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in sample_rand_circuits_for_heavy_out, we loop over bitstrings with a python for loop, converting each bitstring to a number with a python function, and then count those that belong to heavy_outputs.
There's probably a clever numpy vectorized way of doing this that's much faster
The text was updated successfully, but these errors were encountered:
mpharrigan
changed the title
Vectorize categorization of output as heaving in quantum volume
Vectorize categorization of output as heavy in quantum volume
Feb 8, 2019
in
sample_rand_circuits_for_heavy_out
, we loop over bitstrings with a python for loop, converting each bitstring to a number with a python function, and then count those that belong toheavy_outputs
.There's probably a clever numpy vectorized way of doing this that's much faster
cc https://github.com/rigetti/forest-benchmarking/pull/15/files#r251163544
The text was updated successfully, but these errors were encountered: