The paper introduces Accordion, an end-to-end framework that significantly improves the efficiency of compiling fermionic Hamiltonians into quantum circuits for simulation on constrained quantum hardw…

The paper constructs a family of simple quantum states (pseudoentangled states) generated by constant-depth circuits that exhibit non-trivial entanglement structure, demonstrating that entanglement st…

The paper introduces QADR, a novel hybrid quantum-classical framework that efficiently trains variational quantum circuits by localizing entanglement reduction, thereby overcoming the exponential memo…

QML-PipeGuard introduces a contract-based framework that monitors the behavioral fingerprint of quantum machine learning pipelines to detect both hardware drift and malicious channel substitution.

This paper surveys the security vulnerabilities of Variational Quantum Circuits (VQCs) to backdoor attacks, detailing various attack mechanisms and analyzing current detection and defense strategies.

The paper introduces a unified framework for Quantum Fully Homomorphic Encryption (QFHE) that achieves exponential efficiency improvements by integrating a novel modular arithmetic program (MAP) tailo…

This paper presents a quantum attack on Module-LWE based lattice schemes like ML-KEM, demonstrating a polynomial-time quantum algorithm with a high success probability.

The paper provides the first machine-checked universal proof, using ring theory, that value-independence implies identical marginal distributions for arithmetic masking, thereby extending the verifica…

The paper introduces Quantum Tunneling-Aware Machine Learning (QTAML) and a compensation algorithm (TAC) that accurately models and compensates for quantum tunneling errors in AI inference, achieving…

The paper proposes Q-AGNN, a Quantum-Enhanced Attentive Graph Neural Network, to improve intrusion detection by modeling network flows as graphs and leveraging quantum circuits to capture complex rela…

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 survey provides a detailed overview of quantum adversarial machine learning, examining existing attacks, novel quantum-enhanced defense strategies, and the theoretical challenges in securing quan…

QCIVET introduces a novel contract-based framework to ensure the integrity of hybrid quantum-classical pipelines by verifying both the structure (syntactic) and the behavior (semantic) of quantum stag…

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…

This paper introduces a quantum optimization framework using QAOA to perform Subgroup Discovery for network intrusion detection, demonstrating that quantum methods can find complex feature interaction…

This paper introduces survey sampling techniques to estimate or minimize empirical pairwise loss functions, showing that targeting informative pairs significantly reduces computational cost while main…

This paper presents a GPU-accelerated implementation of a Learning with Errors (LWE)-based Key Encapsulation Mechanism (KEM), demonstrating significant speedups and energy efficiency gains on modern G…

The paper argues that current lattice-based post-quantum cryptography, which relies on injecting noise, is not unconditionally secure because advanced quantum error correction and learning techniques…

The paper introduces an LLM-guided evolutionary workflow that successfully discovers and certifies a large number of novel bivariate quantum error-correcting codes, demonstrating the utility of LLMs i…

The paper uses majorization theory to analyze lattice reduction, showing that local swaps smooth the Gram-Schmidt profile and deriving variational and telescoping identities for the worst-case profile…