Adversarial Robustness of Partitioned Quantum Classifiers

Fuente: arXiv
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Main Authors: Kananian, Pouya, Jacobsen, Hans-Arno
Format: Preprint
Published: 2025
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author Kananian, Pouya
Jacobsen, Hans-Arno
author_facet Kananian, Pouya
Jacobsen, Hans-Arno
contents Adversarial robustness in quantum classifiers is a critical area of study, providing insights into their performance compared to classical models and uncovering potential advantages inherent to quantum machine learning. In the NISQ era of quantum computing, circuit cutting is a notable technique for simulating circuits that exceed the qubit limitations of current devices, enabling the distribution of a quantum circuit's execution across multiple quantum processing units through classical communication. In contrast, when quantum communication is available, teleportation-based methods can be used to support the distribution of the quantum circuit. We study the robustness of partitioned quantum classifiers to adversarial perturbations targeting wire cutting or quantum state teleportation and show a link between such perturbations and implementing adversarial gates within intermediate layers of a quantum classifier. We then proceed to study the latter problem from both a theoretical and experimental perspective.
format Preprint
id arxiv_https___arxiv_org_abs_2502_20403
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Adversarial Robustness of Partitioned Quantum Classifiers
Kananian, Pouya
Jacobsen, Hans-Arno
Emerging Technologies
Artificial Intelligence
Cryptography and Security
Machine Learning
Quantum Physics
Adversarial robustness in quantum classifiers is a critical area of study, providing insights into their performance compared to classical models and uncovering potential advantages inherent to quantum machine learning. In the NISQ era of quantum computing, circuit cutting is a notable technique for simulating circuits that exceed the qubit limitations of current devices, enabling the distribution of a quantum circuit's execution across multiple quantum processing units through classical communication. In contrast, when quantum communication is available, teleportation-based methods can be used to support the distribution of the quantum circuit. We study the robustness of partitioned quantum classifiers to adversarial perturbations targeting wire cutting or quantum state teleportation and show a link between such perturbations and implementing adversarial gates within intermediate layers of a quantum classifier. We then proceed to study the latter problem from both a theoretical and experimental perspective.
title Adversarial Robustness of Partitioned Quantum Classifiers
topic Emerging Technologies
Artificial Intelligence
Cryptography and Security
Machine Learning
Quantum Physics
url https://arxiv.org/abs/2502.20403