name under which op is added as attribute to self.
op (np.ndarray |
Array) – A matrix acting on the local hilbert space representing the local operator. Dense numpy arrays are automatically converted toArray. LegCharges have to be[leg, leg.conj()]. We set labels'p', 'p*'.need_JW (bool) – Whether the operator needs a Jordan-Wigner string. If
True, add name toneed_JW_string.hc (None | False | str) – The name for the hermitian conjugate operator, to be used for
hc_ops. By default (None), try to auto-determine it. IfFalse, disable adding entries tohc_ops.permute_dense (bool | None) – Flag to enable/disable permutations when converting op from numpy to np_conserved arrays. If True, the operator is permuted with
permto account for permutations induced by sorting charges; False disables the permutations. By default (None), the value ofused_sort_chargeis used.
- change_charge(new_leg_charge=None, permute=None)[source]
Change the charges of the site (in place).
- Parameters:
new_leg_charge (
LegCharge| None) – The new charges to be used. IfNone, use trivial charges.permute (ndarray | None) – The permutation applied to the physical leg, which also gets used to adjust
state_labelsandperm. If you sorted the previous leg withperm_qind, new_leg_charge = leg.sort(), useold_leg.perm_flat_from_perm_qind(perm_qind). Ignored ifNone.
- Return type:
The modified
self.
- charge_to_JW_signs(charges)[source]
Convert charge values to Jordan-Wigner parity.
Often, charge conservation contains the (parity of) the total fermion number. This information is enough to lift a Jordan-Wigner string applied on the left of a given bond to the virtual leg of an MPS: given the total parity number of fermions
parity[alpha] = N_fermions[alpha] % 2in each Schmidt state|alpha>, simply send|alpha> --> (-1)**parity[alpha] |alpha>. Given the charges values of the Schmidt states|alpha>, this function returns the corresponding(-1)**parityJordan-Wigner signs.- Parameters:
charges (2D or 1D array) – Charge values, last dimension is len
chinfo.qnumber. We choose the convention that these charge values correspond to an “incoming” leg withqconj=+1.- Returns:
Should only have values +1 or -1.
- Return type:
JW_signs
- property dim
Dimension of the local Hilbert space.
- classmethod from_hdf5(hdf5_loader, h5gr, subpath)[source]
Load instance from a HDF5 file.
This method reconstructs a class instance from the data saved with
save_hdf5().- Parameters:
hdf5_loader (
Hdf5Loader) – Instance of the loading engine.h5gr (
Group) – HDF5 group which is represent the object to be constructed.subpath (str) – The name of h5gr with a
'/'in the end.
- Returns:
obj – Newly generated class instance containing the required data.
- Return type:
cls
- get_op(name)[source]
Return operator of given name.
- Parameters:
name (str) – The name of the operator to be returned. In case of multiple operator names separated by whitespace, we multiply them together to a single on-site operator (with the one on the right acting first).
- Returns:
op – The operator given by name, with labels
'p', 'p*'. If name already was an npc Array, it’s directly returned.- Return type:
- multiply_op_names(names)[source]
Multiply operator names together.
Join the operator names in names such that get_op returns the product of the corresponding operators.
- multiply_operators(operators)[source]
Multiply local operators (possibly given by their names) together.
- Parameters:
operators (list of {str |
Array}) – List of valid operator names (to be translated withget_op()) or directly on-site operators in the form of npc arrays with'p', 'p*'label. The operators are multiplied left-to-right.- Returns:
combined_operator – The product of the given operators in a left-to-right multiplication following the usual mathematical convention. For example, if
operators=['Sz', 'Sp', 'Sx'], the final operator is equivalent tosite.get_op('Sz Sp Sx'), with the'Sx'operator acting first on any physical state.- Return type:
- property onsite_ops
Dictionary of on-site operators for iteration.
Single operators are accessible as attributes.
- op_needs_JW(name)[source]
Whether an (composite) onsite operator is fermionic and needs a Jordan-Wigner string.
- remove_op(name)[source]
Remove an added operator.
- Parameters:
name (str) – The name of the operator to be removed.
- save_hdf5(hdf5_saver, h5gr, subpath)[source]
Export self into a HDF5 file.
This method saves all the data it needs to reconstruct self with
from_hdf5().This implementation saves the content of
__dict__withsave_dict_content(), storing the format under the attribute'format'.
- sort_charge(bunch=True)[source]
Sort the
legcharges (in place).- Parameters:
bunch (bool) – Whether to also group equal charges into larger blocks (usually a good idea).
- Returns:
perm – The permutation
- Return type:
1D ndarray
- state_indices(labels)[source]
Same as
state_index(), but for multiple labels.