Asynchronous Quantum Distributed Computing: Causality, Snapshots, and Global Operations
2026-04-09 • Distributed, Parallel, and Cluster Computing
Distributed, Parallel, and Cluster Computing
AI summaryⓘ
The authors study how to perform global quantum tasks across asynchronous quantum computing systems by breaking them down into local steps. They build on a classical method for taking system-wide snapshots to create a quantum version called the QGO Algorithm. Their analysis shows that certain timing and cause-effect ideas from classical computing also apply in quantum systems, despite the complexities of entanglement. They also propose a formal framework for quantum distributed computing that could be useful more broadly.
asynchronous distributed systemsquantum distributed computingatomic quantum operationsquantum snapshotChandy-Lamport algorithmquantum entanglementcomputational causalityglobal quantum operationsrandomized algorithms
Authors
Siddhartha Visveswara Jayanti, Anand Natarajan
Abstract
We initiate the study of asynchronous quantum distributed systems, focusing on the case of implementing atomic quantum global operations that can be decomposed into a collection of local operations on the components of the system. A simple example of such an operation is a quantum snapshot in which the whole system is instantaneously measured. Based on the classical snapshot algorithm of Chandy and Lamport, we design a quantum distributed algorithm to implement such decomposable global operations, which we call the QGO Algorithm. The analysis of our algorithm shows that arguments based on Lamport's computational causality remain valid in the quantum world, even though, due to entanglement, causality is not manifest from the standard description of the system in terms of a (global) quantum state. Our other contributions include a formal model of quantum distributed computing, and a formal specification for the desired behavior of a global operation, which may be of interest even in classical settings (such as in the setting of randomized algorithms).