<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Anastasios Giovanidis | LIP6 - Équipe QI</title><link>https://qi.lip6.fr/fr/people/anastasios-giovanidis/</link><atom:link href="https://qi.lip6.fr/fr/people/anastasios-giovanidis/index.xml" rel="self" type="application/rss+xml"/><description>Anastasios Giovanidis</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>fr</language><copyright>© 2022 LIP6 Quantum Information Team</copyright><lastBuildDate>Mon, 01 Jan 2024 00:00:00 +0000</lastBuildDate><image><url>https://qi.lip6.fr/media/icon_hudf2fdaa51677944daa4f50609104ef9a_13950_512x512_fill_lanczos_center_3.png</url><title>Anastasios Giovanidis</title><link>https://qi.lip6.fr/fr/people/anastasios-giovanidis/</link></image><item><title>A Linear Algebraic Framework for Dynamic Scheduling Over Memory-Equipped Quantum Networks</title><link>https://qi.lip6.fr/fr/publication/4165718-a-linear-algebraic-framework-for-dynamic-scheduling-over-memory-equipped-quantum-networks/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://qi.lip6.fr/fr/publication/4165718-a-linear-algebraic-framework-for-dynamic-scheduling-over-memory-equipped-quantum-networks/</guid><description>&lt;p>Quantum Internetworking is a recent field that promises numerous interesting applications, many of which require the distribution of entanglement between arbitrary pairs of users. This work deals with the problem of scheduling in an arbitrary entanglement swapping quantum network - often called first generation quantum network - in its general topology, multicommodity, loss-aware formulation. We introduce a linear algebraic framework that exploits quantum memory through the creation of intermediate entangled links. The framework is then employed to mathematically derive a natural class of quadratic scheduling policies for quantum networks by applying Lyapunov Drift Minimization, a standard technique in classical network science. Moreover, an additional class of Max-Weight inspired policies is proposed and benchmarked, reducing significantly the computation cost, at the price of a slight performance degradation. The policies are compared in terms of information availability, localization and overall network performance through an ad-hoc simulator that admits user-provided network topologies and scheduling policies in order to showcase the potential application of the provided tools to quantum network design.&lt;/p></description></item><item><title>A Linear Algebraic Framework for Quantum Internet Dynamic Scheduling</title><link>https://qi.lip6.fr/fr/publication/3740551-a-linear-algebraic-framework-for-quantum-internet-dynamic-scheduling/</link><pubDate>Sun, 18 Sep 2022 00:00:00 +0000</pubDate><guid>https://qi.lip6.fr/fr/publication/3740551-a-linear-algebraic-framework-for-quantum-internet-dynamic-scheduling/</guid><description>&lt;p>Future quantum internet aims to enable quantum communication between arbitrary pairs of distant nodes through the sharing of end-to-end entanglement, a universal resource for many quantum applications. As in classical networks, quantum networks also have to resolve problems related to routing and satisfaction of service at a sufficient rate. We deal here with the problem of scheduling when multiple commodities must be served through a quantum network based on first generation quantum repeaters, or quantum switches. To this end, we introduce a novel discrete-time algebraic model for arbitrary network topology, including transmission and memory losses, and adapted to dynamic scheduling decisions. Our algebraic model allows the scheduler to use the storage of temporary intermediate links to optimize the performance, depending on the information availability, ranging from full global information for a centralized scheduler to partial local information for a distributed one. As an illustrative example, we compare a simple greedy scheduling policy with several Max-Weight inspired scheduling policies and illustrate the resulting achievable rate regions for two competing pairs of clients through a network.&lt;/p></description></item></channel></rss>