This survey provides a comprehensive review of the security challenges, threats, and mitigation strategies associated with the rapid advancement of quantum computing.

This study empirically benchmarks classical and quantum machine learning models for image recognition, finding that while quantum models offer superior accuracy and resource efficiency at high dimensi…

The paper proposes a two-dimensional coordinate system to map the co-evolution of cryptographic resilience and computational capability, identifying the 'Quantum Gap' as the primary systemic risk requ…

This paper presents QAccCert, a quantum software framework for quantum computer certification using FPGAs, AI, and ideal quantum simulations.

The paper presents Broken Quantum, a comprehensive formal security audit that identifies 547 security vulnerabilities across 45 open-source quantum computing simulators, revealing critical flaws in me…

This paper compares the performance of quantum machine learning models with classical models and finds that the quantum models do not yet surpass classical baselines.

The paper reviews adversarial machine learning vulnerabilities and proposes conceptual frameworks for enhancing AI robustness by integrating quantum computing techniques.

The paper reviews the vulnerability of AI to adversarial attacks and proposes conceptual frameworks for enhancing AI robustness by integrating quantum computing techniques.

This paper shows that shallow circuits cannot prepare near-optimal states for random quantum $p$-spin glasses, and proves depth lower bounds for such preparations.

This paper shows that larger gradient-based parameterized quantum circuits can exhibit improved performance on unseen data, contrasting the traditional view.

QSignAI is an open-source platform that integrates quantum-randomness-seeded identity signatures into a conversational AI social messaging system, demonstrating a practical bidirectional link between…

This paper proposes a method to explore the design space of quantum-classical applications using a formalization of an architectural style, enabling dynamic selection of the most suitable configuratio…

This paper provides a comprehensive, system-level taxonomy for designing quantum-resistant network architectures, moving beyond simple protocol substitutions to address key distribution and management…

The paper introduces covert quantum computing, a framework to ensure privacy in multi-tenant quantum cloud environments, and finds that while local crosstalk is limited, long-range coupling effects cr…

The paper proposes a novel Meta-Quantum Ensemble (MQE) framework, which fuses outputs from Quantum Support Vector Machines (QSVMs) and Quantum Neural Networks (QNNs) using a Random Forest meta-learner…