QuasiDistribution

class QuasiDistribution(data, shots=None)

Bases: dict

A dict-like class for representing qasi-probabilities.

Builds a quasiprobability distribution object.

Parameters

• data (dict) –

  Input quasiprobability data. Where the keys represent a measured classical value and the value is a float for the quasiprobability of that result. The keys can be one of several formats:

  • A hexadecimal string of the form "0x4a"

  • A bit string e.g. '0b1011' or "01011"

  • An integer

• shots (int) – Number of shots the distribution was derived from.

Raises

• TypeError – If the input keys are not a string or int

• ValueError – If the string format of the keys is incorrect

Methods

binary_probabilities	Build a quasi-probabilities dictionary with binary string keys
clear
copy
fromkeys	Create a new dictionary with keys from iterable and values set to value.
get	Return the value for key if key is in the dictionary, else default.
hex_probabilities	Build a quasi-probabilities dictionary with hexadecimal string keys
items
keys
nearest_probability_distribution	Takes a quasiprobability distribution and maps it to the closest probability distribution as defined by the L2-norm.
pop	If key is not found, d is returned if given, otherwise KeyError is raised
popitem	2-tuple; but raise KeyError if D is empty.
setdefault	Insert key with a value of default if key is not in the dictionary.
update	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values