Search Results (453)

Magnetocardiography (MCG) provides a non-invasive, contactless technique for evaluating the magnetic fields generated by cardiac electrical activity, offering unique spatial insights into cardiac electrophysiology. However, conventional MCG systems depend on superconducting quantum interference devices that require cryogenic cooling and magnetic shielded environments, posing considerable impediments to widespread clinical adoption. In this study, we present a novel MCG system utilizing a high-sensitivity, wide-dynamic-range magnetoresistive sensor array operating at room temperature. To mitigate environmental interference, identical sensors were deployed as reference channels, enabling adaptive noise cancellation (ANC) without the need for traditional magnetic shielding. MCG recordings were obtained from 40 healthy participants, with signals processed using ANC, R-peak-synchronized averaging, and Bayesian spatial signal separation. This approach enabled the reliable detection of key cardiac components, including P, QRS, and T waves, from the unshielded MCG recordings. Our findings underscore the feasibility of a cost-effective, portable MCG system suitable for clinical settings, presenting new opportunities for noninvasive cardiac diagnostics and monitoring. Full article

This review article aims to provide an overview of superconducting magnetic quantum sensors and their applications in the biomedical field, particularly in the neurological field. These quantum sensors are based on superconducting quantum interference devices (SQUIDs), the operating principles of which will be presented along with the most relevant characteristics. Emphasis will be placed on the magnetic flux and magnetic field noise, which are essential for applications, especially brain investigations requiring ultra-high magnetic field sensitivity. The main configurations of SQUID magnetometers used for highly sensitive applications will be shown, stressing their design aspects. In particular, the configurations based on the superconducting flux transformer and the multiloop will be explained. We will discuss the most critical application of SQUID magnetometers, magnetoencephalography, which measures the weak magnetic signals produced by neuronal currents. Starting from the realization of a multichannel system for magnetoencephalography, we will present an accurate comparison with recent systems using optically pumped magnetometers. Finally, we will discuss the main clinical applications of magnetoencephalography. Full article

In this work we study the spectral dimensionality of spacetime around a radiating Schwarzschild black hole using a recently introduced formalism of quantum gravity, where the alterations of the gravitational field produced by the radiation are represented on an extended manifold, and describe a non-commutative and nonlinear quantum algebra. The relation between classical and quantum perturbations of spacetime can be measured by the parameter $z\ge 0$. In this work we have found that when $z=(1+\sqrt{3})/2\simeq 1.3660$, a relativistic observer approaching the Schwarzschild horizon perceives a spectral dimension $N\left(z\right)=4\left[\theta \left(z\right)-1\right]\simeq 2.8849$, which is related to quantum gravitational interference effects in the environment of the black hole. Under these conditions, all studied Schwarzschild black holes with masses ranging from the Planck mass to ${10}^{46}$ times the Planck mass present the same stability configuration, which suggests the existence of a universal property of these objects under those particular conditions. The difference from the spectral dimension previously obtained at cosmological scales leads to the conclusion that the spacetime dimensionality is scale-dependent. Another important result presented here is the fundamental alteration of the effective gravitational potential near the horizon due to Hawking radiation. This quantum phenomenon prevents the potential from diverging to negative infinity as the observer approaches the Schwarzschild horizon. Full article

This article reconsiders the double-slit experiment by establishing a new type of relationship between it and the concept of entanglement. While the role of entanglement in the double-slit experiment has been considered, this particular relationship appears to have been missed in preceding discussions of the experiment, even by Bohr, who extensively used it to support his argument concerning quantum physics. The main reason for this relationship is the different roles of the diaphragm with slits in two setups, S1 and S2, defining the double-slit experiment as a quantum experiment. In S1, in each individual run of the experiment one can in principle (even if not actually) know throughout which slit the quantum object considered has passed; in S2 this knowledge is in principle impossible, which impossibility is coextensive with the appearance of the interference pattern, once a sufficient number of individual runs of the experiment have taken place. The article offers the following argument based on two new concepts, an “experimentally quantum object” and an “ontologically quantum object.” In S1 the diaphragm can be treated as part of an observational arrangement and thus considered as a classical object, while the object passing through one or the other slit is considered as an “ontologically quantum object,” defined as an object necessary to establish a quantum phenomenon. By contrast, in S2, the diaphragm can, via the concept of Heisenberg-von-Neumann cut, be treated as an “experimentally quantum object,” defined as an object treatable by quantum theory, even while possibly being an ontologically classical object. This interaction is not an observation but a quantum entanglement between these two quantum objects, one ontologically and one experimentally quantum. This argument is grounded in a particular interpretation of quantum phenomena and quantum theory, which belongs to the class of interpretations designated here as “reality without realism” (RWR) interpretations. The article also argues that wave-particle complementarity, with which the concept of complementarity is often associated, plays little, if any, role in quantum physics, or in Bohr’s thinking, and may be misleading in considering the double-slit experiment, often explained by using this complementarity. Full article

In this paper, the first demonstration of a highly strained In_0.8Ga_0.2As/In_0.2Ga_0.8Sb type-II superlattice structure grown on InAs substrates by molecular beam epitaxy (MBE) for long-wavelength infrared detection was reported. Novel methodologies were developed to optimize the As and Sb flux growth conditions. The quality of the epitaxial layer was characterized using multiple analytical techniques, including differential interference contrast microscopy, atomic force microscopy, high-resolution X-ray diffraction, and high-resolution transmission electron microscopy. The high-quality superlattice structure, with a total thickness of 1.5 μm, exhibited exceptional surface morphology with a root-mean-square roughness of 0.141 nm over a 5 × 5 μm² area. Single-element devices with PIN architecture were fabricated and characterized. At 77 K, these devices demonstrated a 50% cutoff wavelength of approximately 12.1 μm. The long-wavelength infrared PIN devices exhibited promising performance metrics, including a dark current density of 7.96 × 10⁻² A/cm² at −50 mV bias and a high peak responsivity of 4.90 A/W under zero bias conditions, both measured at 77 K. Furthermore, the devices achieved a high peak quantum efficiency of 65% and a specific detectivity (D*) of 2.74 × 10¹⁰ cm·Hz^1/2/W at the peak responsivity wavelength of 10.7 µm. These results demonstrate the viability of this material system for long-wavelength infrared detection applications. Full article

The chiral nonlinear Schrödinger equation (CNLSE) serves as a simplified model for characterizing edge states in the fractional quantum Hall effect. In this paper, we leverage the generalization and parameter inversion capabilities of physics-informed neural networks (PINNs) to investigate both forward and inverse problems of 1D and 2D CNLSEs. Specifically, a hybrid optimization strategy incorporating exponential learning rate decay is proposed to reconstruct data-driven solutions, including bright soliton for the 1D case and bright, dark soliton as well as periodic solutions for the 2D case. Moreover, we conduct a comprehensive discussion on varying parameter configurations derived from the equations and their corresponding solutions to evaluate the adaptability of the PINNs framework. The effects of residual points, network architectures, and weight settings are additionally examined. For the inverse problems, the coefficients of 1D and 2D CNLSEs are successfully identified using soliton solution data, and several factors that can impact the robustness of the proposed model, such as noise interference, time range, and observation moment are explored as well. Numerical experiments highlight the remarkable efficacy of PINNs in solution reconstruction and coefficient identification while revealing that observational noise exerts a more pronounced influence on accuracy compared to boundary perturbations. Our research offers new insights into simulating dynamics and discovering parameters of nonlinear chiral systems with deep learning. Full article

In this work, we conduct a sentiment analysis of English-language reviews using a quantum-like (wave-based) model of text representation. This model is explored as an alternative to machine learning (ML) techniques for text classification and analysis tasks. Special attention is given to the problem of segmenting text into semantic units, and we illustrate how the choice of segmentation algorithm is influenced by the structure of the language. We investigate the impact of quantum-like semantic interference on classification accuracy and compare the results with those obtained using classical probabilistic methods. Our findings show that accounting for interference effects improves accuracy by approximately $15\%$. We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. The results demonstrate that the quantum-like model can serve as a viable alternative or complement to traditional ML approaches. The model achieves classification precision and recall scores of around 0.8. Furthermore, the classification algorithm is readily amenable to optimization: the proposed procedure reduces the estimated computational complexity from $O\left(n^2\right)$ to $O\left(n\right)$. Full article

Recent achievements in ultrafast spin physics have enabled the use of heterostructures composed of ferromagnetic (FM)/non-magnetic (NM) thin layers for terahertz (THz) generation. The mechanism of THz emission from FM/NM multilayers has been typically ascribed to the inverse spin Hall effect (ISHE). In this work, we probe the mechanism of the ISHE by inserting a second ferromagnetic layer in the form of an alloy between the FM/NM system. In particular, by utilizing the co-sputtering technique, we fabricate Fe/L1₀-FePt/Pt ultra-thin heterostructures. We successfully grow the tetragonal phase of FePt (L1₀-phase) as revealed by X-ray diffraction and reflection techniques. We show the strong magnetic coupling between Fe and L1₀-FePt using magneto-optical and Superconducting Quantum Interference Device (SQUID) magnetometry. Subsequently, by utilizing THz time domain spectroscopy technique, we record the THz emission and thus we the reveal the efficiency of spin-to-charge conversion in Fe/L1₀-FePt/Pt. We establish that Fe/L1₀-FePt/Pt configuration is significantly superior to the Fe/Pt bilayer structure, regarding THz emission amplitude. The unique trilayer structure opens new perspectives in terms of material choices for the future spintronic THz sources. Full article

The wave–particle duality is the quintessence of quantum mechanics. This duality gives rise to distinct behaviors depending on the experimental setup, with the system exhibiting either wave-like or particle-like properties, depending on whether the focus is on interference (wave) or trajectory (particle). In the interaction with a beam splitter, photons with particle behavior can transform into a wave behavior and vice versa. In Wheeler’s delayed-choice gedanken experiment, this interaction is delayed so that the wave that initially travels through the interferometer can become a particle, avoiding the interaction. We show that this contradiction can be resolved using polarized entangled photon pairs. An analysis of Shannon’s entropy supports this proposal. Full article

Millimeter-wave (mmWave) antennas and antenna arrays have gained significant attention due to their pivotal role in emerging wireless communication, sensing, and imaging technologies. With the rapid deployment of 5G and the transition toward 6G networks, the demand for compact, high-gain, and reconfigurable mmWave antennas has intensified. This article highlights recent advancements in mmWave antenna technologies, including hybrid beamforming using phased arrays, dynamic beam-steering enabled by liquid crystal and MEMS-based structures, and high-capacity MIMO architectures. We also examine the integration of metamaterials and metasurfaces for miniaturization and gain enhancement. Applications covered include wearable antennas with low-SAR textile substrates, conformal antennas for UAV-based mmWave relays, and high-resolution radar arrays for autonomous vehicles. The study further analyzes innovative fabrication methods such as inkjet and aerosol jet printing, micromachining, and laser direct structuring, along with advanced materials like Kapton, PDMS, and graphene. Numerical modeling techniques such as full-wave EM simulation and machine learning-based optimization are discussed alongside experimental validation approaches. Beyond communications, we assess mmWave systems for biomedical imaging, security screening, and industrial sensing. Key challenges addressed include efficiency degradation at high frequencies, interference mitigation in dense environments, and system-level integration. Finally, future directions, including AI-driven design automation, intelligent reconfigurable surfaces, and integration with quantum and terahertz technologies, are outlined. This comprehensive synthesis aims to serve as a valuable reference for advancing next-generation mmWave antenna systems. Full article

The current study presents the results of a methodical investigation into the ionization of rare gas atoms, specifically focusing on argon. In this study, two configurations are examined: ionization via a near-infrared (NIR) laser field alone, and ionization caused by extreme ultraviolet (XUV) radiation in the presence of a strong, synchronized NIR pulse. The theoretical investigation is conducted using an ab initio method to solve the time-dependent Schrödinger equation within the single active electron (SAE) approximation. The simulation results show a sequence of above-threshold ionization (ATI) peaks that shift to lower energies with increasing laser intensity. This behavior reflects the onset of the Stark effect, which modifies atomic energy levels and increases the number of photons required for ionization. An examination of the two-color photoionization spectrum, which includes sideband structures and harmonic peaks, shows how the ionization probability is redistributed between the direct path (single XUV photon absorption) and sideband pathways (XUV ± n × IR) as the intensity of the infrared field increases. Quantum interference between continuum states is further revealed by the photoelectron angular distribution, clearly indicating the control of ionization dynamics by the IR field. Full article

We report on asymmetrically shaped Fano resonances in Al_0.2Ga_0.8N/GaN-based quantum cascade structures. In order to observe this type of resonance in electro-luminescence, a spectrally narrow feature must interact with a broad, quasi-continuous emission. While the narrow waveform is provided by the GaN-based LO-phonon at 92 meV (13.5 µm, 741 cm⁻¹), the broad peak consists of overlapping inter-subband transitions between several higher-order excited states ranging from 80 to 300 meV and the ground state. Through the interference of these spectrally dissimilar peaks, a typical, asymmetric Fano line shape is generated. Full article

Superparamagnetic iron oxide nanoparticles (SPIONs) have gained significant attention for Magnetic Fluid Hyperthermia (MFH)-based cancer therapy. However, achieving high heating efficiency under a biologically safe Alternating Magnetic Field (AMF) remains a challenge. This study investigates the synthesis and optimization of SPIONs encapsulated in TPGS-stabilized PLGA nanoparticles (TPS-NPs) using a modified single emulsion solvent evaporation (M-SESE) method. The aim was to achieve efficient magnetic heating under biologically safe AMF conditions while maintaining biocompatibility and colloidal stability, making these magnetic nanoplatforms suitable for MFH-based cancer treatment. TPS-NPs were characterized using various techniques, including Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), Transmission Electron Microscopy (TEM), and Superconducting Quantum Interference Device (SQUID) magnetometry, to evaluate their hydrodynamic size (Dh), zeta potential (ζ), encapsulation efficiency, and superparamagnetic properties. Calorimetric MFH studies demonstrated superior heating efficiency, with Specific Absorption Rate (SAR) and Intrinsic Loss Power (ILP) values optimized at an AMF of 4.1 GAm⁻¹s⁻¹, remaining within Hergt’s biological safety limit (~5 GAm⁻¹s⁻¹). These findings suggest that SPION-encapsulated TPS-NPs exhibit enhanced heat induction, making them promising candidates for MFH-based cancer therapy. The study highlights their potential as multifunctional nanoplatforms for magnetic hyperthermia therapy, paving the way for clinical translation in oncology for advanced cancer treatment. Full article

Nanotechnology, specifically magnetic nanoparticles (MNPs), is revolutionizing cancer treatment. Magnetic hyperthermia is a treatment that, using MNPs, can selectively kill cancer cells without causing damage to the surrounding tissues. Background/Objectives: This work aimed to analyze how the synthesis conditions, namely, how the pH of the reaction can influence the magnetic properties of Fe₃O₄ nanoparticles for magnetic hyperthermia, using the hydrothermal synthesis. Methods: For the hydrothermal synthesis, FeCl₃·6H₂O and FeCl₂·4H₂O were mixed with different quantities of NaOH to adjust the pH. After obtaining a black precipitate, the samples were placed in an autoclave at 200 °C for 60 h, followed by a washing and drying phase. The obtained MNPs were analyzed using X-Ray Diffraction (XRD), Transmission Electron Microscopy, a Superconducting Quantum Interference Device, Specific Absorption Rate analysis, and cytotoxicity assays. Results: Different MNPs were analyzed (9.06 < pH < 12.75). The XRD results showed the presence of various iron oxide phases (magnetite, maghemite, and hematite), resulting from the oxidization of the iron phases present in the autoclave. In terms of the average particle size, it was verified that, by increasing the pH value, the size decreases (from 53.53 nm to 9.49 nm). Additionally, MNPs possess a superparamagnetic behaviour with high SAR values (above 69.3 W/g). Conclusions: It was found that the pH of the reaction can influence the size, morphology, magnetization, and thermal efficiency of the MNP. The MNP with the highest composition of Fe₃O₄ was synthesized with a pH of 12.75, with a cubic morphology and a SAR value of 92.7 ± 3.2 W/g. Full article

In multi-criteria group decision making, decision makers are commonly regarded as independent. However, in practice, heterogeneous backgrounds and complex cognitive processes lead to mutual interference among their judgments. To address this gap, a novel multi-criteria quantum group decision-making model is proposed that explicitly incorporates opinion interference effects. First, type-2 fuzzy numbers are employed to represent evaluation information, and a specialized Euclidean distance measure for them is introduced. Second, an extended distance-based criteria importance through an inter-criteria correlation method incorporating Deng entropy is developed to derive robust criteria weights under uncertainty. Third, the TODIM method integrates cumulative prospect theory to capture decision makers’ risk perceptions and computes prospect-based dominance degrees. Fourth, a quantum-inspired aggregation mechanism models the mutual interference in group opinions. Finally, a case study on FinTech startup investment demonstrates the model’s practical applicability, while sensitivity analysis and comparisons to established methods confirm its robustness and effectiveness. Full article