Harnessing Quantum Resources in Network Communication and Their Thermodynamic Underpinnings

We are currently at the midst of Second Quantum Revolution, a transformative era harnessing various quantum resources for the efficient execution of communication and computational tasks previously unattainable through classical means.

During the recent past the point-to-point communication scenarios have seen extensive exploration and practical realization of quantum resource benefits across diverse quantum architectures.

Within the realm of network scenario, typical communication systems involve multiple distant parties seeking to exchange information.

In the present project, our primary objective is to delve into the advantageous applications of several quantum resources, including quantum superposition, quantum entanglement, quantum steering, and quantum nonlocal correlations, in the context of network communications.

Our focus is particularly directed at two broad channel categories in the network scenario: the Multiple Access Channel (MAC), featuring multiple senders and a single receiver, and the Broadcasting Channel (BC), comprising one sender and multiple receivers.

A fundamental goal lies in examining how distinct non-classical correlations, achieved from multipartite quantum systems, can enhance the effectiveness of the limited communication channels available to both senders and receivers.

In this endeavor, we intend to uncover a deeper connection between quantum information theory and quantum thermodynamics.

While the intricate link between these domains has been highlighted by the work of Szilard, Landauer, and Bennett, our aim is to explore this connection within the quantum realm to its broadest extent, with a specific focus on network communication scenarios.

In addition to introducing a novel avenue for quantifying and detecting quantum resources through experimentally measurable thermodynamic quantities, this undertaking also offers insights into why quantum theory holds a special status among mathematically allowed models.