netket.hilbert.DoubledHilbert¶
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class
netket.hilbert.DoubledHilbert(hilb)[source]¶ Bases:
netket.hilbert.doubled_hilbert.DoubledHilbertSuperoperatorial hilbert space for states living in the tensorised state \(\hat{H}\otimes \hat{H}\), encoded according to Choi’s isomorphism.
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__init__(hilb)[source]¶ Superoperatorial hilbert space for states living in the tensorised state \(\hat{H}\otimes \hat{H}\), encoded according to Choi’s isomorphism.
- Parameters
hilb (
AbstractHilbert) – 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
- Methods
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all_states(out=None)¶ Returns all valid states of the Hilbert space.
Throws an exception if the space is not indexable.
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numbers_to_states(numbers, out=None)¶ Returns the quantum numbers corresponding to the n-th basis state for input n. n is an array of integer indices such that
numbers[k]=Index(states[k]). Throws an exception iff the space is not indexable.
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ptrace(sites)¶ Returns the hilbert space without the selected sites.
Not all hilbert spaces support this operation.
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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.]]
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states()¶ Returns an iterator over all valid configurations of the Hilbert space. Throws an exception iff the space is not indexable. Iterating over all states with this method is typically inefficient, and
`all_states`should be prefered.
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states_to_numbers(states, out=None)¶ Returns the basis state number corresponding to given quantum states. The states are given in a batch, such that states[k] has shape (hilbert.size). Throws an exception iff the space is not indexable.
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