dq.random.ket

ket(
    key: PRNGKeyArray, dims: int | tuple[int, ...], *, batch: int | tuple[int, ...] = ()
) -> QArray

Returns a random ket with unit norm.

Parameters:

• key –

  A PRNG key used as the random key.

• dims –

  Hilbert space dimension of each subsystem.

• batch –

  Batch shape of the returned qarray.

Returns:

• (qarray of shape (*batch, prod(dims), 1)) –

  Random ket.

Examples:

>>> key = jax.random.PRNGKey(42)

Random ket for an individual system:

>>> dq.random.ket(key, 2)
QArray: shape=(2, 1), dims=(2,), dtype=complex64, layout=dense
[[0.563+0.107j]
 [0.027+0.819j]]

Batched random kets for an individual system:

>>> dq.random.ket(key, 2, batch=3)
QArray: shape=(3, 2, 1), dims=(2,), dtype=complex64, layout=dense
[[[ 0.563+0.107j]
  [ 0.027+0.819j]]

 [[-0.141+0.66j ]
  [-0.731-0.101j]]

 [[-0.489+0.465j]
  [-0.107+0.73j ]]]

Random ket for a composite system:

>>> dq.random.ket(key, (2, 3))
QArray: shape=(6, 1), dims=(2, 3), dtype=complex64, layout=dense
[[ 0.18 +0.034j]
 [ 0.009+0.262j]
 [-0.091+0.425j]
 [-0.471-0.065j]
 [-0.339+0.323j]
 [-0.074+0.508j]]

Batched random kets for a composite system:

>>> dq.random.ket(key, (2, 3), batch=(4, 5, 6, 7)).shape
(4, 5, 6, 7, 6, 1)