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Manik Dawar

Publications and source records attributed to Manik Dawar.

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Feasibility of satellite-augmented global quantum repeater networks

A large scale quantum network requires the distribution of high-fidelity end-to-end entanglement. To overcome the range limitations inherent to terrestrial fiber, a leading architecture has emerged: satellite-based sources transmitting entanglement to quantum repeaters on the ground. By bridging the gap between abstract analytical frameworks and computationally heavy numerical simulations, this paper provides the first quantitative answer to the question of such a network's achievable performance with current and near-term space technology, while accounting for entanglement swapping and purification. This is achieved by integrating a detailed physical model of a satellite-to-ground link into an analytical entanglement resource estimation framework for quantum repeaters, enabling an optimization of the end-to-end entanglement rate. Our analysis, performed across leading quantum hardware platforms, shows that Low Earth Orbit satellite constellations combined with quantum repeaters employing Neutral Atom or Nitrogen and Silicon Vacancy qubits, could enable a global quantum network, distributing entanglement over distances up to 20,000 km, sufficient for connecting any two points on Earth. This work highlights the major bottlenecks in space and quantum hardware technologies, which need to be addressed, thereby guiding informed investments necessary for enabling a large scale quantum network.

quant-ph

Quantum Internet: Resource Estimation for Entanglement Routing

Quantum repeaters have promised efficient scaling of quantum networks for over two decades. Despite numerous platforms proclaiming functional repeaters, the realization of large-scale networks remains elusive, indicating that the resources required to do so were thus far underestimated. Here, we investigate the dependence of resource scaling of networks on realistic experimental errors. Using a nested repeater protocol based on the purification protocol by Bennett et. al., we provide an analytical approximation of the polynomial degree of the resources consumed by entanglement routing. Our error model predicts substantially stricter thresholds for efficient network operation than previously suggested, requiring two-qubit gate errors below 1.3% for resource scaling with polynomial degree below 10. The analytical model presented here provides insight into the reason why previous experimental implementations of quantum repeaters failed to scale efficiently and inform the development of truly scalable systems, highlighting the need for high-fidelity local two-qubit gates. We employ our analytical approximation of the scaling exponent as a figure of merit to compare different platforms and find that trapped ions and color centers in diamond currently provide the best route towards large-scale networks.

quant-ph

Applying an Evolutionary Algorithm to Minimize Teleportation Costs in Distributed Quantum Computing

By connecting multiple quantum computers (QCs) through classical and quantum channels, a quantum communication network can be formed. This gives rise to new applications such as blind quantum computing, distributed quantum computing, and quantum key distribution. In distributed quantum computing, QCs collectively perform a quantum computation. As each device only executes a sub-circuit with fewer qubits than required by the complete circuit, a number of small QCs can be used in combination to execute a large quantum circuit that a single QC could not solve on its own. However, communication between QCs may still occur. Depending on the connectivity of the circuit, qubits must be teleported to different QCs in the network, adding overhead to the actual computation; thus, it is crucial to minimize the number of teleportations. In this paper, we propose an evolutionary algorithm for this problem. More specifically, the algorithm assigns qubits to QCs in the network for each time step of the circuit such that the overall teleportation cost is minimized. Moreover, network-specific constraints such as the capacity of each QC in the network can be taken into account. We run experiments on random as well as benchmarking circuits and give an outline on how this method can be adjusted to be incorporated into more realistic network settings as well as in compilers for distributed quantum computing. Our results show that an evolutionary algorithm is well suited for this problem when compared to the graph partitioning approach as it delivers better results while simultaneously allows the easy integration and consideration of various problem-specific constraints.

quant-ph