Search Results (2,142)

Quantum energy teleportation (QET) has been proposed to overcome the restrictions of strong local passivity (SLP) and to facilitate energy transfer in quantum systems. Traditionally, QET has only been considered under strict constraints, including the requirements that the initial state be the ground state of an interacting Hamiltonian, that Alice’s measurement commute with the interaction terms, and that entanglement be present. These constraints have significantly limited the broader applicability of QET protocols. In this work, we demonstrate that SLP can arise beyond these conventional constraints, establishing the necessity of QET in a wider range of scenarios for local energy extraction. This leads to a more flexible and generalized framework for QET. Furthermore, we introduce the concept of a “local effective Hamiltonian,” which eliminates the need for optimization techniques in determining Bob’s optimal energy extraction in QET protocols. As an additional advantage, the amount of energy that can be extracted using our new protocol is amplified to be 7.2 times higher than that of the original protocol. These advancements enhance our understanding of QET and extend its broader applications to quantum technologies. To support our findings, we implement the protocol on quantum hardware, confirming its theoretical validity and experimental feasibility. Full article

Entangled photons are essential for photonic quantum technologies. Their generation typically relies on spontaneous parametric down-conversion, but conventional nonlinear crystals are bulky and hard to integrate on chips. Rhombohedral-stacked MoS₂ combines a high refractive index, large second-order nonlinearity, and flexibility for heterogeneous integration, making it a promising platform for integrated quantum photonics. However, the typical thin-film form of 3R-MoS₂ restricts the effective nonlinear interaction length, limiting entanglement generation efficiency in practical devices. To overcome this, phase-matching strategies in integrated waveguides are required but have so far remained undeveloped. Here, we introduce a waveguide-integrated 3R-MoS₂ platform with periodic grooves to achieve quasi-phase matching, enhancing down-conversion efficiency. Leveraging ${\chi }^{\left(2\right)}$ tensor symmetries and orthogonal waveguide modes, the design efficiently generates entangled photons, providing a compact, scalable route toward 2D-material-based integrated quantum photonic circuits. Full article

We present a two-mode squeezed Jaynes–Cummings model, built upon the formalism of pair coherent states (PCSs), to investigate the dynamics of a two-level atom interacting with a two-mode quantized field. By solving the time-dependent Schrödinger equation under the rotating-wave approximation, we elucidate the system’s quantum evolution, with particular emphasis on how the squeezing degree and photon number difference modulate atomic population inversion and entanglement. We further quantify the nonclassical traits of the two-mode squeezed PCSs via Mandel’s parameter and the violation of the Cauchy–Schwarz inequality, highlighting their sensitivity to model parameters. These findings illuminate the subtle interplay of squeezing, photon statistics, and entanglement in advanced quantum optical systems. Full article

To address the problem of the bottom velocity being directly affected by the time-varying ocean currents when DVL operates in the water observation mode, it cannot be directly used for combined SINS/DVL navigation. Existing methods generally approximate small-scale, short-term currents as constant; however, this assumption is inconsistent with reality over longer durations. When the conventional Kalman filter (KF) algorithm incorporates currents into the state vector, their velocities become entangled with the SINS errors, limiting estimation accuracy. This paper proposes an augmented observation algorithm (AOA) that achieves error decoupling by enhancing DVL observation and deriving the observable current velocity equation without needing external observation information. This approach effectively estimates time-varying currents. The results from simulations and shipboard tests show that, compared to the reference algorithm (Augmented Observation Quantity Filtering algorithm (AOQ)), the proposed AOA significantly decreases the root mean square error (RMSE) of time-varying current velocity estimation by more than 67%. Additionally, the RMSE of the positioning accuracy of the combined SINS/DVL navigation is improved by over 68%. Full article

Hydroelectricity energy harvesting has emerged as a promising, eco-friendly alternative for addressing the growing demand for sustainable energy solutions. In this study, we present a hydroelectricity energy harvester fabricated from shredded waste printing paper (WPP), offering a novel waste-to-energy conversion strategy that requires neither material purification nor complex processing. The device leverages the randomly entangled fiber network of WPP to facilitate capillary-driven moisture diffusion and electric double layer (EDL) formation, thereby enabling efficient electrokinetic energy conversion. The random arrangement of WPP fibers increases the effective EDL area, allowing the waste printing paper generator (WPPG) to achieve an open-circuit voltage of 0.372 V and a short-circuit current of 135 μA at room temperature under optimized electrolyte conditions. This study demonstrates that carbon-black-coated WPP can be effectively upcycled into a high-performance hydroelectricity generator, exhibiting excellent electrical output at ambient conditions. By combining material recycling with efficient energy conversion, this system establishes a practical and sustainable pathway for distributed power generation. Overall, this work not only presents an environmentally responsible approach to device fabrication but also highlights that hydroelectricity energy harvesting using WPPG represents a promising alternative energy route for future applications. Full article

This article reports on an international project involving higher education institutions working in partnership with third sector organizations, to explore facilitating children and young people in expressing their concerns and ideas about climate change directly to decision-makers. Children and young people were invited to engaged in ‘artivism’ (the use of art for activism) to create exhibitions for policymakers and business leaders in Scotland, Kenya and Nigeria. Through co-creation, underpinned by the principles of sustainable pedagogies, the project team created spaces and research methods exploring how artivism for climate action can be supported and enacted. The focus of this article is on the role of adults as local facilitators, educators, research team members, and exhibition attendees in facilitating, listening to, and engaging with children and young people as they express themselves and generate climate action through their artivism. It illustrates how adults enacting sustainable pedagogies, care and compassion are critical, and how arts-based education for sustainability involves pedagogies of collaboration and co-creation which entangle us with people, places, ideas, languages, materials and environments beyond our immediate educational settings. Full article

Quantum machine learning (QML) integrates quantum computing with classical machine learning. Within this domain, QML-CQ classification tasks, where classical data is processed by quantum circuits, have attracted particular interest for their potential to exploit high-dimensional feature maps, entanglement-enabled correlations, and non-classical priors. Yet, practical realizations remain constrained by the Noisy Intermediate-Scale Quantum (NISQ) era, where limited qubit counts, gate errors, and coherence losses necessitate frugal, noise-aware strategies. The Data Re-Uploading (DRU) algorithm has emerged as a strong NISQ-compatible candidate, offering universal classification capabilities with minimal qubit requirements. While DRU has been experimentally demonstrated on ion-trap, photonic, and superconducting platforms, no implementations exist for spin-based quantum processing units (QPU-SBs), despite their scalability potential via CMOS-compatible fabrication and recent demonstrations of multi-qubit processors. Here, we present a pulse-level, noise-aware DRU framework for spin-based QPUs, designed to bridge the gap between gate-level models and realistic spin-qubit execution. Our approach includes (i) compiling DRU circuits into hardware-proximate, time-domain controls derived from the Loss–DiVincenzo Hamiltonian, (ii) explicitly incorporating coherent and incoherent noise sources through pulse perturbations and Lindblad channels, (iii) enabling systematic noise-sensitivity studies across one-, two-, and four-spin configurations via continuous-time simulation, and (iv) developing a noise-aware training pipeline that benchmarks gate-level baselines against spin-level dynamics using information-theoretic loss functions. Numerical experiments show that our simulations reproduce gate-level dynamics with fidelities near unity while providing a richer error characterization under realistic noise. Moreover, divergence-based losses significantly enhance classification accuracy and robustness compared to fidelity-based metrics. Together, these results establish the proposed framework as a practical route for advancing DRU on spin-based platforms and motivate future work on error-attentive training and spin–quantum-dot noise modeling. Full article

The article aims is to make the case for an essential entanglement between faith and understanding, and to show how Wittgenstein’s philosophy, like that of Socrates’, was informed and/or underpinned by such an entanglement. Centrally, the article argues that Wittgenstein’s critique of metaphysical uses of words and the subsequent turn from explanation to description in his Philosophical Investigations have crucial affinities with Socrates’ claim, in the Apology, to “human wisdom”. The first part of the article comprises a somewhat novel reading of Plato’s Apology, while the second part focuses on Wittgenstein and on capturing the entanglement between faith and understanding shared by the two. Full article

This conceptual paper presents a framework for understanding how technology can help transform formal education by blurring five foundational boundaries: time and space, knowledge, pedagogy, hierarchy, and community. It is grounded in the interactions between technology and key schooling components, namely, learners, instructors, peers, and content, and promotes thinking about technology integration in schools not merely as instrumental, but as a driver for educational change. We apply the framework to three reported cases of technology integration in different educational contexts, analyzing each in terms of its potential to disrupt traditional boundaries. Through this analysis, we illustrate how certain uses of technology may enable deeper pedagogical shifts and foster more equitable, flexible, and collaborative learning settings. This illustrates the power of the proposed framework in allowing a nuanced understanding of technology integration, and the entanglement of pedagogy and technology for meaningful changes to occur. The paper concludes with recommendations for educators, policymakers, researchers, and designers seeking to promote boundary-blurring innovation. Ultimately, we advocate for a shift in discourse—from using technology to optimize education, to using it to reimagine its foundational structures. Full article

This paper presents a semi-quantum secret sharing (SQSS) protocol based on three-particle W states, designed for efficient and secure secret sharing in quantum-resource-constrained scenarios. In the protocol, a fully quantum-capable sender encodes binary secrets using W, while receivers with limited quantum capabilities reconstruct the secret through collaborative Z basis measurements and classical communication, ensuring no single participant can obtain the complete information independently. The protocol employs a four-state decoy photon technique ($\left\{\right|0⟩,|1⟩,|+⟩,|-⟩\}$) and position randomization, combined with photon number splitting (PNS) and wavelength filtering (WF) technologies, to resist intercept–resend, entanglement–measurement, and double controlled-NOT(CNOT) attacks. Theoretical analysis shows that the detection probability of intercept–resend attacks increases exponentially with the number of decoy photons (approaching 1). For entanglement–measurement attacks, any illegal operation by an attacker introduces detectable quantum state disturbances. Double CNOT attacks are rendered ineffective by the untraceability of particle positions and mixed-basis strategies. Leveraging the robust entanglement of W states, the protocol proves that the mutual information between secret bits and single-participant measurement results is strictly zero, ensuring lossless reconstruction only through authorized collaboration. Full article

Optimizing Boolean function components to have the minimum number of inputs in order to reduce the memory space required during these functions in computing devices is a significant demand. This paper proposes a quantum computation approach based on the degree-of-entanglement quantum computation model to estimate the number of junta variables of an unknown Boolean function presented through an oracle. The time complexity of the developed quantum approach is independent of the number of inputs and depends on an allowable assigned error $ϵ$. Thus, the time complexity of the developed algorithm is $O\left({ϵ}^{-2}\right)$, compared to $O\left(2^{n+1}\right)$ in the traditional approach. Also, the memory space of the developed approach is linear, $O(2n+4)$, in terms of the number of inputs compared to the exponential memory space $O\left(2^{n+1}\right)$ using the traditional approach. Therefore, the developed quantum approach has exponential supremacy in comparison to the traditional approach. The developed approach was implemented practically using both the Qiskit simulator and the IBM real quantum computer. The obtained results expose high statistical fidelities between the empirical and theoretical results. Full article

This paper analyzes the entangled relationship between feline divinanimality and extraterrestrial ontology, which has spawned a New Religious Movement (NRM) called Lyran Starseeds, centered upon a human–feline interspecies coevolution and exogenesis. Alongside offering a detailed exposition of this new intergalactic creature exotheology, I will also analyze the many ways it has been inspired by historical feline veneration and contemporary science fiction film and literature. I shall argue that both offer Lyran Starseeds an epistemological framework to situate and legitimize their intergalactic feline ontology. Full article

Local droplet etching and subsequent refilling enables the fabrication of highly symmetric quantum dots with low fine structure splitting, suitable for generating polarization entangled photons. While well established in GaAs/Al_xGa_1−xAs, this approach does not yield emission in the telecom bands required for low loss fiber-based quantum communication. To achieve emission at 1.55 μm, local droplet etching must be adapted to alternative material platforms such as InP. Here, we systematically investigate how the etching material deposition rate and etching time influence nanohole morphology in In_0.52Al_0.48As layers lattice-matched to InP. In the first experiment, InAl was deposited at fluxes of 0.2–4.0 Å s⁻¹ at $T_{etch} = 350 °\mathrm{C}$ and 460 °C. Lower fluxes produced nanoholes with lower density and larger ring diameters, indicating fewer and larger initial droplets, consistent with scaling theory. The average nanohole diameter decreased monotonically with increasing flux, whereas the average depth showed no clear dependence on flux. In the second experiment, etching times of 30–600 s were tested for InAl, In, and Al droplets. Average nanohole diameters remained constant for Al across all etching times, but decreased for In and InAl with increasing etching time, suggesting sidewall redeposition during etching. For all droplet types, depths peaked at intermediate times and decreased for prolonged etching, consistent with material diffusion into the nanohole after droplet consumption. Full article

One-dimensional (1D) nanowires represent a critical class of nanomaterials with extensive applications in biosensing, biomedicine, bioelectronics, and energy harvesting. In materials science, accurately extracting their morphological and structural features is essential for effective image segmentation. However, 1D nanowires frequently appear in dispersed or entangled configurations, often with blurred backgrounds and indistinct boundaries, which significantly complicates the segmentation process. Traditional threshold-based methods struggle to segment these structurally complex nanowires with high precision. To address this challenge, we propose a wavelet-based Bilateral Segmentation Network named WaveBiSeNet, to which a Dual Wavelet Convolution Module (DWCM) and a Flexible Upsampling Module (FUM) are introduced to enhance feature representation and improve segmentation accuracy. In this study, we benchmarked WaveBiSeNet against ten segmentation models on a peptide nanowire image dataset. Experimental results demonstrate that WaveBiSeNet achieves, mIoU of 77.59%, an accuracy of 89.95%, an F1 score of 87.22%, and a Kappa coefficient of 74.13%, respectively. Compared to other advanced models, our proposed model achieves better segmentation performance. These findings demonstrate that WaveBiSeNet is an end-to-end deep segmentation network capable of accurately analyzing complex 1D nanowire structures. Full article

We investigate the spatial structure of quantum entanglement in one- and two-dimensional lattice systems containing structural defects, using the Time-Dependent Quantum Monte Carlo (TDQMC) method. By constructing reduced density matrices from ensembles of guide waves, we resolve spatial variations in both Coulomb-mediated entanglement and coherence without requiring full many-body wavefunctions. This approach reveals localized regions, entanglement islands, where quantum correlations are enhanced or suppressed due to the presence of vacancies or interaction inhomogeneities. In 1D systems, entanglement tends to concentrate near defects, while in 2D systems, we observe bridge-like and radially symmetric domains. Our results demonstrate that TDQMC offers a scalable and physically transparent framework for real-space quantum information analysis, with implications for information transfer in atomic-size structures, quantum materials, entanglement-based sensing, and coherent state engineering. Full article