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1. A throughput optimal scheduling policy for a quantum switch

   https://doi.org/10.1117/12.2616950  

   Vasantam, Thirupathaiah; Towsley, Don (March 2022, Proceedings Volume 12015, Quantum Computing, Communication, and Simulation II;)

   Hemmer, Philip R.; Migdall, Alan L. (Ed.)

   We study a quantum switch that creates shared end-to-end entangled quantum states to multiple sets of users that are connected to it. Each user is connected to the switch via an optical link across which bipartite Bell-state entangled states are generated in each time-slot with certain probabilities, and the switch merges entanglements of links to create end-to-end entanglements for users. One qubit of an entanglement of a link is stored at the switch and the other qubit of the entanglement is stored at the user corresponding to the link. Assuming that qubits of entanglements of links decipher after one time-slot, we characterize the capacity region, which is defined as the set of arrival rates of requests for end-to-end entanglements for which there exists a scheduling policy that stabilizes the switch. We propose a Max-Weight scheduling policy and show that it stabilizes the switch for all arrival rates that lie in the capacity region. We also provide numerical results to support our analysis. 

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2. Optimizing Age of Information in Wireless Networks with Throughput Constraints

   Kadota, Igor; Sinha, Abhishek; Modiano, Eytan (April 2018, IEEE Infocom)

   Age of Information (AoI) is a performance metric that captures the freshness of the information from the perspective of the destination. The AoI measures the time that elapsed since the generation of the packet that was most recently delivered to the destination. In this paper, we consider a singlehop wireless network with a number of nodes transmitting timesensitive information to a Base Station and address the problem of minimizing the Expected Weighted Sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes. We develop three low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluate their performance against the optimal policy. In particular, we develop a randomized policy, a Max- Weight policy and a Whittle’s Index policy, and show that they are guaranteed to be within a factor of two, four and eight, respectively, away from the minimum AoI possible. In contrast, simulation results show that Max-Weight outperforms the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieves near optimal performance. 

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3. A quantum processor based on coherent transport of entangled atom arrays

   https://doi.org/10.1038/s41586-022-04592-6  

   Bluvstein, Dolev; Levine, Harry; Semeghini, Giulia; Wang, Tout T.; Ebadi, Sepehr; Kalinowski, Marcin; Keesling, Alexander; Maskara, Nishad; Pichler, Hannes; Greiner, Markus; et al (April 2022, Nature)

   Abstract The ability to engineer parallel, programmable operations between desired qubits within a quantum processor is key for building scalable quantum information systems 1,2 . In most state-of-the-art approaches, qubits interact locally, constrained by the connectivity associated with their fixed spatial layout. Here we demonstrate a quantum processor with dynamic, non-local connectivity, in which entangled qubits are coherently transported in a highly parallel manner across two spatial dimensions, between layers of single- and two-qubit operations. Our approach makes use of neutral atom arrays trapped and transported by optical tweezers; hyperfine states are used for robust quantum information storage, and excitation into Rydberg states is used for entanglement generation 3–5 . We use this architecture to realize programmable generation of entangled graph states, such as cluster states and a seven-qubit Steane code state 6,7 . Furthermore, we shuttle entangled ancilla arrays to realize a surface code state with thirteen data and six ancillary qubits 8 and a toric code state on a torus with sixteen data and eight ancillary qubits 9 . Finally, we use this architecture to realize a hybrid analogue–digital evolution 2 and use it for measuring entanglement entropy in quantum simulations 10–12 , experimentally observing non-monotonic entanglement dynamics associated with quantum many-body scars 13,14 . Realizing a long-standing goal, these results provide a route towards scalable quantum processing and enable applications ranging from simulation to metrology. 

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4. Entanglement of nanophotonic quantum memory nodes in a telecom network

   https://doi.org/10.1038/s41586-024-07252-z  

   Knaut, C M; Suleymanzade, A; Wei, Y-C; Assumpcao, D R; Stas, P-J; Huan, Y Q; Machielse, B; Knall, E N; Sutula, M; Baranes, G; et al (May 2024, Nature)

   Abstract A key challenge in realizing practical quantum networks for long-distance quantum communication involves robust entanglement between quantum memory nodes connected by fibre optical infrastructure^1–3. Here we demonstrate a two-node quantum network composed of multi-qubit registers based on silicon-vacancy (SiV) centres in nanophotonic diamond cavities integrated with a telecommunication fibre network. Remote entanglement is generated by the cavity-enhanced interactions between the electron spin qubits of the SiVs and optical photons. Serial, heralded spin-photon entangling gate operations with time-bin qubits are used for robust entanglement of separated nodes. Long-lived nuclear spin qubits are used to provide second-long entanglement storage and integrated error detection. By integrating efficient bidirectional quantum frequency conversion of photonic communication qubits to telecommunication frequencies (1,350 nm), we demonstrate the entanglement of two nuclear spin memories through 40 km spools of low-loss fibre and a 35-km long fibre loop deployed in the Boston area urban environment, representing an enabling step towards practical quantum repeaters and large-scale quantum networks. 

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5. Dynamic Pricing and Matching for Two-Sided Queues

   https://doi.org/10.1287/opre.2021.2233  

   Varma, Sushil Mahavir; Bumpensanti, Pornpawee; Maguluri, Siva Theja; Wang, He (January 2023, Operations Research)

   Motivated by applications from gig economy and online marketplaces, we study a two-sided queueing system under joint pricing and matching controls. The queueing system is modeled by a bipartite graph, where the vertices represent customer or server types and the edges represent compatible customer-server pairs. We propose a threshold-based two-price policy and queue length-based maximum-weight matching policy and show that it achieves a near-optimal profit. We study the system under the large-scale regime, wherein the arrival rates are scaled up, and under the large-market regime, wherein both the arrival rates and numbers of customer and server types increase. We show that two-price policy is a primary driver for optimality in the large-scale regime. We demonstrate the advantage of maximum-weight matching with respect to the number of customer and server types. Concurrently, we show that the interplay of pricing and matching is crucial for optimality in the large-market regime. 

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