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arXiv:2109.07072 · SN Computer Science

Qurzon: A Prototype for a Divide and Conquer-Based Quantum Compiler for Distributed Quantum Systems

Turbasu Chatterjee, Arnav Das, Shah Ishmam Mohtashim, Amit Saha, Amlan Chakrabarti

Published Jun 10, 2022• 17 citations
arXivHTMLPDF
DOI
10.1007/s42979-022-01207-9

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arXiv:2107.07532•IEEE International Conference on Quantum Computing and Engineering (QCE)•Sep 17, 2023•26 citations
When working with algorithms on quantum devices, quantum memory becomes a crucial bottleneck due to low qubit count in NISQ era devices. In this context, the concept of `divide and compute', wherein a quantum circuit is broken into several subcircuits and executed separately, while stitching the results of the circuits via classical post-processing, becomes a viable option, especially in NISQ era devices. This paper introduces Qurzon, a proposed novel quantum compiler that incorporates the marriage of techniques of divide and compute with the state-of-the-art algorithms of optimal qubit placement for executing on real quantum devices. A scheduling algorithm is also introduced within the compiler that can explore the power of distributed quantum computing while paving the way for quantum parallelism for large algorithms. Several benchmark circuits have been executed using the compiler, thereby demonstrating the power of the divide and compute when working with real NISQ-era quantum devices.
Scaling the size of monolithic quantum computer systems is a difficult task. As the number of qubits within a device increases, a number of factors contribute to decreases in yield and performance. To meet this challenge, distributed architectures composed of many networked quantum computers have been proposed as a viable path to scalability. Such systems will need algorithms and compilers that are tailored to their distributed architectures. In this work we introduce the Quantum Divide and Conquer Algorithm (QDCA), a hybrid variational approach to mapping large combinatorial optimization problems onto distributed quantum architectures. This is achieved through the combined use of graph partitioning and quantum circuit cutting. The QDCA, an example of application-compiler co-design, alters the structure of the variational ansatz to tame the exponential compilation overhead incurred by quantum circuit cutting. The result of this cross-layer co-design is a highly flexible algorithm which can be tuned to the amount of classical or quantum computational resources that are available, and can be applied to both near- and long-term distributed quantum ar-chitectures. We simulate the QDCA on instances of the Maximum Independent Set problem and find that it is able to outperform similar classical algorithms. We also evaluate an 8-qubit QDCA ansatz on a superconducting quantum computer and show that circuit cutting can help to mitigate the effects of noise. Our work demonstrates how many small-scale quantum computers canwork together to solve problems 85 % larger than their own qubit count, motivating the development and potential of large-scale distributed quantum computing.