hardware algorithms

Toward Secure Multitenant Quantum Computing: Circuit Affinity, Crosstalk Patterns, and Grouping Strategies

Curator's Take

This research tackles a critical challenge as quantum cloud computing scales up: how to safely run multiple users' quantum circuits simultaneously without compromising security or performance. The authors discovered that different quantum algorithms have distinct "personalities" when it comes to interference - some are naturally aggressive and disrupt neighboring circuits, while others are sensitive victims of crosstalk, creating predictable patterns that could potentially be exploited by malicious actors. What makes this particularly valuable is their systematic analysis across multiple IBM quantum processors, showing that these interference signatures are consistent within hardware generations but change between different chip revisions. This work provides essential groundwork for developing secure quantum cloud services that can maximize efficiency while protecting users from both accidental interference and intentional eavesdropping through crosstalk analysis.

— Mark Eatherly

Summary

Multitenancy increases throughput and reduces costs in cloud-based quantum computing, but concurrent job execution introduces security risks through inter-circuit crosstalk. We characterize the structural predictability of these interference patterns across seven IBM superconducting processors, spanning Heron (r1-r3) and Nighthawk (r1) architectures and five different circuit types. We evaluate pairwise interactions, by applying the Structural Similarity Index (SSIM) and a structural $t$-statistic to the concurrent execution of five foundational quantum circuits (QAOA, Grover's, QPE, QFT, and ZZFeatureMap), we quantify behavioral consistency across disparate hardware. Our results identify three types of circuits: universally aggressive, universally sensitive, and cotenant-dependent circuits. Aggressive circuits, such as Grover's Algorithm, exhibit a statistically significant interference pattern, yielding a $t$-statistic range of $[1.37,2.61]$ relative to the standalone baselines across all tested pairings. Conversely, sensitive circuits, such as the Quantum Fourier Transform, demonstrate a disproportionate susceptibility to multitenant execution, showing high deviations from single-tenant computational behavior. We demonstrate that crosstalk signatures are highly consistent within architectural revisions--with intra-revision similarity reaching $0.77$ (Hr3) and $0.68$ (Hr2)--while inter-revision similarity drops to $0.43$. Furthermore, we identify a ``topological decoupling" between Heavy-Hex and square lattice systems, where structural similarity falls to $0.01$ between Heron r1 and Nighthawk r1. These findings provide an empirical foundation for hardware-aware schedulers to strategically pair jobs, maximizing system utilization while preserving computational integrity.