Search Results (1,243)

The burgeoning Internet of Medical Things (IoMT) offers unprecedented opportunities for real-time patient monitoring and predictive diagnostics, yet the current systems struggle with scalability, data confidentiality against quantum threats, and real-time privacy-preserving intelligence. This paper introduces Med-Q Ledger, a novel, multi-layered framework designed to overcome these critical limitations in the Medical IoT domain. Med-Q Ledger integrates a permissioned Hyperledger Fabric for transactional integrity with a scalable Holochain Distributed Hash Table for high-volume telemetry, achieving horizontal scalability and sub-second commit times. To fortify long-term data security, the framework incorporates post-quantum cryptography (PQC), specifically CRYSTALS-Di lithium signatures and Kyber Key Encapsulation Mechanisms. Real-time, privacy-preserving intelligence is delivered through an edge-based federated learning (FL) model, utilizing lightweight autoencoders for anomaly detection on encrypted gradients. We validate Med-Q Ledger’s efficacy through a critical application: the prediction of intestinal complications like necrotizing enterocolitis (NEC) in preterm infants, a condition frequently necessitating emergency colostomy. By processing physiological data from maternal wearable sensors and infant intestinal images, our integrated Random Forest model demonstrates superior performance in predicting colostomy necessity. Experimental evaluations reveal a throughput of approximately 3400 transactions per second (TPS) with ~180 ms end-to-end latency, a >95% anomaly detection rate with <2% false positives, and an 11% computational overhead for PQC on resource-constrained devices. Furthermore, our results show a 0.90 F1-score for colostomy prediction, a 25% reduction in emergency surgeries, and 31% lower energy consumption compared to MQTT baselines. Med-Q Ledger sets a new benchmark for secure, high-performance, and privacy-preserving IoMT analytics, offering a robust blueprint for next-generation healthcare deployments. Full article

The resource theory of coherence addresses the extent to which quantum properties are present in a given quantum system. While coherence has been extensively studied for individual quantum states, measures of coherence for ensembles of quantum states remain an area of active research. The entanglement-based approach to ensemble coherence—arising from the measurement–ensemble duality principle and the Born rule—connects the ensemble coherence with both the entanglement resource and the measurement’s uncertainty. This paper presents two methods for generating ensemble coherence from a fixed amount of entanglement between two qubit systems. The first method involves applying a von Neumann measurement to one part of a non-maximally entangled bipartite state, resulting in a pair of non-orthogonal states whose coherence can equal the initial entanglement. The second method considers a class of symmetric observables capable of generating ensembles used in quantum key distribution (QKD) protocols such as B92, BB84, and three-state QKD. As a result, this work contributes to understanding how much ensemble coherence can be obtained from a given amount of entanglement. Full article

The emergence of quantum computing poses significant threats to conventional public-key cryptography, driving the urgent need for quantum-resistant cryptographic solutions. While quantum key distribution addresses secure key exchange, its dependency on symmetric keys and point-to-point limitations present scalability constraints. Quantum Asymmetric Encryption (QAE) offers a promising alternative by leveraging quantum mechanical principles for security. This paper presents the first practical implementation of a QAE protocol on IBM Quantum devices, building upon the theoretical framework originally proposed by Yoon et al. We develop a generalized Grover Search Algorithm (GSA) framework that supports non-standard initial quantum states through novel diffusion operator designs, extending its applicability beyond idealized conditions. The complete QAE protocol, including key generation, encryption, and decryption stages, is translated into executable quantum circuits and evaluated on both IBM Quantum simulators and real quantum hardware. Experimental results demonstrate significant scalability challenges, with success probabilities deteriorating considerably for larger systems. The 2-qubit implementation achieves near-perfect accuracy (100% on the simulator, and 93.88% on the hardware), while performance degrades to 78.15% (simulator) and 45.84% (hardware) for 3 qubits, and declines critically to 48.08% (simulator) and 7.63% (hardware) for 4 qubits. This degradation is primarily attributed to noise and decoherence effects in current Noisy Intermediate-Scale Quantum (NISQ) devices, highlighting the limitations of single-iteration GSA approaches. Our findings underscore the critical need for enhanced hardware fidelity and algorithmic optimization to advance the practical viability of quantum cryptographic systems, providing valuable insights for bridging the gap between theoretical quantum cryptography and real-world implementations. Full article

We propose a general and experimentally accessible framework to quantify transition timing in discrete quantum systems via the time-of-flow (TF) distribution. Defined from the rate of population change in a target state, the TF distribution can be reconstructed through repeated projective measurements at discrete times on independently prepared systems, thus avoiding Zeno inhibition. In monotonic regimes, it admits a clear interpretation as a time-of-arrival (TOA) or time-of-departure (TOD) distribution. We apply this approach to optimize time-dependent Hamiltonians, analyze shortcut-to-adiabaticity (STA) protocols, study non-adiabatic features in the dynamics of a three-level time-dependent detuning model, and derive a transition-based quantum speed limit (TF-QSL) for both closed and open quantum systems. We also establish a lower bound on temporal uncertainty and examine decoherence effects, demonstrating the versatility of the TF framework for quantum control and diagnostics. This method provides both a conceptual tool and an experimental protocol for probing and engineering quantum dynamics in discrete-state platforms. Full article

Wireless sensor networks (WSNs) play a major role in various applications, but the main challenge is to maintain security and balanced energy efficiency. Classical routing protocols struggle to achieve both energy efficiency and security because they are more vulnerable to security risks and resource limitations. This paper introduces QSEER, a novel approach that uses quantum technologies to overcome these limitations. QSEER employs quantum-inspired optimization algorithms that leverage superposition and entanglement principles to efficiently explore multiple routing possibilities, thereby identifying energy-efficient paths and reducing redundant transmissions. The proposed protocol enhances the security of data transmission against eavesdropping and tampering by using the principles of quantum mechanics, thus mitigating potential security vulnerabilities. Through extensive simulations, we demonstrated the effectiveness of QSEER in achieving both security and energy efficiency objectives, which achieves 15.1% lower energy consumption compared to state-of-the-art protocols while maintaining 99.8% data integrity under various attack scenarios, extending network lifetime by an average of 42%. These results position QSEER as a significant advancement for next-generation WSN deployments in critical applications such as environmental monitoring, smart infrastructure, and healthcare systems. Full article

In this study, we present the development of a high-average-power, exceptionally stable extreme-ultraviolet (EUV) laser source based on a high-order harmonic generation (HHG) technique. The spectrum of an ytterbium-doped laser is broadened through self-phase modulation (SPM) in a gas-filled hollow fiber and compressed down to 25.3 fs for efficient harmonic generation. The high harmonics are generated in a krypton (Kr) gas cell, delivering a total power of 241 μW within the 30–60 nm spectral range, corresponding to a single harmonic output of 166 μW at a central wavelength of 46.8 nm. Notably, the system demonstrates good power stability with a root-mean-square (RMS) deviation of only 1.95% over 12 h of continuous operation. This advanced light source holds great potential for applications in nano- and quantum-material development and in semiconductor wafer defect detection. Future work aims to further enhance the output power in the 30–60 nm band to the milliwatt level, which would significantly bolster scientific research and technological development in related fields. Full article

Against the background of the accelerating global transition towards a low-carbon energy system, the lithium-ion battery (LIB) industry has witnessed a rapid development. Concurrently, fire accidents in LIB application scenarios have occurred frequently, with safety issues becoming increasingly prominent. Thermal runaway of LIBs is the direct cause of such fires. During the thermal runaway process of LIBs, lithium salts in the electrolyte undergo thermal decomposition reactions with carbonate-based electrolytes, releasing a large amount of heat and fire gases. Among them, the thermal decomposition reactions of LiPF₆ with electrolytes are coupled and superimposed, exhibiting a significant synergistic effect. This paper employs quantum chemical calculation methods to investigate the thermal decomposition reaction mechanisms between PF₅ and POF₃, which generated from the thermal decomposition of LiPF₆ and carbonate-based electrolytes (EC, DMC, and DEC) during the thermal runaway process of LIBs; and presents detailed chemical reaction mechanism models. The P atoms in PF₅ or POF₃ combine with the O atoms of the ether oxygen groups in carbonates, while the F atoms combine with the C atoms adjacent to the ether oxygen groups. This promotes the ring-opening or chain scission of carbonate molecules, reduces the energy required for the reaction, and accelerates the thermal decomposition reaction and the generation of fire gases. Modification of EC, DMC, and DEC through fluorination can effectively inhibit the catalytic effect of PF₅ and POF₃ and improve the oxidation resistance and thermal stability of the electrolytes. Full article

In this work, we propose a novel quantum-informed epistemic framework that extends the classical notion of probability by integrating plausibility, credibility, and possibility as distinct yet complementary measures of uncertainty. This enriched quadruple (P, Pl, Cr, Ps) enables a deeper characterization of quantum systems and decision-making processes under partial, noisy, or ambiguous information. Our formalism generalizes the Born rule within a multi-valued logic structure, linking Positive Operator-Valued Measures (POVMs) with data-driven plausibility estimators, agent-based credibility priors, and fuzzy-theoretic possibility functions. We develop a hybrid classical–quantum inference engine that computes a vectorial aggregation of the quadruples, enhancing robustness and semantic expressivity in contexts where classical probability fails to capture non-Kolmogorovian phenomena such as entanglement, contextuality, or decoherence. The approach is validated through three real-world application domains—quantum cybersecurity, quantum AI, and financial computing—where the proposed model outperforms standard probabilistic reasoning in terms of accuracy, resilience to noise, interpretability, and decision stability. Comparative analysis against QBism, Dempster–Shafer, and fuzzy quantum logic further demonstrates the uniqueness of architecture in both operational semantics and practical outcomes. This contribution lays the groundwork for a new theory of epistemic quantum computing capable of modelling and acting under uncertainty beyond traditional paradigms. Full article

This study couples a carbon quantum dot photocatalyst with a proton relay installed (EDTA-CQDs) for efficient hydrogen peroxide (H₂O₂) production with an ozone (O₃) system. In situ activation of O₃ is achieved by the photogenerated H₂O₂, which integrates the photocatalytic hydrogen peroxide production (PHP) and advanced oxidation processes (AOPs) to form a new photocatalytic peroxone (H₂O₂/O₃) system, achieving highly efficient solar-driven degradation of recalcitrant organic pollutants in landfill leachate without the addition of external H₂O₂. The composite system exhibits efficient degradation ability for various typical pollutants in landfill leachate, among which the degradation percentage of 100 mg L⁻¹ hydroquinone (HQ) reaches 97% within 30 min. This is due to the synergistic effects of O₃ oxidation, photoactivation of O₃, activation of O₃ by EDTA-CQDs, and activation of O₃ by in situ-generated H₂O₂. In the EDTA-CQD-based H₂O₂/O₃ system, free radicals can be dynamically regenerated after the addition of pollutants, achieving sustained and efficient degradation. Therefore, in the treatment of actual leachate, the removal percentages of COD, TOC, and UV254 are nearly 90%, 70%, and 55%, respectively, demonstrating the significant advantage of this system in treating high-concentration recalcitrant organic pollutants in wastewater of complex quality. Full article

Recent publications have introduced the concept of quantum-like (QL) bits, along with their associated QL states and QL gate operations, which emerge from the dynamics of complex, synchronized networks. The present work extends these ideas to multi-level QL resources, referred to as QL dits, as higher-dimensional analogs of QL bits. We employ systems of k-regular graphs to construct QL-dits for arbitrary dimensions, where the emergent eigenspectrum of their adjacency matrices defines the QL-state space. The tensor product structure of multi-QL dit systems is realized through the Cartesian product of graphs. Furthermore, we examine the potential computational advantages of employing d-nary QL systems over two-level QL bit systems, particularly in terms of classical resource efficiency. Overall, this study generalizes the paradigm of using synchronized network dynamics for QL information processing to include higher-dimensional QL resources. Full article

Colloidal quantum dots (CQDs) have attracted significant attention in optoelectronics due to their size-tunable bandgap, high photoluminescence quantum yield, and solution processability, which enable integration into compact and energy-efficient systems. This review consolidates recent progress in multifunctional CQD-based light-emitting devices and on-chip integration strategies. This review systematically examines fundamental CQD properties (quantum confinement, carrier dynamics, and core–shell heterostructures), key synthesis methods including hot injection, ligand-assisted reprecipitation, and microfluidic flow synthesis, and device innovations such as light-emitting field-effect transistors, light-emitting solar cells, and light-emitting memristors, alongside on-chip components including ongoing electrically pumped lasers and photodetectors. This review concludes that synergies in material engineering, device design, and system innovation are pivotal for next-generation optoelectronics, though challenges such as environmental instability, Auger recombination, and CMOS compatibility require future breakthroughs in atomic-layer deposition, 3D heterostructures, and data-driven optimization. Full article

Aerial-assisted vehicular edge computing (AVEC) has emerged as a transformative approach to addressing the limitations of traditional vehicular edge computing (VEC) in dynamic vehicular environments. By integrating platforms such as unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and satellites, AVEC systems offer enhanced scalability, flexibility, and responsiveness, enabling efficient resource allocation and adaptive decision-making. This paper presents a comprehensive survey of resource allocation techniques in AVEC, addressing both traditional and reinforcement learning-based approaches. These techniques aim to optimize the allocation of bandwidth, computation, and energy resources across heterogeneous platforms, ensuring reliable and efficient operations in diverse scenarios. Additionally, the study examines key challenges inherent in AVEC, including achieving seamless interoperability among diverse platforms, addressing scalability in large-scale systems, and adapting to real-time environmental dynamics. To address these challenges, the paper proposes future research directions, such as leveraging advanced technologies like quantum computing for solving complex optimization problems, employing tiny machine learning (TinyML) to enable resource-efficient intelligence on low-power devices, and predictive task offloading to enhance proactive resource management. By presenting a detailed analysis of existing techniques and identifying critical research opportunities, this paper seeks to guide researchers and practitioners in developing more efficient, secure, and adaptive AVEC systems. The insights from this study contribute to advancing the design and deployment of resilient intelligent transportation networks, paving the way for the next generation of vehicular connectivity. Full article

In exotic atomic systems with hadronic constituent particles, it is notoriously difficult to estimate the strong-interaction correction to energy levels. It is well known that, due to the strength of the nuclear interaction, the problem cannot be solved using Wigner–Brillouin perturbation theory alone. Recently, high-angular-momentum Rydberg states of exotic atomic systems with hadronic constituents have been identified as promising candidates in the search for new physics in the low-energy sector of the Standard Model. We thus derive a generalized Deser–Trueman formula for the induced energy shift for a general hydrogenic bound state with principal quantum number n and orbital angular momentum quantum number ℓ, and we find that the energy shift is given by the formula $\delta E=2{\alpha }_{n,\ell }{\beta }_{\ell }{(a_h/a_0)}^{2\ell +1}{E}_h/n^3$, where ${\alpha }_{n,0}=1$, ${\alpha }_{n,\ell }={\prod }_{s=1}^{\ell }(s^{-2}-n^{-2})$, ${\beta }_{\ell }=(2\ell +1)/{[(2\ell +1)!!]}^2$, $E_h$ is the Hartree energy, $a_h$ is the hadronic radius and $a_0$ is the generalized Bohr radius. The square of the double factorial, ${[(2\ell +1)!!]}^2$, in the denominator implies a drastic suppression of the effect for higher angular momenta. Full article

Wireless communication applications above 300 GHz need careful analog electronics design that takes into account the frequency-dependent nature of ohmic resistance at these frequencies. The cumbersome development of electronics brings quantum optical communication solutions for the sixth generation (6G) THz band located between 300 GHz and 10 THz into focus. In this manuscript, the authors propose to replace the classical radio frequency based inner physical layer transceiver blocks used in classical channel coded short range wireless communication systems by wireless quantum optical communication concepts. In addition to discussing the resulting generic concept of the wireless quantum optical communications and illustrating optimum quantum data detection schemes, novel reduced state quantum data detection and novel Kohonen maps-based quantum data detection, will be addressed. All the considered quantum data detection schemes provide soft outputs required for the lowest possible block error ratio (BLER) at the output of the channel decoding. Furthermore, a novel polar codes design approach determining the polar sequence by appropriately combining already available polar sequences tailored for low BLER is presented for the first time after illustrating the basics of polar codes. In addition, turbo equalization for wireless quantum optical communications using polar codes will be presented, for the first time explicitly stating the generation of soft information associated with the codebits and introducing a novel scheme for the computation of extrinsic soft outputs to be used in the turbo equalization iterations. New simulation results emphasize the viability of the theoretical concepts. Full article

Blockchain technology has introduced new paradigms for identity management systems (IDMSs), enabling users to regain control over their identity data and reduce reliance on centralized authorities. In recent years, numerous blockchain-based IDMS solutions have emerged across both practical application domains and academic research. However, prior reviews often focus on single application areas, provide limited cross-domain comparison, and insufficiently address security challenges such as interoperability, revocation, and quantum resilience. This paper bridges these gaps by presenting the first comprehensive survey that examines IDMSs from three complementary perspectives: (i) historical evolution from centralized and federated models to blockchain-based decentralized architectures; (ii) a cross-domain taxonomy of blockchain-based IDMSs, encompassing both general-purpose designs and domain-specific implementations; and (iii) a security analysis of threats across the full identity lifecycle. Drawing on a systematic review of 47 studies published between 2019 and 2025 and conducted in accordance with the PRISMA methodology, the paper synthesizes academic research and real-world deployments to identify unresolved technical, economic, and social challenges, and to outline directions for future research. The findings aim to serve as a timely reference for both researchers and practitioners working toward secure, interoperable, and sustainable blockchain-based IDMSs. Full article