White Paper on Quantum Internet Computer Science Research Challenges

TL;DR

This work identifies critical challenges in designing quantum network control architectures for near-term quantum Internet deployments, focusing on a generate-when-request model compatible with end-node OS such as QNodeOS. It analyzes a central controller-based architecture, demonstrates proof-of-concept results, and highlights gaps in admission control, scheduling speed, latency management, and governance, proposing directions for robust protocols and capability management. The findings show high success under moderate load but reveal performance degradation under heavier loads, underscoring the need for faster scheduling, reliable admission control, and clear policies for node joining and service agreements. Collectively, the paper provides a roadmap for developing practical quantum network control protocols and architectures to enable reliable end-to-end entanglement delivery in the near term.

Abstract

The aim of a quantum network is to enable the generation of end-to-end entangled links between end nodes of the network, so that they can execute quantum network applications. To facilitate this, it is desirable to have robust control of the network in order to be able to provide a reliable service to the end nodes. In recent work arXiv:2503.12582, we proposed a modular control architecture for a generate-when-request type network. This control architecture enables quantum network applications to be executed on end nodes running a modern operating system such as QNodeOS arXiv:2407.18306. In that work, we performed an evaluation of our architecture based on a proof-of-concept implementation. In the course of performing this evaluation, we discovered many outstanding questions and challenges. These relate not only to implementing our specific control architecture, but also to the design of any quantum network control architecture. Here, we describe some outstanding questions and challenges, discuss possible solutions, and identify where existing protocols require adaptation or new protocols must be designed.

Figures (3)

• Figure 1: Flow of information through the architecture proposed in journal-arx. The processes of 'Network Capability Update' and 'Capability Negotiation' allow the nodes to gather enough information to be able to submit a unified demand. These demands are then used to construct a central network schedule, which in turn is used when the operating systems of nodes construct their local schedules. Reproduced from journal-arx.
• Figure 2: Example of a star-topology network with 6 nodes. The outer circles represent the end nodes and the central hexagon a central junction node. The orange dots represent communication qubits and the black dots represent memory qubits. The central node is capable of creating an entangled link with each of the end nodes and performing entanglement swaps to create end-to-end links between pairs of end nodes. Reproduced from journal-arx.
• Figure 3: Results from simulations for client-server CKA on a six-node star network. (a) Proportion of initiated sessions which obtained minimal service from the network. (b) The average time a demand spent in the demand queue. The shaded region represents $\pm1\sigma$, where $\sigma$ is the standard deviation. The red dotted line represents the expected value of $t_{\text{queue}}$ for a single pair of end nodes submitting demands. The total simulated time was 360 days. Reproduced from journal-arx.