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SWAP Attack: Stealthy Side-Channel Attack on Multi-Tenant quantum Cloud System

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arXiv 2025年

作者： Lee, Wei Jie Bryan Wang, Siyi Dutta, Suman Maouaki, Walid El Chattopadhyay, Anupam College of Computing and Data Science Nanyang Technological University Singapore Applied Statistics Unit Indian Statistical Institute Kolkata India Quantum Physics and Spintronics Team LPMC Faculty of Sciences Ben M’Sik Hassan II University of Casablanca Morocco

The rapid advancement of quantum computing has spurred widespread adoption, with cloud-based quantum devices gaining traction in academia and industry. This shift raises critical concerns about the privacy and security of computations on shared, multi-tenant quantum platforms accessed remotely. In several recent works, crosstalk has been exploited on shared quantum devices, enabling adversaries to interfere with the victim circuits within a neighborhood. Though illuminating, these studies left several unresolved questions regarding the fundamental cause of crosstalk, effective countermeasures, and replicability across different circuits. In this paper, we revisit the crosstalk effect, tracing its origins to the SWAP path between various qubits in a circuit and demonstrating its effectiveness even over long distances. The results significantly improve our understanding of the phenomenon beyond prior works. Our proposed SWAP-based side-channel attack can be executed in both active and passive modes, as verified on real shared IBM quantum devices. In the active attack, an adversary executing a single CNOT gate can perturb victim circuits running Grover’s Algorithm from afar, reducing the expected output accuracy through 81.62% by strategically positioning qubits. Moreover, this phenomenon can be clearly explained through modeling, where specific qubits in a platform can be identified as more susceptible to an attacker. The passive attack, leveraging a stealthy circuit as small as 6.25% of the victim’s, achieves 100% accuracy in predicting the circuit size of the victim, running Simon’s Algorithm. These findings challenge the existing defense strategy of maximizing topological distance between circuits, demonstrating that attackers can still extract sensitive information or manipulate results remotely. Our work highlights the need for more robust security measures to safeguard quantum computations against such emerging threats. © 2025, CC BY.

关键词： Qubits

Collapse-based models for gravity do not violate the Entanglement-Based Witness of non-classicality

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arXiv 2025年

作者： Feng, Tianfeng Vedral, Vlatko Marletto, Chiara QICI Quantum Information and Computation Initiative School of Computing and Data Science The University of Hong Kong Pokfulam Road Hong Kong Clarendon Laboratory University of Oxford Parks Road OxfordOX1 3PU United Kingdom

It is known that an entanglement-based witness of non-classicality can be applied to testing quantum effects in gravity. Specifically, if a system can create entanglement between two quantum probes by local means only, then it must be non-classical. Recently, claims have been made that collapse-based models of classical gravity, i.e. Diósi-Penrose model, can predict gravitationally induced entanglement between quantum objects, resulting in gravitationally induced entanglement is insufficient to conclude that gravity is fundamentally quantum, contrary to the witness statement. Here we vindicate the witness. We analyze the underlying physics of collapse-based models for gravity and show that these models have nonlocal features, violating the principle of locality. Copyright © 2025, The Authors. All rights reserved.

关键词： quantum entanglement

Artificial Intelligence for the Classification of Neuromuscular Diseases Using Dominant MUAP 8

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Artificial Intelligence for the Classification of Neuromuscu...

8th International Conference on Smart Structures and Systems, ICSSS 2022

作者： Maheshwary, Priti Vinu, W. Velvadivu, P. Shukla, Surendra Kumar Srivastava, Prabhat Kumar Pareek, Prakash Centre for Internet of Things and Advance Computing Rabindranath Tagore University Bhopal India Annamalai University Department of Physical Education Tamilnadu Chidambaram India Coimbatore Institute of Technology Department of Computing-Data Science Tamilnadu Coimbatore India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Quantum University Department of Computer Science and Engineering Uttrakhand Roorkee India Vishnu Institute of Technology Department of Electronics and Communication Engineering Andhra Pradesh Bhimavaram India

ISBN: (纸本)9781665497619

Motor-unit-action-potentials in an electromyographic isolated signals shape & sounds are valuable diagnosis information for neuro-muscular disorders-treatment & management. An expert can analyse these parameters qualitatively or quantitative by pattern recognition techniques. Because of benefits of the quantitatively method of EMG, producing robust automated MUAP types is investigated, & many systems is produced for this purpose, but correctness of the previous methods isn't peak enough to use in clinical settings. The developed system uses an EMG signal decomposition mechanism to extract both time & frequency domain for M-U-A-P's retrieved from E-M-G. Un-similar type of algorithms was studied, including 1 & many types with many sub-sets characteristics. The multi-classifier methods proposed here performed well in experiments by real set EMG. The multi-classifier, which aggregates base classifiers using multiple feature sets & both trainable & non-trainable fusion techniques, performed the best of the methods studied, with an average precision is 98%. © 2022 IEEE.

关键词： Support vector machines Time-frequency analysis Shape Neuromuscular Morphology Electromyography Pattern recognition

Logical entanglement distribution between distant 2D array qubits

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arXiv 2025年

作者： Maeda, Yuya Suzuki, Yasunari Kobayashi, Toshiki Yamamoto, Takashi Tokunaga, Yuuki Fujii, Keisuke Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka560-8531 Japan NTT Computer and Data Science Laboratories NTT Corporation Musashino180-8585 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan Center for Quantum Information and Quantum Biology Institute for Open and Transdisciplinary Research Initiatives Osaka University Japan Center for Quantum Computing RIKEN Wako Saitama351-0198 Japan

Sharing logical entangled pairs between distant quantum nodes is a key process to achieve fault-tolerant quantum computation and communication. However, there is a gap between current experimental specifications and theoretical requirements for sharing logical entangled states while improving experimental techniques. Here, we propose an efficient logical entanglement distribution protocol based on surface codes for two distant 2D qubit array with nearest-neighbor interaction. A notable feature of our protocol is that it allows post-selection according to error estimations, which provides the tunability between the infidelity of logical entanglements and the success probability of the protocol. With this feature, the fidelity of encoded logical entangled states can be improved by sacrificing success rates. We numerically evaluated the performance of our protocol and the trade-off relationship, and found that our protocol enables us to prepare logical entangled states while improving fidelity in feasible experimental parameters. We also discuss a possible physical implementation using neutral atom arrays to show the feasibility of our protocol. © 2025, CC BY.

关键词： Qubits

Indirect influence in social networks as an induced percolation phenomenon (vol 119, e2100151119, 2022)

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PROCEEDINGS OF THE NATIONAL ACADEMY OF scienceS OF THE UNITED STATES OF AMERICA 2022年第24期119卷 e2100151119-e2100151119页

作者： Xie, Jiarong Wang, Xiangrong Feng, Ling Zhao, Jin-Hua Liu, Wenyuan Moreno, Yamir Hu, Yanqing School of Computer Science and Engineering Sun Yat-sen University 510006 Guangzhou China Institute of Future Networks Southern University of Science and Technology 518055 Shenzhen China Peng Cheng Laboratory 518066 Shenzhen China Institute of High Performance Computing A*STAR 138632 Singapore Department of Physics National University of Singapore 117551 Singapore Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University 510006 Guangzhou China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University 510006 Guangzhou China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Institute for Biocomputation and Physics of Complex Systems University of Zaragoza 50018 Zaragoza Spain Department of Theoretical Physics University of Zaragoza 50018 Zaragoza Spain ISI Foundation 10126 Torino Italy Department of Statistics and Data Science College of Science Southern University of Science and Technology 518055 Shenzhen China

Percolation theory has been widely used to study phase transitions in network systems. It has also successfully explained various macroscopic spreading phenomena across different fields. Yet, the theoretical frameworks have been focusing on direct interactions among nodes, while recent empirical observations have shown that indirect interactions are common in many network systems like social and ecological networks, among others. By investigating the detailed mechanism of both direct and indirect influence on scientific collaboration networks, here we show that indirect influence can play the dominant role in behavioral influence. To address the lack of theoretical understanding of such indirect influence on the macroscopic behavior of the system, we propose a percolation mechanism of indirect interactions called induced percolation. Surprisingly, our model exhibits a unique anisotropy property. Specifically, directed networks show first-order abrupt transitions as opposed to the second-order continuous transition in the same network structure but with undirected links. A mix of directed and undirected links leads to rich hybrid phase transitions. Furthermore, a unique feature of the nonmonotonic pattern is observed in network connectivities near the critical point. We also present an analytical framework to characterize the proposed induced percolation, paving the way to further understanding network dynamics with indirect interactions.

关键词： percolation indirect interactions social network phase transition behavioral contagion

quantum Fourier Transform of Atrial Fibrillation

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Quantum Fourier Transform of Atrial Fibrillation

quantum computing and Engineering (QCE), IEEE International Conference on

作者： Yu-Ching Chen Chih-Yu Chen Tsung-Wei Huang Chia-Ho Ou Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Electrocardiograms (ECGs) are crucial for detecting cardiac diseases like atrial fibrillation (AF). Traditional analysis methods like fast Fourier transform (FFT) face challenges with increasing data complexity. This study uses Taipei Veterans General Hospital data to explore quantum Fourier transform (QFT) for ECG analysis. Results show that QFT effectively analyzes ECG signals, matching FFT performance while benefiting from quantum computing's efficiency.

关键词： Heart quantum computing Fast Fourier transforms Hospitals High performance computing Atrial fibrillation Machine learning Electrocardiography Real-time systems Signal analysis

Full minimal coupling Maxwell-TDDFT: An ab initio framework for light-matter interaction beyond the dipole approximation

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Physical Review B 2025年第8期111卷 085114-085114页

作者： Franco P. Bonafé Esra Ilke Albar Sebastian T. Ohlmann Valeriia P. Kosheleva Carlos M. Bustamante Francesco Troisi Angel Rubio Heiko Appel Max Planck Institute for the Structure and Dynamics of Matter Center for Free Electron Laser Science Luruper Chaussee 149 22761 Hamburg Germany Max Planck Computing and Data Facility Gießenbachstrasse 2 85748 Garching Germany Center for Computational Quantum Physics (CCQ) The Flatiron Institute 162 Fifth Avenue New York New York 10010 USA

We report an ab initio, nonrelativistic QED method that couples light and matter self-consistently beyond the electric dipole approximation and without multipolar truncations. This method is based on an extension of the Maxwell-Pauli-Kohn-Sham approach to a full minimal coupling Hamiltonian, where the space- and time-dependent vector potential is coupled to the matter system, and its back reaction to the radiated fields is generated by the full current density. The implementation in the open-source code octopus is designed for massively parallel multiscale simulations considering different grid spacings for the Maxwell and matter subsystems. Here, we show applications of this framework to simulate renormalized Cherenkov radiation of an electronic wave packet, magneto-optical effects with nonchiral light in nonchiral molecular systems, and renormalized plasmonic modes in a nanoplasmonic dimer. We show that in some cases, the beyond-dipole effects cannot be captured by a multipolar expansion Hamiltonian in the length gauge. Finally, we discuss further opportunities enabled by the framework in the field of twisted light and orbital angular momentum, inelastic light scattering, and strong-field physics.

关键词： Light scattering

Distributed quantum Simulation

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arXiv 2024年

作者： Feng, Tianfeng Xu, Jue Yu, Wenjun Ye, Zekun Yao, Penghui Zhao, Qi QICI Quantum Information and Computation Initiative Department of Computer Science School of Computing and Data Science The University of Hong Kong Pokfulam Road Hong Kong State Key Laboratory for Novel Software Technology Nanjing University Hefei National Laboratory Nanjing 210023 China Hefei230088 China

quantum simulation is a promising pathway toward practical quantum advantage by simulating large-scale quantum systems. In this work, we propose communication-efficient distributed quantum simulation protocols by exploring three quantum simulation algorithms, including the product formula, the truncated Taylor series, and the processing of quantum signals over a quantum network. Our protocols are further shown to be optimal by deriving a lower bound on the quantum communication complexity for distributed quantum simulations with respect to evolution time and the number of distributed quantum processing units. Additionally, our distributed techniques go beyond quantum simulation and are applied to distributed versions of Grover’s algorithms and quantum phase estimation. Our work not only paves the way for achieving a practical quantum advantage by scalable quantum simulation but also enlightens the design of more general distributed architectures across various physical systems for quantum computation. Copyright © 2024, The Authors. All rights reserved.

关键词： quantum computers

Optical quantum sensing for agnostic environments via deep learning

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Physical Review Research 2024年第4期6卷 043267-043267页

作者： Zeqiao Zhou Yuxuan Du Xu-Fei Yin Shanshan Zhao Xinmei Tian Dacheng Tao MoE Key Laboratory of Brain-inspired Intelligent Perception and Cognition University of Science and Technology of China Hefei 230026 China JD Explore Academy Beijing 101111 China College of Computing and Data Science Nanyang Technological University Singapore 639798 Singapore Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences University of Science and Technology of China Hefei 230026 China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 China School of Computer Science The University of Sydney NSW 2008 Australia

Optical quantum sensing promises measurement precision beyond classical sensors termed the Heisenberg limit (HL). However, conventional methodologies often rely on prior knowledge of the target system to achieve HL, presenting challenges in practical applications. Addressing this limitation, we introduce an innovative deep-learning-based quantum sensing scheme (DQS), enabling optical quantum sensors to attain HL in agnostic environments. DQS incorporates two essential components: a graph neural network (GNN) predictor and a trigonometric interpolation algorithm. Operating within a data-driven paradigm, DQS utilizes the GNN predictor, trained on offline data, to unveil the intrinsic relationships between the optical setups employed in preparing the probe state and the resulting quantum Fisher information (QFI) after interaction with the agnostic environment. This distilled knowledge facilitates the identification of optimal optical setups associated with maximal QFI. Subsequently, DQS employs a trigonometric interpolation algorithm to recover the unknown parameter estimates for the identified optical setups. Extensive experiments are conducted to investigate the performance of DQS under different settings up to eight photons. Our findings not only offer a different lens through which to accelerate optical quantum sensing tasks but also catalyze future research integrating deep learning and quantum mechanics.

关键词： Graph neural networks