Source code for netket.hilbert.doubled_hilbert

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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#    http://www.apache.org/licenses/LICENSE-2.0
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from typing import List, Optional

import numpy as np

from netket.utils.dispatch import parametric

from .abstract_hilbert import AbstractHilbert
from .discrete_hilbert import DiscreteHilbert


@parametric
class DoubledHilbert(DiscreteHilbert):
    r"""
    Superoperatorial hilbert space for states living in the tensorised state
    :math:`\hat{H}\otimes \hat{H}`, encoded according to Choi's isomorphism.
    """

[docs] def __init__(self, hilb: AbstractHilbert): r""" Superoperatorial hilbert space for states living in the tensorised state :math:`\hat{H}\otimes \hat{H}`, encoded according to Choi's isomorphism. Args: hilb: the Hilbert space H. Examples: Simple superoperatorial hilbert space for few spins. >>> import netket as nk >>> g = nk.graph.Hypercube(length=5,n_dim=2,pbc=True) >>> hi = nk.hilbert.Spin(N=3, s=0.5) >>> hi2 = nk.hilbert.DoubledHilbert(hi) >>> print(hi2.size) 6 """ self.physical = hilb self._size = 2 * hilb.size super().__init__(shape=hilb.shape * 2)
@property def size(self): return self._size @property def shape(self): return self._shape @property def is_finite(self): return self.physical.is_finite @property def local_size(self): return self.physical.local_size @property def local_states(self): return self.physical.local_states def size_at_index(self, i: int) -> int: return self.physical.size_at_index( i if i < self.physical.size else i - self.physical.size ) def states_at_index(self, i: int) -> Optional[List[float]]: r"""A list of discrete local quantum numbers at the site i. If the local states are infinitely many, None is returned.""" return self.physical.states_at_index( i if i < self.physical.size else i - self.physical.size ) @property def size_physical(self): return self.physical.size @property def n_states(self): return self.physical.n_states**2 def _numbers_to_states(self, numbers, out): # !!! WARNING # This code assumes that states are stored in a MSB # (Most Significant Bit) format. # We assume that the rightmost-half indexes the LSBs # and the leftmost-half indexes the MSBs # HilbertIndex-generated states respect this, as they are: # 0 -> [0,0,0,0] # 1 -> [0,0,0,1] # 2 -> [0,0,1,0] # etc... n = self.physical.size dim = self.physical.n_states left, right = np.divmod(numbers, dim) self.physical.numbers_to_states(left, out=out[:, 0:n]) self.physical.numbers_to_states(right, out=out[:, n : 2 * n]) return out def _states_to_numbers(self, states, out): # !!! WARNING # See note above in numbers_to_states n = self.physical.size dim = self.physical.n_states self.physical._states_to_numbers(states[:, 0:n], out=out) _out_l = out * dim self.physical._states_to_numbers(states[:, n : 2 * n], out=out) out += _out_l return out def __repr__(self): return "DoubledHilbert({})".format(self.physical) @property def _attrs(self): return (self.physical,)