The goal of machine learning is to facilitate a computer to execute a specific task without
explicit instruction by an external party. Quantum foundations seek to explain the conceptual …

Despite the conceptual importance of contextuality in quantum mechanics, there is a hitherto
limited number of applications requiring contextuality but not entanglement. Here, we show …

Although'quantum contextuality'is one of the most fundamental non-classical feature, its
generic role in information processing and computation is an open quest. In this article, we …

The predictions of quantum theory resist generalised noncontextual explanations. In
addition to the foundational relevance of this fact, the particular extent to which quantum …

We develop a hypergraph-theoretic framework for Spekkens contextuality applied to Kochen-
Specker (KS) type scenarios that goes beyond the Cabello-Severini-Winter (CSW) …

In this paper, we present a protocol to obtain photonic circuits that can be used in the
implementation of contextuality tests on qutrit systems. The use of photonic integrated …

Quantum entanglement is an important resource for quantum information processing,
quantum communication, quantum computation and quantum sensing. Hence, several …

A comprehensive investigation of the entanglement characteristics is carried out on tripartite
spin-1/2 systems, examining prototypical tripartite states, the thermal Heisenberg model, and …

In quantum cryptography, secure randomness expansion involves using a short private
string of random bits to generate a longer one, even in the presence of an adversary who …

We consider a continuous-variable Clauser-Horne Bell-type inequality to study nonlocality in
four-mode continuous-variable systems, which goes beyond two-photon states and can be …