Generalized bent Boolean functions and strongly regular Cayley graphs

In this paper we define the (edge-weighted) Cayley graph associated to a generalized Boolean function, introduce a notion of strong regularity and give several of its properties. We show some connections between this concept and generalized bent functions (gbent), that is, functions with flat Walsh-Hadamard spectrum. In particular, we find a complete characterization of quartic gbent functions in terms of the strong regularity of their associated Cayley graph.Comment: 13 pages, 2 figure

Rayleigh quotients of Dillon's functions

The Walsh--Hadamard spectrum of a bent function uniquely determines a dual function. The dual of a bent function is also bent. A bent function that is equal to its dual is called a self-dual function. The Hamming distance between a bent function and its dual is related to its Rayleigh quotient. Carlet, Danielsen, Parker, and Sole studied Rayleigh quotients of bent functions in ${\mathcal PS}_{ap}$, and obtained an expression in terms of a character sum. We use another approach comprising of Desarguesian spreads to obtain the complete spectrum of Rayleigh quotients of bent functions in $\mathcal{PS}_{ap}$

The Good lower bound of Second-order nonlinearity of a class of Boolean function

In this paper we find the lower bound of second-order nonlinearity of Boolean function $f_{\lambda}(x) = Tr_{1}^{n}(\lambda x^{p})$ with $p = 2^{2r} + 2^{r} + 1$, $\lambda \in \mathbb{F}_{2^{r}}^{*}$ and $n = 5r$. It is also demonstrated that the lower bound obtained in this paper is much better than the lower bound obtained by Iwata-Kurosawa \cite{c14}, and Gangopadhyay et al. (Theorem 1, \cite{c12})

On construction of non-normal Boolean functions

Given two non-weakly $k$-normal Boolean functions on $n$ variables a method is proposed to construct a non-weakly $(k+1)$-normal Boolean function on $(n+2)$ variables

A New Class of Bent--Negabent Boolean Functions

In this paper we develop a technique of constructing bent--negabent Boolean functions by using complete mapping polynomials. Using this technique we demonstrate that for each $\ell \ge 2$ there exits bent--negabent functions on $n = 12\ell$ variables with algebraic degree $\frac{n}{4}+1 = 3\ell + 1$. It is also demonstrated that there exist bent--negabent functions on $8$ variables with algebraic degrees $2$, $3$ and $4$

On Kasami Bent Functions

It is proved that no non-quadratic Kasami bent is affine equivalent to Maiorana-MacFarland type bent functions

On lower bounds of second-order nonlinearities of cubic bent functions constructed by concatenating Gold functions

In this paper we consider cubic bent functions obtained by Leander and McGuire (J. Comb. Th. Series A, 116 (2009) 960-970) which are concatenations of quadratic Gold functions. A lower bound of second-order nonlinearities of these functions is obtained. This bound is compared with the lower bounds of second-order nonlinearities obtained for functions belonging to some other classes of functions which are recently studied

On lower bounds on second--order nonliearities of bent functions obtained by using Niho power functions

In this paper we find a lower bound of the second-order nonlinearities of Boolean bent functions of the form $f(x) = Tr_{1}^{n}(\alpha_{1}x^{d_{1}} + \alpha_{2}x^{d_{2}})$,where $d_1$ and $d_2$ are Niho exponents. A lower bound of the second-order nonlinearities of these Boolean functions can also be obtained by using a result proved by Li, Hu and Gao (eprint.iacr.org/2010 /009.pdf). It is demonstrated that for large values of $n$ the lower bound obtained in this paper are better than the lower bound obtained by Li, Hu and Gao

Generalized Boolean Functions and Quantum Circuits on IBM-Q

We explicitly derive a connection between quantum circuits utilising IBM's quantum gate set and multivariate quadratic polynomials over integers modulo 8. We demonstrate that the action of a quantum circuit over input qubits can be written as generalized Walsh-Hadamard transform. Here, we derive the polynomials corresponding to implementations of the Swap gate and Toffoli gate using IBM-Q gate set.Comment: 7 pages, 8 figures, Accepted to Publish in: 10th International Conference on Computing, Communication and Networking Technologies and IEEE Xplor

On Learning with LAD

The logical analysis of data, LAD, is a technique that yields two-class classifiers based on Boolean functions having disjunctive normal form (DNF) representation. Although LAD algorithms employ optimization techniques, the resulting binary classifiers or binary rules do not lead to overfitting. We propose a theoretical justification for the absence of overfitting by estimating the Vapnik-Chervonenkis dimension (VC dimension) for LAD models where hypothesis sets consist of DNFs with a small number of cubic monomials. We illustrate and confirm our observations empirically