Add qml.generator(op) function
#2256
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Co-authored-by: Maria Schuld <mariaschuld@gmail.com>
…to matrix-function
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josh146
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qml.generator(op) functionqml.generator(op) function
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@@ Coverage Diff @@
## master #2256 +/- ##
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+ Coverage 99.28% 99.31% +0.02%
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Files 236 237 +1
Lines 18869 18899 +30
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+ Hits 18734 18769 +35
+ Misses 135 130 -5
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| @@ -63,8 +63,7 @@ def get_spectrum(op, decimals): | |||
| Returns: | |||
| set[float]: non-negative frequencies contributed by this input-encoding gate | |||
| """ | |||
| matrix, coeff = get_generator(op, return_matrix=True) | |||
| matrix = coeff * matrix | |||
| matrix = qml.matrix(qml.generator(op, format="observable")) | |||
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This could have been done in #2182 already, but now that we're touching this code, we could simply use parameter_frequencies instead of this whole utility function? Might be a separate PR, though (maybe together with Rotosolve using parameter_frequencies, grouping it into an "application" PR).
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@dwierichs which would you prefer, doing it here, or doing it in a separate PR?
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I guess a separate one that uses parameter_frequencies where applicable is more clean? :)
| op = qml.Rot(0.1, 0.2, 0.3, wires=0) | ||
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| class CustomOp(qml.operation.Operation): | ||
| num_wires = 1 | ||
| num_params = 1 | ||
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| op = CustomOp(0.5, wires=0) |
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Out of curiousity: Why was this change required? :)
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@cvjjm suggested (very wisely) to move the num_params validation before getting the generator. So this test started raising 'Generator only supports single param operations' instead!
I couldn't think of another gate that would fit the test, and probably better practise to have test data designed for the test.
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Thanks for the explanation :)
Co-authored-by: David Wierichs <davidwierichs@gmail.com>
Co-authored-by: Maria Schuld <mariaschuld@gmail.com>
| with warnings.catch_warnings(): | ||
| warnings.filterwarnings( | ||
| action="ignore", message=r".+ eigenvalues will be computed numerically\." | ||
| ) | ||
| eigvals = qml.eigvals(qml.generator(self, format="observable")) | ||
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| if isinstance(gen, qml.SparseHamiltonian): | ||
| mat = gen.sparse_matrix().toarray() | ||
| eigvals = tuple(np.round(np.linalg.eigvalsh(mat), 8)) | ||
| return qml.gradients.eigvals_to_frequencies(eigvals) | ||
| eigvals = tuple(np.round(eigvals, 8)) | ||
| return qml.gradients.eigvals_to_frequencies(eigvals) |
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@dwierichs I made the change here because I realized the old version was simply duplicating qml.eigvals(); this makes the method cleaner, and less likely to break in the future.
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Oh great, this does look very nice :)
Context:
Currently, to get the generator of an operator, you must do
op.generator().However, there are many downsides to this:
op.generator()is overwritten by each operator, and thus does not take into account behaviour like operator inversesOperators can return arbitrary operators as generators. Until this is standardized, we need to consider Hamiltonians and matrices separately!
If the generator is a Pauli word, it is sometimes nice to be able to extract the 'prefactor'.
Currently,
qml.utils.get_generator()is available which is a temporary function to address the above.Description of the Change:
Adds
qml.generator(), which generalizes the temporaryqml.utils.get_generator()Remove
qml.utils.get_generator().Generalize
qml.generator()to return generators in various different formats:"prefactor", as per the old system"observable", as per the operator defines"hamiltonian", always return a Hamiltonian.Benefits: As above.
Possible Drawbacks: Not a drawback per se, but this function will become a lot simpler once the operator subclasses are merged.
Related GitHub Issues: n/a