Socio-cognitive correlates of primary school children's deceptive behavior toward peers in competitive settings.

Competing for limited resources with peers is common among children from an early age, illustrating their propensity to use deceptive strategies to win. We focused on how primary school-age (6-8 years old) children's strategic deception toward peers is associated with their socio-cognitive development (theory of mind and executive functions). In a novel computerized competitive hide-and-seek game, we manipulated the peer opponents' familiarity (familiar vs. unfamiliar) and actions (following vs. not following children's indications), as well as the stimuli likability (liked vs. disliked cards). Our findings demonstrated that children deceived the familiar opponent less than the unfamiliar one, indicating their determination to preserve positive peer interactions. We showed that theory of mind and executive functions significantly predicted children's willingness to deceive. Notably, second-order false belief understanding and visuospatial working memory positively predicted children's use of truths to deceive, whereas inhibitory control and cognitive flexibility efficacy scores were negatively related to their deceptive performance when using the same strategy. Implications for children's competitive behavior toward peers involving lie-telling are discussed.

Distribution of controlled unitary quantum gates towards factoring large numbers on today's small-register devices.

Factoring a 2048-bit number using Shor's algorithm, when accounting for error correction, reportedly requires 400,000 qubits. However, it is well known that there is yet much time before we will have this many qubits in the same local system. This is why we propose a protocol for distributed quantum computation applicable to small register devices, specifically for the distribution of controlled unitary gates, the key element in the construction of every quantum computation algorithm. We leverage quantum sharing of partial results to obtain a parallel processing scheme, allowing for the first time the quantum distribution of very large gates with thousands of inputs using only small register devices with tens of qubits. In this way, we improve all previous controlled unitary gate distribution approaches, obtaining surprising results. The impact is quantified for recent milestone hardware realizations of quantum processors.

Tight and Scalable Side-Channel Attack Evaluations through Asymptotically Optimal Massey-like Inequalities on Guessing Entropy.

The bounds presented at CHES 2017 based on Massey's guessing entropy represent the most scalable side-channel security evaluation method to date. In this paper, we present an improvement of this method, by determining the asymptotically optimal Massey-like inequality and then further refining it for finite support distributions. The impact of these results is highlighted for side-channel attack evaluations, demonstrating the improvements over the CHES 2017 bounds.

Exploiting the Massey Gap.

In this paper, we find new refinements to the Massey inequality, which relates the Shannon and guessing entropies, introducing a new concept: the Massey gap. By shrinking the Massey gap, we improve all previous work without introducing any new parameters, providing closed-form strict refinements, as well as a numerical procedure improving them even further.