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Bulletin of the American Physical Society

Modeling Networks of Superconducting Qubit Arrays from the Physical to Processing Layers

Nicholas D. LaRacuente, Kaitlin N. Smith, Poolad Imany, Kevin L. Silverman, Frederic T. Chong

Published Mar 19, 2021• 0 citations
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A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address these challenges in a scalable manner. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. Our methods of modeling and evaluating the chiplet architecture bridge the physical and network layers in these processors. We find evidence that distributing computation across chiplets may reduce the overall error rates associated with moving data across the device, despite higher error figures for transfers across links. Preliminary analyses suggest that latency is not substantially impacted, and that at least some applications and architectures may avoid bottlenecks around chiplet boundaries. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.
Superconducting qubits arrays have become one of the most promising architectures for the practical implementation of universal quantum computing with quantum error correction codes. Here we propose a defect-tolerant surface code topology which is resistant to sparse fabrication defects. The topology is equivalent to a disk folded into NNN layers. A physically defective qubit can be replaced with a working physical qubit within the same unit cell from a different layer. Thereby sparse fabrication errors can be collected into one sacrificial layer and isolated from the working layers by turning off their controllable couplers. We propose two schemes to realize this robust topology. One is to use flux qubits, and the other is based on Xmon qubits. A modified quantum circuit for the stabilization cycle of the Xmon qubits scheme is developed. We calculate and compare the per-operation error thresholds for these two schemes and find that the error threshold for the modified quantum circuit is close to that for the original stabilization cycle. A possible way to implement the intersecting connections between different Xmon qubits on the circuit level is also provided.
Abstract We investigate the influence of topology on the magnetic response of inductively coupled superconducting flux-qubit networks. Using exact diagonalization methods and linear response theory, we compare the magnetic response of linear and cross-shaped array geometries, used as paradigmatic examples. We find that the peculiar coupling matrix in cross-shaped arrays yields a significant enhancement of the magnetic flux response compared to linear arrays, this network-topology effect arising from cooperative coupling among the central and the peripheral qubits. These results establish quantitative design criteria for function-oriented superconducting quantum circuits, with direct implications for advancing performance in both quantum sensing and quantum information processing applications. Concerning the latter, by exploiting the non-linear and high-dimensional dynamics of such arrays, we demonstrate their suitability for quantum reservoir computing technology. This dual functionality suggests a novel platform in which the same device serves both as a quantum-limited electromagnetic sensor and as a reservoir capable of signal processing, enabling integrated quantum sensing and processing architectures.