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| case _: | ||
| raise NotImplementedError | ||
| assert isinstance(angle, float | int) | ||
| [jeff_angle] = self.add_op(jeff.const_float(angle * math.pi, 64)).outputs |
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TODO: Need to check if this radians conversion is correct
| params: list[float] = None, | ||
| params: list[JeffValue] = None, |
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Drive-by: Passing Python floats as params causes an error when encoding via capnproto. They should be jeff float values
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Thanks for working on this @mark-koch 🙏🏼 Sorry for probably being the stupid one here, but none of these benchmarks are structured benchmarks or am I missing something? |
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The original circuits are flat, but the MBQC conversion introduces measurements and classical branches conditioned on mid-circuit measurement outcomes. If you load the jeff files you should see measurements and branches |
Ah, I figured I must have been stupid. |
Here is my take on the MBQC benchmark set. I took a subset of the standard benchmark circuits from https://github.com/meamy/feynman and converted them into an MBQC pattern using
graphixwhich I then convert to jeff.I wasn't entirely sure about the directory structure. Is it ok to put the code to generate the benchmarks into the
_recipiesdirectory?