netket.hilbert.AbstractHilbert

class netket.hilbert.AbstractHilbert

Bases: ABC

Abstract class for NetKet hilbert objects.

This class defines the common interface used to interact with Hilbert spaces.

An AbstractHilbert object identifies an Hilbert space and a computational basis on such hilbert space, such as the z-basis for spins on a lattice, or the position-basis for particles in a box.

Hilbert Spaces are generally immutable python objects that must be hashable in order to be used as static arguments to jax.jit functions.

Inheritance

Attributes

is_indexable

Whether the space can be indexed with an integer

size

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

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:

Array

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.]]