estimate_purity_err

forest.benchmarking.randomized_benchmarking.estimate_purity_err(dim: int, op_expect: numpy.ndarray, op_expect_var: numpy.ndarray, renorm=True)

Propagate the observed variance in operator expectation to an error estimate on the purity. This assumes that each operator expectation is independent.

Parameters:

• dim – dimension of the Hilbert space
• op_expect – array of estimated expectations of each operator being measured
• op_expect_var – array of estimated variance for each operator expectation
• renorm – flag that provides error for the renormalized purity

Returns:

purity given the operator expectations