Quantum algorithms to check Resiliency, Symmetry and Linearity of a Boolean function

In this paper, we present related quantum algorithms to check the order of resiliency, symmetry and linearity of a Boolean function that is available as a black-box (oracle). First we consider resiliency and show that the Deutsch-Jozsa algorithm can be immediately used for this purpose. We also point out how the quadratic improvement in query complexity can be obtained over the Deutsch-Jozsa algorithm for this purpose using the Grover\u27s technique. While the worst case quantum query complexity to check the resiliency order is exponential in the number of input variables of the Boolean function, we require polynomially many measurements only. We also describe a subset of $n$-variable Boolean functions for which the algorithm works in polynomially many steps, i.e., we can achieve an exponential speed-up over best known classical algorithms. A similar kind of approach can be exploited to check whether a Boolean function is symmetric (respectively linear) or not. Given a Boolean function as an oracle, it is important to devise certain algorithms to test whether it has a specific property or it is $\epsilon$-far from having that property. The efficiency of the algorithm is judged by the number of calls to the oracle so that one can decide, with high probability, between these two alternatives. We show that this can be achieved in $O(\epsilon^{-\frac{1}{2}})$ query complexity. This is obtained by showing that the problem of checking symmetry or linearity can be efficiently reduced to testing whether a Boolean function is constant

Attribute estimation and testing quasi-symmetry

A Boolean function is symmetric if it is invariant under all permutations of its arguments; it is quasi-symmetric if it is symmetric with respect to the arguments on which it actually depends. We present a test that accepts every quasi-symmetric function and, except with an error probability at most δ\u3e0, rejects every function that differs from every quasi-symmetric function on at least a fraction ε\u3e0 of the inputs. For a function of n arguments, the test probes the function at O((n/ε)log(n/δ)) inputs. Our quasi-symmetry test acquires information concerning the arguments on which the function actually depends. To do this, it employs a generalization of the property testing paradigm that we call attribute estimation. Like property testing, attribute estimation uses random sampling to obtain results that have only “one-sided” errors and that are close to accurate with high probability