estimator.lwe_parameters.LWEParameters#

class estimator.lwe_parameters.LWEParameters(n: int, q: int, Xs: estimator.nd.NoiseDistribution, Xe: estimator.nd.NoiseDistribution, m: int = <MagicMock id='140185315134528'>, tag: typing.Optional[str] = None)[source]#

The parameters for a Learning With Errors problem instance.

__call__(**kwargs)#

Call self as a function.

Methods

__init__(n, q, Xs, Xe[, m, tag])

amplify_m(m)

Return a LWE instance parameters with m samples produced from the samples in this instance.

normalize()

EXAMPLES:

switch_modulus()

Apply modulus switching and return new instance.

updated(**kwds)

Return a new set of parameters updated according to kwds.

Attributes

m

the number of LWE samples allowed to an attacker, optionally sage.all.oo for allowing infinitely many samples.

tag

a name for the patameter set

n

the dimension of the LWE sample vector (Z/qZ)^n.

q

the modulus of the space Z/qZ of integers the LWE samples are in.

Xs

the distribution on Z/qZ from which the LWE secret is drawn

Xe

the distribution on Z/qZ from which the error term is drawn