netket.hilbert.ContinuousHilbert#

class netket.hilbert.ContinuousHilbert#

Bases: netket.hilbert.AbstractHilbert

Abstract class for the Hilbert space of particles in continuous space. This class defines the common interface that can be used to interact with particles defined in continuous space.

Inheritance
Inheritance diagram of netket.hilbert.ContinuousHilbert
__init__(domain, pbc)[source]#
Constructs new Particles given specifications

of the continuous space they are defined in.

Parameters
  • domain (Tuple[float, ...]) – Tuple indicating the maximum of the continuous quantum number(s) in the configurations. Each entry in the tuple corresponds to a different physical dimension. If np.inf is used an infinite box is considered and pbc=False is mandatory (because what are PBC if there are no boundaries?). If a finite value is given, a minimum value of zero is assumed for the quantum number(s). A particle in a 3D box of size L would take (L,L,L). A rotor model would take e.g. (2pi,).

  • pbc (Union[bool, Tuple[bool, ...]]) – Tuple or bool indicating whether to use periodic boundary conditions in a given physical dimension. If tuple it must have the same length as domain. If bool the same value is used for all the dimensions defined in domain.

Attributes
extent#

Spatial extension in each spatial dimension

Return type

Tuple[float, ...]

is_indexable#

Whether the space can be indexed with an integer

Return type

bool

pbc#

Whether or not to use periodic boundary conditions for each spatial dimension

Return type

Tuple[bool, ...]

size#

The number number of degrees of freedom in the basis of this Hilbert space.

Return type

int

Methods
ptrace(sites)#

Returns the hilbert space without the selected sites.

Not all hilbert spaces support this operation.

Parameters

sites (Union[int, Iterable]) – a site or list of sites to trace away

Return type

AbstractHilbert

Returns

The partially-traced hilbert space. The type of the resulting hilbert space might be different from the starting one.

random_state(key=None, size=None, dtype=<class 'numpy.float32'>)#

Generates either a single or a batch of uniformly distributed random states. Runs as random_state(self, key, size=None, dtype=np.float32) by default.

Parameters
  • key – rng state from a jax-style functional generator.

  • size (Optional[int]) – If provided, returns a batch of configurations of the form (size, N) if size is an integer or (*size, N) if it is a tuple and where \(N\) is the Hilbert space size. By default, a single random configuration with shape (#,) is returned.

  • dtype – DType of the resulting vector.

Return type

ndarray

Returns

A state or batch of states sampled from the uniform distribution on the hilbert space.

Example

>>> import netket, jax
>>> hi = netket.hilbert.Qubit(N=2)
>>> k1, k2 = jax.random.split(jax.random.PRNGKey(1))
>>> print(hi.random_state(key=k1))
[1. 0.]
>>> print(hi.random_state(key=k2, size=2))
[[0. 0.]
 [0. 1.]]