estimator.prob

Description

Functions

amplify(target_success_probability, ...[, ...])	Return the number of trials needed to amplify current success_probability to target_success_probability
amplify_sigma(target_advantage, sigma, q)	Amplify distinguishing advantage for a given σ and q
babai(r, norm)	Babai probability following [EPRINT:Wun16].
conditional_chi_squared(d1, d2, lt, l2)	Probability that a gaussian sample (var=1) of dim d1+d2 has length at most lt knowing that the d2 first coordinates have length at most l2
drop(n, h, k[, fail, rotations])	Probability that k randomly sampled components have fail non-zero components amongst them.
gaussian_cdf(mu, sigma, t)	Compute the cdf of a continuous gaussian random variable with mean mu and standard deviation sigma (i.e. computes Pr(X <= t), where X is a gaussian random variable).
mitm_babai_probability(r, stddev, q[, fast])	Compute the "e-admissibility" probability associated to the mitm step, according to [EPRINT:SonChe19]