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George Kanellos

Publications and source records attributed to George Kanellos.

6 recordsLinked to original sources

Phase noise characterisation of a 2-km Hollow-Core Nested Antiresonant Nodeless Fibre for Twin-Field Quantum Key Distribution

The performance of quantum key distribution (QKD) is heavily dependent on the physical properties of the channel over which it is executed. Propagation losses and perturbations in the encoded photons' degrees of freedom, such as polarisation or phase, limit both the QKD range and key rate. The maintenance of phase coherence over optical fibres has lately received considerable attention as it enables QKD over long distances, e.g., through phase-based protocols like Twin-Field (TF) QKD. While optical single mode fibres (SMFs) are the current standard type of fibre, recent hollow core fibres (HCFs) could become a superior alternative in the future. Whereas the co-existence of quantum and classical signals in HCF has already been demonstrated, the phase noise resilience required for phase-based QKD protocols is yet to be established. This work explores the behaviour of HCF with respect to phase noise for the purpose of TF-QKD-like protocols. To achieve this, two experiments are performed. The first, is a set of concurrent measurements on 2 km of HCF and SMF in a double asymmetric Mach-Zehnder interferometer configuration. The second, uses a TF-QKD interferometer consisting of HCF and SMF channels. These initial results indicate that HCF is suitable for use in TF-QKD and other phase-based QKD protocols.

quant-ph

First Demonstration of 25λ x 10 Gb/s C+L Band Classical / DV-QKD Co-Existence Over Single Bidirectional Fiber Link

As quantum key distribution has reached the maturity level for practical deployment, questions about the co-integration with existing classical communication systems are of utmost importance. To this end we demonstrate how the co-propagation of classical and quantum signals can benefit from the development of novel hollow-core fibers. We demonstrate a secure key rate of 330 bit/s for a quantum channel at 1538 nm in the presence of 25 x 10 Gb/s classical channels, transmitted at an aggregated launch power of 12 dBm, spanning over the C+L-band in the same hollow-core fiber link. Furthermore, we show the co-integration of the classical key-distillation channel onto this fiber link, turning it into a bidirectional fiber link and thereby mitigating the need for multiple fibers. We believe this to be an important step towards the deployment and integration of hollow-core fibers together with DV-QKD for the inherently secure telecom network of the future.

quant-ph

Introducing explainable supervised machine learning into interactive feedback loops for statistical production system

Statistical production systems cover multiple steps from the collection, aggregation, and integration of data to tasks like data quality assurance and dissemination. While the context of data quality assurance is one of the most promising fields for applying machine learning, the lack of curated and labeled training data is often a limiting factor. The statistical production system for the Centralised Securities Database features an interactive feedback loop between data collected by the European Central Bank and data quality assurance performed by data quality managers at National Central Banks. The quality assurance feedback loop is based on a set of rule-based checks for raising exceptions, upon which the user either confirms the data or corrects an actual error. In this paper we use the information received from this feedback loop to optimize the exceptions presented to the National Central Banks thereby improving the quality of exceptions generated and the time consumed on the system by the users authenticating those exceptions. For this approach we make use of explainable supervised machine learning to (a) identify the types of exceptions and (b) to prioritize which exceptions are more likely to require an intervention or correction by the NCBs. Furthermore, we provide an explainable AI taxonomy aiming to identify the different explainable AI needs that arose during the project.

cs.LG

End-to-end Quantum Secured Inter-Domain 5G Service Orchestration Over Dynamically Switched Flex-Grid Optical Networks Enabled by a q-ROADM

Dynamic and flexible optical networking enabled by NFV and SDN are the key technology enablers for supporting the dynamicity and bandwidth requirements of emerging 5G network services. To achieve the objective of 5G, Network Services (NSes) must be often deployed transparently over multiple administrative and technological domains. Such case often presents security risks since a typical NS may comprise a chain of network functions, each executed in different remote locations, and tampering within the network infrastructure may compromise their communication. To avoid such threats, QKD has been identified and proposed as a future-proof method immune to any algorithmic cryptanalysis based on quantum-physics mechanisms. The maturity of QKD has enabled the R&D of quantum networks coexisting with optical networks using telecom equipment. This makes the QKD a suitable candidate for the security of distributed and virtualised network services. In this paper, for the first time, we propose a dynamic quantum-secured optical network for supporting network services that are dynamically created by chaining VNF over multiple network domains. This work includes a new quantum-ROADM, extensions to SDN-enabled optical control plane, and extensions to NFV orchestration to achieve quantum-aware, on-demand chaining of VNFs. The experimental results verify the capability of routing quantum and classical data channels both individually and dynamically over shared fibre links. Moreover, quantum secured chaining of VNFs in 5G networks is experimentally demonstrated via interconnecting four autonomous 5G islands simultaneously through the q-ROADM with eight optical channels using the 5GUK Exchange orchestration platform. The experimental scenarios and results confirm the benefit of the proposed data plane architecture and control/management plane framework.

cs.NI