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A Link Layer Protocol for Quantum Networks. Axel Dahlberg, Matt Skrzypczyk , Tim Coopmans , Leon Wubben , Filip Rozpędek , Matteo Pompili , Arian Stolk , Przemysław Pawełczak , Robert Knegjens , Julio de Oliveira Filho, Ronald Hanson, Stephanie Wehner
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A Link Layer Protocol for Quantum Networks Axel Dahlberg, Matt Skrzypczyk, Tim Coopmans, Leon Wubben, Filip Rozpędek, Matteo Pompili, Arian Stolk, PrzemysławPawełczak, Robert Knegjens, Julio de Oliveira Filho, Ronald Hanson, Stephanie Wehner ACM SIGCOMM 2019 – Wednesday 08/21/2019
Joint work with Axel Dahlberg Tim Coopmans Leon Wubben Filip Rozpędek Przemysław Pawełczak Arian Stolk MatteoPompili Rob Knegjens Julio de Oliveira Filho Ronald Hanson Stephanie Wehner
Quantum Information Classical Quantum 1 0+1 0
Applications Quantum Key Distribution Bennett and Brassard. Theor. Comput. Sci. 560.12 (2014): 1984 Ekert. Physical review letters 67.6 (1991): 661. 1991 Clock Synchronization Gottesman, Jennewein, and Croke. Physical Review Letters 109.7 (2012) Secure Quantum Computing in the Cloud Fitzsimons and Kashefi. Physical Review A 96.1 (2017). 2017
Quantum Network Structure End Node End Node Bridge long distances End Node Repeater End Node Repeater Prepare/Measure Qubits Store/Manipulate Qubits End Node
Stages of Quantum Networks Functionality Quantum Computing Networks • Cryptography • Sensing and Metrology • Distributed Systems • Secure Quantum Cloud Computing Fault-Tolerant Few Qubit Networks Quantum Memory Networks Entanglement Distribution Networks Prepare and Measure Networks Trusted Repeater Networks Time Wehner, Elkouss, and Hanson. Science 362, 6412 (oct). 2018
Our Contribution • Functional allocation of quantum network stack • Systematic study of design considerations and use cases • First physical and link layer protocols • Performance evaluation and scheduling investigation
Related Work Entanglement generation experiments Hensen et al. Nature 526, 7575 (2015), 682-686. 2015 Hofmann et al. Science 337, 6090 (2012), 72-75. 2012 QKD networks Liu et al. ACM SIGCOMM Computer Communication Review. Vol. 43. No. 4. 2013 Yu et al. IEEE International Conference on Computer and Communications. IEEE, 2017 Network stack sketches Aparicio et al. Asian Internet Engineering Conference. ACM, 2011 Pirker and Dür. New Journal of Physics 21.3. 2019
Why a Quantum Network Stack is Different No copying! Short lifetime! Inherently connected!
Sending Qubits via Entanglement End node End node
Sending Qubits via Entanglement End node End node
Sending Qubits via Entanglement End node End node
Quantum Repeater… Entanglement Swapping End node End node Repeater
Quantum Repeater… Entanglement Swapping End node End node Repeater
Quantum Repeater… Entanglement Swapping End node End node Repeater
Example of Quantum Hardware • Nitrogen vacancy in diamond • Communication qubit • Storage qubits • Entanglement at 1.3 km 10 mm
Our Contribution • Functional allocation of quantum network stack • Systematic study of design considerations and use cases • First physical and link layer protocols • Performance evaluation and scheduling investigation
Quantum Network Stack Application Transport Network Link Physical
Quantum Network Stack Application Quantum Application Protocols Transport End-to-end Qubit Delivery Network Long-distance Entanglement Generation Link Entanglement Generation on a Link Physical Quantum Device Layer
Quantum Network Stack Application Quantum Application Protocols Transport End-to-end Qubit Delivery Network Long-distance Entanglement Generation Link Entanglement Generation on a Link Physical Quantum Device Layer
Our Contribution • Functional allocation of quantum network stack • Systematic study of design considerations and use cases • First physical and link layer protocols • Performance evaluation and scheduling investigation
Link Layer: Entanglement Generation Service CREATE OK, … OK, … QEGP QEGP
Performance Metrics • Quantum Metrics • Fidelity: quality of entanglement, rate of success trade-off • Standard Metrics • Latency: issuing request to getting a pair • Throughput: pairs/s • Fairness: difference in performance metrics between nodes
Use Cases • Application Use Cases • Measure directly: many pairs measured immediately • Create and keep: few pair(s) stored for processing • Network Layer Use Case • Create and keep: entanglement swapping with two pairs
Design Considerations • Noise due to attempts • Producing entanglement induces noise on storage qubits • (Kalb et al, Phys. Rev. A, 97. 2018) • Avoid triggering unless both nodes agree • Noise is time dependent • Avoid waiting once entanglement made • Prior discussion preferred • Quantum CRC for error detection difficult • Applications do not require perfect entanglement • Reduce complexity
Our Contribution • Functional allocation of quantum network stack • Systematic study of design considerations and use cases • First physical and link layer protocols • Performance evaluation and scheduling investigation
CREATE: Expected Service CREATE Node A Node B QEGP QEGP Link Layer Physical Layer • Higher layer to QEGP • Remote node ID, # pairs, min fidelity, max time, request type, ...
OK: Expected Service OK OK Node B Node A QEGP QEGP Link Layer Physical Layer • QEGP to higher layer • Entanglement ID, qubit ID, fidelity estimate, ...
How to Prioritize CREATE Requests • Requires context and information • Simple version: first come first serve • More interesting: cater to different use cases
Our Contribution • Functional allocation of quantum network stack • Systematic study of design considerations and use cases • First physical and link layer protocols • Performance evaluation and scheduling investigation
Simulation Tool: NetSQUID • Discrete event simulator • Model and validate simulated quantum hardware • Model physical components e.g. fibers, nodes, and midpoint
Simulation Environment: SurfSARA • Long runs • Protocol robustness: recovery mechanisms • Short runs • Performance trade-offs: latency, throughput and fidelity • Metric fluctuations: different scheduling strategies
Simulation Example: QL2020 KPN PB400 node location 15km KPN PBX detector location Assumed loss 0.1 dB/splice 0.3 dB/km 10km TU Delft node location
Evaluation: Quantum Hardware Model • Simulate experiments • Fidelity vs rate of success • Qubit memory lifetimes