Architectures and Circuits for Distributed Quantum Computing

Martin Suchara, Yuri Alexeev, Frederic T. Chong +5 more

Leo Sünkel, Jonas Stein, Jonas Nüßlein +2 more

Scaling quantum computers, i.e., quantum processing units (QPUs) to enable the execution of large quantum circuits is a major challenge, especially for applications that should provide a quantum advantage over classical algorithms. One approach to scale QPUs is to connect multiple machines through quantum and classical channels to form clusters or even quantum networks. Using this paradigm, several smaller QPUs can collectively execute circuits that each would not be able on its own. However, communication between QPUs is costly as it requires generating and maintaining entanglement, and hence it should be used wisely. In this paper, we evaluate the architectures, and in particular the entanglement patterns, of variational quantum circuits in a distributed quantum computing (DQC) setting. That is, using Qiskit, we simulate the execution of an eight qubit circuit using four QPUs each with two computational and two communication qubits where non-local CX-gates are performed using the remote-CX protocol. We compare the performance of various circuits on a binary classification task where training is executed under ideal and testing under noisy conditions. The study provides initial results on suitable VQC architectures for the DQC paradigm, and indicates that a standard VQC baseline is not always the best choice, and alternative architectures that use entanglement between QPUs sparingly deliver better results under noise.

Daniel Casado-Faulí, Parfait Atchade-Adelomou, David Pérez de Lara +1 more

Debin Xiang, Liqiang Lu, Siwei Tan +5 more

We present AdaptDQC, an adaptive compiler framework for optimizing distributed quantum computing (DQC) under diverse performance metrics and inter-chip communication (ICC) architectures. AdaptDQC leverages a novel spatial-temporal graph model to describe quantum circuits, model ICC architectures, and quantify critical performance metrics in DQC systems, yielding a systematic and adaptive approach to constructing circuit-partitioning and chip-mapping strategies that admit hybrid ICC architectures and are optimized against various objectives. Experimental results on a collection of benchmarks show that AdaptDQC outperforms state-of-the-art compiler frameworks: It reduces, on average, the communication cost by up to 35.4% and the latency by up to 38.4%.

Juan Carlos Boschero, Niels M. P. Neumann, Ward van der Schoot +2 more

D. Main, P. Drmota, D. P. Nadlinger +6 more

Abstract Distributed quantum computing (DQC) combines the computing power of multiple networked quantum processing modules, ideally enabling the execution of large quantum circuits without compromising performance or qubit connectivity 1,2 . Photonic networks are well suited as a versatile and reconfigurable interconnect layer for DQC; remote entanglement shared between matter qubits across the network enables all-to-all logical connectivity through quantum gate teleportation (QGT) 3,4 . For a scalable DQC architecture, the QGT implementation must be deterministic and repeatable; until now, no demonstration has satisfied these requirements. Here we experimentally demonstrate the distribution of quantum computations between two photonically interconnected trapped-ion modules. The modules, separated by about two metres, each contain dedicated network and circuit qubits. By using heralded remote entanglement between the network qubits, we deterministically teleport a controlled-Z (CZ) gate between two circuit qubits in separate modules, achieving 86% fidelity. We then execute Grover’s search algorithm 5 —to our knowledge, the first implementation of a distributed quantum algorithm comprising several non-local two-qubit gates—and measure a 71% success rate. Furthermore, we implement distributed iSWAP and SWAP circuits, compiled with two and three instances of QGT, respectively, demonstrating the ability to distribute arbitrary two-qubit operations 6 . As photons can be interfaced with a variety of systems, the versatile DQC architecture demonstrated here provides a viable pathway towards large-scale quantum computing for a range of physical platforms.