Return a mixture of exact and sampled weights as appropriate #255
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garrison
added
quantum performance
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`math.nextafter` wasn't introduced until Python 3.9
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garrison
commented
Jun 22, 2023
circuit_knitting/cutting/qpd/qpd.py
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| Generate weights from the joint quasiprobability distribution. | ||
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| All weights above ``1 / num_samples`` will be returned exactly, while the | ||
| remaining weights will be sampled from. |
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| remaining weights will be sampled from. | |
| remaining weights will be generated by sampling from the low-probability elements of the distribution. |
I think something like this is a little more clear. What do you think?
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I rephrased this in 8830c94.
circuit_knitting/cutting/qpd/qpd.py
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| qpd_bases: The :class:`QPDBasis` objects from which to sample | ||
| num_samples: Number of random samples to generate | ||
| qpd_bases: The :class:`QPDBasis` objects from which to generate weights | ||
| num_samples: Maximum number of weights to generate |
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| num_samples: Maximum number of weights to generate | |
| num_samples: Number of times to sample from the quasiprobability distribution |
I see what you're getting at here, and it makes sense for the CX/CZ case, but I think the description of this arg is more informative if you make it a bit more general
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I also rephrased this a bit in 8830c94.
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caleb-johnson
previously approved these changes
Jul 10, 2023
docs/circuit_cutting/tutorials/02_gate_cutting_to_reduce_circuit_depth.ipynb
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Fixes #199
Remaining action items:
generate_qpd_weights