cirq.SupportsApplyMixture
An object that can efficiently implement a mixture.
cirq.SupportsApplyMixture(
*args, **kwargs
)
Methods
_apply_mixture_
View source
_apply_mixture_(
args: cirq.ApplyMixtureArgs
) -> Union[np.ndarray, None, NotImplementedType]
Efficiently applies a mixture.
This method is given both the target tensor and workspace of the same
shape and dtype. The method then either performs inline modifications of
the target tensor and returns it, or writes its output into the
a workspace tensor and returns that. This signature makes it possible to
write specialized simulation methods that run without performing large
allocations, significantly increasing simulation performance.
Args |
args
|
A cirq.ApplyMixtureArgs object with the args.target_tensor
to operate on, an args.available_workspace buffer to use as
temporary workspace, and the args.axes of the tensor to target
with the unitary operation. Note that this method is permitted
(and in fact expected) to mutate args.target_tensor and
args.available_workspace .
|
Returns |
If the receiving object is not able to apply its unitary effect,
None or NotImplemented should be returned.
If the receiving object is able to work inline, it should directly
mutate args.target_tensor and then return args.target_tensor .
The caller will understand this to mean that the result is in
args.target_tensor .
If the receiving object is unable to work inline, it can write its
output over args.available_buffer and then return
args.available_buffer . The caller will understand this to mean
that the result is in args.available_buffer (and so what was
args.available_buffer will become args.target_tensor in the next
call, and vice versa).
The receiving object is also permitted to allocate a new
numpy.ndarray and return that as its result.
|
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Last updated 2024-06-27 UTC.
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