Physical Quantities Research Articles

The study of fracional anomalous diffusion laws on the hypersphere

In this work, we present an extended mathematical study of the fractional anomalous diffusion of a target particle which moves on a curved surface. To do explicit calculations, we assumed that this particle moves on a hypersphere of radius R. We analyzed the particle dynamics using a generalized fractional Langevin equation approach, based on the Caputo fractional derivative and Laplace transform techniques. We derived three physical quantities:the mean square displacement (MSD), the time diffusion coefficient (TDC), and the velocity autocorrelation function (VACF). We performed exact calculations of their temporal evolution by selecting power-law and Dirac delta memory functions. The results obtained are expressed in terms of Mittag-Leffler-type functions. The introduction of the fractional derivative affected the behavior of balistic regime. We plotted the dynamic quantities for different values fractional derivative order and analyzed their influence on diffusion scaling laws.

Positivity properties of scattering amplitudes

Abstract We investigate positivity properties in quantum field theory (QFT). We provide evidence, and in some case proofs, that many building blocks of scattering amplitudes, and in some cases the full amplitudes, satisfy an infinite number of positivity conditions: the functions, as well as all their signed derivatives, are non-negative in a specified kinematic region. Such functions are known as completely monotonic (CM) in the mathematics literature. A powerful way to certify complete monotonicity is via integral representations. We thus show that it applies to planar and non-planar Feynman integrals possessing a Euclidean region, as well as to certain Euler integrals relevant to cosmological correlators and stringy integrals. This implies in particular that many basic building blocks appearing in perturbation theory, such as master integrals, can be chosen to be completely monotone. We also discuss two pathways for showing complete monotonicity for full amplitudes. One is related to properties of the analytic S-matrix. The other one is a close connection between the CM property and Positive Geometry. Motivated by this, we investigate positivity properties in planar maximally supersymmetric Yang-Mills theory. We present evidence, based on known analytic multi-loop results, that the CM property extends to several physical quantities in this theory. This includes the (suitably normalized) finite remainder function of the six-particle maximally-helicity-violating (MHV) amplitude, four-point scattering amplitudes on the Coulomb branch, four-point correlation functions, as well as the angle-dependent cusp anomalous dimension. Our findings are however not limited to supersymmetric theories. It is shown that the CM property holds for the QCD and QED cusp anomalous dimensions, to three and four loops, respectively. We comment on open questions, and on possible numerical applications of complete monotonicity.

Influence Mechanism of Vertical Mirror Symmetry on Out-of-Plane Dielectric Properties in 2D Materials.

In vertically integrated transistor structures, understanding the out-of-plane dielectric properties of 2D materials is crucial. We performed first-principles calculations to investigate the out-of-plane dielectric properties, including electronic and ionic polarization, of three types of 2D materials: transition metal dichalcogenides MX2 (M = Mo, W; X = S, Se, Te), transition metal halide nitrides MNX (M = Ti, Zr, Hf; X = Cl, Br), and MF4 (M = Sn, Pb). We identified a suppression mechanism for ionic polarization caused by vertical mirror symmetry, which becomes more pronounced with higher structural symmetry and atomic coordination. This mechanism ultimately reduces the out-of-plane ionic contribution of 2D MX2 to nearly zero. Using the classical spring oscillator model and second-order perturbation theory, we identified relevant physical quantities to specifically analyze the variation of the dielectric constant. This study provides a framework for analyzing 2D materials' dielectric properties and guides the design of novel dielectric materials.

BEACON: JWST NIRCam Pure-parallel Imaging Survey. I. Survey Design and Initial Results

Abstract We introduce the Bias-free Extragalactic Analysis for Cosmic Origins with NIRCam (BEACON) survey, a JWST Cycle 2 program allocated up to 600 pure-parallel hours of observations. BEACON explores high-latitude areas of the sky with JWST/NIRCam over ∼100 independent sight lines, totaling ∼0.3 deg2, reaching a median F444W depth of ≈28.2 AB mag (5σ). Based on existing JWST observations in legacy fields, we estimate that BEACON will photometrically identify 25–150 galaxies at z > 10 and 500–1000 at z ∼ 7–10 uniquely enabled by an efficient multiple filter configuration spanning 0.9–5.0 μm. The expected sample size of z > 10 galaxies will allow us to obtain robust number density estimates and to discriminate between different models of early star formation. In this paper, we present an overview of the survey design and initial results using the first 19 fields. We present 129 galaxy candidates at z ≳7 identified in those fields, including 11 galaxies at z ≳10 and several UV-luminous (M UV < −21 mag) galaxies at z ∼ 8. The number densities of z < 13 galaxies inferred from the initial fields are overall consistent with those in the literature. Despite reaching a considerably large volume (∼105 Mpc3), however, we find no galaxy candidates at z > 13, providing us with a complimentary insight into early galaxy evolution with minimal cosmic variance. We publish imaging and catalog data products for these initial fields. Upon survey completion, all BEACON data will be coherently processed and distributed to the community along with catalogs for redshift and other physical quantities.

Mechanically Adaptive, Self-Adhesive, Conductive, Cross-Linked Interpenetrating Zwitterionic Hydrogel Sensor for Simultaneous Wound Healing and Monitoring.

Hydrogel-based flexible biosensors can monitor biological parameters by responding to changes in the external environment, such as humidity, temperature, pH value, etc., which are converted into electrical signals or other measurable physical quantities. However, balancing biosensors' mechanical, adhesion, and electrical properties is challenging. Here, we design a multifunctional zwitterionic hydrogel-based biosensor with a cross-linked interpenetrating network structure, which consists of covalent and various noncovalent interactions, creating synergistic effects. The unique structure endows the hydrogel with excellent mechanical properties (0.13 ± 0.03 MPa), mechanical stability (10 cycles), and robust bonding strength (32 ± 2 KPa). Remarkably, the synergistic effect gives the hydrogels high conductivity (4.01 ± 0.2 S/m) and sensing ability (GF = 6.28). Noticeably, this synergistic effect improves the comprehensive performance of traditional biosensors and simultaneously endows them with wound-healing monitoring functions. Therefore, multifunctional and high-performance hydrogel-based flexible biosensors display great potential for application in intelligent wound management.

Convective heat transfer for Maxwell hybrid (Cu–Al2O3) nanofluid flow having Darcy–Forchheimer’s porous medium over a stretchable cylindrical pipe

This paper investigates the rheological characteristics of Maxwell hybrid nanoliquid via Darcy–Forchheimer’s permeable medium overtop a stretchable cylindrical surface. Hybrid nanofluid is analyzed with regard to boundary layer description along with convective boundary conditions. The hybrid nanoliquid under investigation is fabricated by the integration of copper (Cu) and aluminum oxide (Al2O3) nanoparticles with sodium alginate as base fluid. The rheological characteristics of hybrid nanoliquid are captured by engaging Maxwell’s rheological model. The above-mentioned phenomena have never been investigated simultaneously, as evidenced by an in-depth review of the relevant literature, making this study a significant innovation. To simplify the study, adequate similarity transformations have been utilized to transform the governing system of nonlinear partial differential equations into a system of ordinary differential equations and resultant system is solved numerically by engaging bvp4c technique via MATLAB software. Graphical illustrations have been utilized in order to portray the supremacy of various parameters on concerned physical quantities. Likewise, numerical data are tabulated to get insights for quantities of engineering interest i.e. skin friction coefficient and local Nusselt number.

The slow violence of waste flowing through the Greenland Ice Sheet

ABSTRACT Military bases are major sources of environmental contamination that are often poorly documented. While there is an evident need to characterize the physical attributes, quantities, and mobility of waste produced by militaries, understanding the full impact of contamination requires a political and sociohistorical analysis. This interdisciplinary work draws specific attention to waste on the Greenland Ice Sheet caused by the construction, and later abandonment, of an extensive network of US military bases during the Cold War. Here we apply a human-ecological perspective to this topic that leverages analysis of existing datasets of the ice sheet’s physical properties (ice flow velocity and firn density modeling) while also revealing – and expanding – the historical context using archival reports. Our modeling demonstrates considerable variability in horizontal movement (23–1959 m) and burial depths (8–59 m) of abandoned military bases from their original positions on or below the ice sheet surface. Alongside these physical processes, we discuss the structural roles that law, location, and information play in burying and trapping waste in the ice sheet.

Vpliv digitalnih aplikacij in Inovativni pristopi z uporabo radarja hitrosti in druge tehnologije za individualni napredek učencev pri predmetu šport v iii. triadi

Innovative approaches to teaching physical education (PE) are key to promoting equal opportunities and active participation for all learners, regardless of their abilities or interests. This article is aimed at teachers who teach PE in primary school and are open to innovative methods in their work with pupils. In a PE lesson, we covered the topic of handball, in grade 8, where the focus was on the shot on goal. The working methods used (individualisation, differentiation, use of digital technology) allow the content to be adapted to the pupils, so that each pupil is active and progresses at his/her own level of ability. Students need to have a computer background in order for the lessons to run smoothly and effectively. Depending on the purpose of the learning, students logged into the online PE classroom using their mobile phones and followed the online learning path. They used the 'Padlet' and 'Copilot' apps to consolidate their prior knowledge and share the information on the interactive screen. In the main part, they measured the speed of the ball with the help of a "radar" and entered the data in an excel spreadsheet. Based on the measured speed of flight of the ball, we calculated the time taken for the ball to travel to the goal. We integrated the content of PE with the subject physics to facilitate the understanding of physical quantities. In addition to developing competences in sharing digital content with each other, we worked with the students to develop basic computer science skills in data analysis and processing. The aim was to present the data and monitor their own progress in the goal kick technique. This allowed the students team-oriented during the lesson, to be motivated and to improve their skills by real-time teacher feedback.

On the geodesics and shadows of Schwarzschild black holes with topological corrections

In this paper, we study the geodesics and shadows of topologically corrected Schwarzschild black holes through a perturbative method which we developed to derive the approximate analytical expressions for physical quantities such as the photon sphere and stable orbits. We find that the topological corrections could shrink the size of the photon sphere but enlarge the size of the event horizon. By exploring various accretion models, we investigate the effects of different parameters on the black hole shadow and intensity. We also discuss the potential for distinguishing corrected or uncorrected black holes based on their photon spheres and shadows.

Species of Structure and Physical Dimensions

Abstract This study addresses the often underestimated importance of physical dimensions and units in the formal reconstruction of physical theories, focusing on structuralist approaches that use the concept of “species of structure” as a meta-mathematical tool. Similar approaches also play a role in current philosophical debates on the metaphysical status of physical quantities. Our approach builds on an earlier proposal by Terence Tao. It involves the representation of fundamental physical quantities by one-dimensional real ordered vector spaces, while derived quantities are formulated using concepts from linear algebra, e.g. tensor products and dual spaces. As an introduction, the theory of Ohm’s law is considered. We then formulate a reconstruction of the calculus of physical dimensions, including Buckingham’s $$\Pi$$ Π -theorem. Furthermore, an application of this method to the Newtonian theory of gravitating systems consisting of point particles is demonstrated, emphasizing the role of the automorphism group and its physical interpretations.

Long Term Predictability of Southern Ocean Surface Nutrients Using Explainable Neural Networks

AbstractThe Southern Ocean is a region of high surface nutrient content, reflecting an inefficient biological carbon pump. The variability, predictability, and causes of changes in these nutrient levels on interannual to decadal time scales remain unclear. We employ a deep learning approach, specifically a Temporal Convolution Attention Neural Network (TCANN), to conduct multi‐year forecasting of surface based on oceanic physical drivers. The TCANN successfully replicates testing data with a prediction skill extending to at least 4 years with the GFDL‐ESM4‐driven model and 1 year with the observation‐driven model. To benchmark the results, we compare the prediction skill of TCANN with a simple persistence model and two regression methods, a linear regression and a ridge regression. The TCANN model was able to predict variability with a higher skill than persistence and the two regression methods indicating that non‐linearities present in the system become too high to predict inter‐annual variability with traditional regression methods. To enhance the interpretability of the predictions, we explore three explainable AI techniques: occlusion analysis, integrated gradients, and Gradient Shap. The outcomes suggest a crucial role played by salinity processes and buoyancy/potential density fluxes on the prediction of on annual time scales. The deep learning tools' ability to provide skillful forecasts well into the future presents a promising avenue for gaining insights into how the Southern Ocean's surface nutrients respond to climate change based on physical quantities.

The minimizing sets method for trend detection in time series of noisy measurement data

This article discusses the problem of trend detection in time series generated by technical devices. The solution to this problem is closely related to the problem of detecting coarse measurements (outliers), which negatively impact the accuracy of estimates of various physical quantities. These are crucial in many applications in various scientific fields in which the input data are observations, such as space geodynamics, geodesy, and others. Previously, the author proposed a trend-detecting method based on the condition of maximizing the amount of data cleared of outliers and used in further processing. The reference values used for trend construction are determined as a result of a completely convergent iterative process, the core of which is the minimizing sets method developed earlier by the author. This paper deals with the aspects of trend construction in the class of harmonic functions with unknown frequencies, phases and amplitudes.The main problem of trend construction in such a functional class is the nonlinear dependence of harmonics on the desired parameters, which does not allow to reduce the problem of trend search to the solution of a system of linear equations. The search for harmonics approximating the measurement data is carried out by the conjugate gradients method generalized to nonlinear problems. The efficiency of the method was tested on the test problem of trend construction in the data obtained by computer simulation.

A new approach to superstring

We show how starting with one-string space of states in BRST formalism one can construct a large class of physical quantities containing, in particular, scattering amplitudes for bosonic string and superstring. The same techniques work for heterotic string.

Reconstruction of spider system’s observables from orbital-period modulations via the Applegate mechanism

Redback and black-widow pulsars are two classes of peculiar binary systems characterised by very short orbital periods, very low-mass companions, and, in several cases, regular eclipses in their pulsed radio signal. Long-term timing revealed systematic but unpredictable variations in the orbital period, which can most likely be explained by the so-called Applegate mechanism. This relies on the magnetic dynamo activity generated inside the companion star and triggered by the pulsar wind, which induces a modification of the star’s oblateness (or quadrupole variation). This, in turn, couples with the orbit by gravity, causing a consequent change in the orbital period. The Applegate description is limited to providing estimates of physical quantities by highlighting their orders of magnitude. Therefore, we derived the time-evolution differential equations underlying the Applegate model; that is, we tracked such physical quantities in terms of time. Our strategy is to employ the orbital period modulations, measured by fitting the observational data, and implement a highly accurate approximation scheme to finally reconstruct the dynamics of the spider system in question and the relative observables. Among the latter is the magnetic field activity inside the companion star, which is still a matter of debate for its complex theoretical modelling and the ensuing expensive numerical simulations. As an application, we exploited our methodology to examine two spider sources: 47 Tuc W (redback) and 47 Tuc O (black widow). In this paper, the results obtained are analysed and then discussed in relation to the literature.

A weak bias-magnetized dynamic permeability testing method for detecting and distinguishing inner and outer diameter defects in gas pipelines

A weak bias-magnetized dynamic permeability testing method for detecting and distinguishing inner and outer diameter defects in gas pipelines

An Efficient Staggered Scheme for Solving the Poromechanics Problem of Quasi-Static Cardiac Perfusion.

The ventricles can be considered a type of poroelastic material, where the mass and pressure of the interstitial fluid, along with the displacement of the skeleton, are the three primary physical quantities of interest. Based on the free energy function of the poroelastic material, we propose a simplified model that requires only two fields to be directly solved, with another quantity obtained through post-processing. To solve this model, we first discretize the equations with the backward Euler scheme and finite element method, leading to a nonlinear system of equations, which can be solved using the Newton method in a monolithic way. For computational efficiency, we proposed a staggered scheme, where the large nonlinear system is divided into two smaller independent systems, and each only solves for one field using the Newton method. The numerical results showed the staggered scheme is more efficient than the monolithic scheme and that the two schemes achieve the same results, and are also in good agreement with those reported in the literature. Finally, we applied the staggered scheme to ventricular myocardial perfusion models and obtained the blood perfusion patterns in the myocardium during the cardiac systole.

Simulation study on the dynamic similarity of oil-liquid spring recoil mechanism

This study focuses on the oil-liquid recoil mechanism of a specific artillery system, deriving the dynamic similarity and similarity constants of physical quantities for the device. By altering boundary conditions, a comparative analysis was conducted using the original and similarity models. A comprehensive simulation of linear dynamic similarity during the operation of the entire system model was performed. Through a comparison of the recoil force data between the similarity model and the original model, it was observed that both exhibit consistent trends and a proportional relationship, with the maximum recoil force of the similarity model being 15% of that of the original model. Further comparison of the similarity coefficient and normalized root mean square error values demonstrates that the similar and test model data exhibit good fitting and similar trends. This study validates the accuracy and effectiveness of the research method for the similarity model of the recoil mechanism in artillery with spring-liquid recoil dampers.

Data-Enabled Parameter Modification for the Shear-Stress-Transport Model with Progressive Neural Networks

Turbulence models based on the Reynolds-averaged Navier–Stokes method are widely employed for simulation in engineering and research. Nonetheless, these models have some limitations in simulating flows with adverse pressure gradients due to the inclusion of various assumptions, such as the eddy viscosity hypothesis. As a result, many researchers have focused their efforts on improving turbulence models, including parameter calibration. In this paper, a progressive neural network framework is utilized to modify the dissipation coefficients of the shear-stress transport (SST) model into a function of physical quantities. Firstly, the zero pressure gradient flat plate case is employed to obtain the calibrated model SST-FP. Subsequently, the flow with a turbulent separation bubble is adopted to progressively acquire the calibrated model SST-TSB. The enhanced model performs well in predicting the mean velocity profile, friction coefficient, and other variables of training cases, owing to joint corrections on the k and ω equations. Furthermore, verification research demonstrates that the SST-TSB model mitigates the potential damage to the wall-law prediction. It can also adapt the forecast properly in circumstances where the original model predicts larger or smaller separation zones, avoiding the drawbacks that Bayesian inference and other methods have when applied to parameter calibration.

A modified permeable model for analyzing two collinear cracks in thermo-electro-elastic materials

In this paper, we propose a modified permeable model to analyze the fracture behavior of two collinear cracks under a thermo-electro-elastic load that is described by a cubic function. By employing this modified model and Fourier transformation, the mixed boundary value problem is firstly reduced to a set of singular integral equations. Then, based on using the Cauchy kernel theory, we derive analytical solutions for these equations, with a focus on key crack-tip physical quantities and intensity factors. Numerical results demonstrate that the crack size, initial unit heat flux adjustment parameters, and initial electric displacement adjustment parameter, accounting for the effects of initial heat flux, electric displacement, and irregular crack surfaces, significantly influence the temperature gradients and intensity factors.

All‐in‐one Cascadable Dynamic Terahertz Logic Gates Enabled by Polarization Encoding and Multiplexing

AbstractMetasurfaces bring an advanced paradigm for optical computing through extraordinary beam manipulation. A metasurface logic gate needs function multiplexing to process different input signals. Integration of multiple gates in one design further increases the multiplexing channels, which necessitates the diffractive neural networks with challenges of decreased system stability, difficulty for connection, and large insertion loss. Here an optical logic gate is demonstrated by sequentially encoding the input signals into polarization and decoding through a 4‐polarization‐multiplexed metasurface. By introducing an idler polarization state, a convenient strategy is developed to integrate and dynamically switch 4 or full 7 logic gates in a single module through overall polarization rotation and proper polarization‐truth multiplexing relation. The all‐in‐one logic gate is validated at 140 GHz through the steady‐state and dynamic test, with the resulting contrast of 6.5 dB, flexible test ranges of 80 mm, and insertion loss of 2.2 dB. The computing result is represented by both the focusing position and the polarization, with the later as a consistent input and output physical quantity for cascading. Cascaded AND–AND gates and AND‐OR gates are demonstrated with 6 dB result contrast, showing great promise for building robust logic systems for future optical signal processing.