Physical Phenomena Research Articles

Seasonal variation and fundamental characteristics of baroclinic tides in the Arabian Gulf

In the Arabian Gulf, baroclinic tides significantly impact physical and biological phenomena, shaping the region’s marine ecosystem. This study provides the first high-resolution investigation of the baroclinic tides using the three-dimensional, nonhydrostatic MIT general circulation model (MITgcm). The simulation outputs were validated against data from Oregon State University’s Tidal Inversion Software (OTIS), tidal stations, and mooring observations, showing high agreement and confirming the model’s accuracy. We further examined the characteristics of baroclinic and barotropic tides, identifying four key regions with high-intensity baroclinic tides based on energy budget analysis: 1) the narrow Strait of Hormuz; 2) the strait’s entrance along the trough, including the islands Farur, Siri, Abumusa, and Greater Tunb; 3) the central axial trough area with sea-bottom ridges; and 4) the northern area following a secondary ridge. Most baroclinic tides dissipate quickly due to interactions with complex bottom topography and do not propagate far from their sources. Significant seasonal variation shows that in winter, only the Strait of Hormuz and the area around the four islands showed significant baroclinic tidal energy, likely due to well-mixed upper layer seawater that hinders thermocline disturbances. The strong correlation between the simulation results and satellite images of internal waves suggests that intense baroclinic tides generate internal solitary waves in the Gulf.

Observation of Thouless pumping of light in quasiperiodic photonic crystals

Topological transport is determined by global properties of physical media where it occurs and is characterized by quantized amounts of adiabatically transported quantities. Discovered for periodic potential, it was also explored in disordered and discrete quasiperiodic systems. Here, we report on experimental observation of pumping of a light beam in a genuinely continuous incommensurate photorefractive quasicrystal emulated by its periodic approximants. We observe a universal character of the transport which is determined by the ratio between periods of the constitutive sublattices, by the sliding angle between them, and by Chern numbers of the excited bands (in the time-coordinate space) of the approximant, for which pumping is adiabatic. This reveals that the properties of quasiperiodic systems determining the topological transport are tightly related to those of their periodic approximants and can be observed and studied in a large variety of physical systems. Our results suggest that the links between quasiperiodic systems and their periodic approximants go beyond the pure mathematical relations: They manifest themselves in physical phenomena which can be explored experimentally.

Dynamic Description of soliton solutions of nonlinear Schrödinger equation with higher order dispersion and nonlinear terms

Abstract The article presents an analytical solution for the higher-order nonlinear Schrödinger equation (NLSE), which describes the propagation of short light pulses in monomode optical fibers. Various traveling wave solutions are obtained using the generalized exponential rational function method, a technique with substantial applications in physics and mathematics. Additionally, the parameters leading to the occurrence of optical bright and multipeak solitons in this medium are provided along with their formation conditions. The derived solutions are graphically displayed to enhance the understanding of the model’s physical phenomena. This approach is credible, potent, and successful in solving a wide variety of different models of this kind that arise in the applied sciences. Its robustness, strength, and efficiency make it suitable for addressing various higher-order nonlinear problems in current research fields, extending beyond the models encountered in the applied sciences.

All-optical manipulation of bandgap dynamics via coherent phonons

The ability to actively and dynamically control electronic states at ultrafast timescales opens up a wide range of potential applications across optoelectronics, quantum computing and sensing, energy conversion and storage, etc. Yet, achieving dynamic electronic manipulation via coherent phonons has posed a considerable challenge. Here, employing time-resolved high-harmonic generation (tr-HHG) spectroscopy, we demonstrate the manipulation of bandgap dynamics in a BaF2 crystal by coherent phonons. The tr-HHG spectrum perturbed by a triply degenerate phonon mode T2g exhibits simultaneously a remarkable two-dimensional (2D) sensitivity, i.e., in both intensity and energy domains. The dynamic compression and enhancement of the harmonics in the intensity domain showed a π/2 phase shift compared to the manifestation of shifts of the harmonics in the energy domain, an astounding example of a physical phenomenon being observed simultaneously in two different perspectives. We employed a quantum model incorporating the electron–phonon coupling to complement our experimental observations, successfully reproducing the results. In addition, we demonstrated complete control over the strength and initial phase of the coherent phonon oscillations by varying the incident electric field polarizations across different crystal orientations. Our findings lay a foundation for engineering the electronic structure through coherent phonons within the terahertz frequency and picosecond to nanosecond time regimes.

Stellar expansion or inflation?

While stellar expansion after core-hydrogen exhaustion related to thermal imbalance has been documented for decades, the physical phenomenon of stellar inflation that occurs close to the Eddington limit has only come to the fore in recent years. We aim to elucidate the differences between these physical mechanisms for stellar radius enlargement, especially given that additional terms such as `bloated' and `puffed-up' stars have been introduced in the recent massive star literature. We employ single and binary star MESA structure and evolution models for constant mass, as well as models allowing the mass to change due to winds or binary interaction. We find cases that were previously attributed to stellar inflation in fact to be due to stellar expansion. We also highlight that while the opposite effect of expansion is contraction, the removal of an inflated zone should not be referred to as contraction but rather deflation as the star is still in thermal balance.

New analytical wave structures for generalized B-type Kadomtsev–Petviashvili equation by improved modified extended tanh function method

Abstract Recently, solving the complicated nonlinear partial differential equations has become very important demand in order to simulate their physical phenomena. This manuscript focuses on extracting the wave solutions of (3 + 1)-dimensional generalized B-type Kadomtsev-Petviashvili equation (GBKPE), which demonstrates the behavior of nonlinear waves in fluid mechanics. The improved modified extended Tanh function (IMETF) method is the suggested method to do this task as it gives different types of solutions. This method enables us to obtain many solutions, such as Jacobi elliptic, dark soliton, and singular soliton, exponential, and singular periodic wave solutions. Additionally, for more illustrations graphical visual representations of some solutions are provided.

River plume identification through a deep-learning model: an innovative approach

ABSTRACT River plumes are complex physical phenomena that occur at the interface between riverine and marine systems. The lack of direct measurements of sediment concentration complicates the study of these geomorphological features, since the boundaries of river plumes are often gradual and unclear. Therefore, the identification and digitalization of river plumes is not simple and the methods applied in different study areas are not always objective and replicable. The aim of this work is to provide a valid approach based on a deep-learning model that uses Convolution Neural Network (CNN) layers for the digitalization of river plumes. We describe the methodology applied to implement the input dataset used for training the model, the errors obtained, and an application for a study area of about 300 km located in the Mediterranean. The model uses Sentinel-2 Level-1C images. The application of the model to a specific study area allowed us to understand the possibility of investigating these geomorphological features to obtain results in agreement with previous works. As a matter of fact, by using the red band as a proxy of sediment concentration, we were able to investigate the average behaviours of sediment dispersion along the coast and to extract innovative data related to specific events for the study of morphological characteristics such as dimension and direction.

Investigation of activation energy of Maxwell fluid with Newtonian heat effect at the boundary layer flow on a cylinder embedded in porous medium

AbstractThis study aims to investigate the flow of Maxwell fluid over a cylinder, considering the combined effect of Magnetohydrodynamics (MHD) and a permeable medium on the equation of momentum, heat generation and radiation on the equation of energy, and activation energy on the mass equation. The objective is to analyze the impression of these physical phenomena on the fluid's behavior under specified boundary conditions, with a focus on the Newtonian heating effect. The significance of this research lies in its application to industrial processes, polymer extrusion and cooling of metallic sheets, where controlling fluid flow and energy transfer is crucial. The dimensional governing equations for momentum, energy, and concentration were changed into non‐dimensional forms via appropriate dimensionless quantities and similarity variables. The subsequent nonlinear ordinary differential equations were answered using the BPV4C inbuilt MATLAB solver. The key findings reveal that the concentration outline rises with a rise in activation energy and declines with a rise in the chemical reaction. Additionally, the Nusselt number profile displays an increasing trend with the Newtonian heating parameter, indicating enhanced heat transfer. Quantitative results demonstrate that the occurrence of a porous medium and MHD significantly impacts the velocity and temperature contours. The real‐time application of this study can be seen in the optimization and design of chemical reactors, heat exchangers, and cooling systems in engineering processes. The developed model delivers insights into controlling energy and mass transfer in processes involving stretching surfaces, which is essential for improving efficiency and product excellence in various industrial applications.

Quantum mechanics and statistical physics: Novel frameworks for enhancing natural language processing

Abstract. This article explores the pioneering application of principles from quantum mechanics and statistical mechanics to the field of natural language processing (NLP). By drawing analogies between physical phenomena such as quantum entanglement, phase transitions, and statistical ensembles, and linguistic concepts like semantic relationships, language use dynamics, and lexical diversity, we offer a novel perspective on language analysis and processing. Quantum linguistic models, leveraging the intricacies of entanglement and quantum probability, provide a framework for understanding complex semantic networks and enhancing computational efficiency through quantum computing. Meanwhile, statistical mechanics inspires models for capturing lexical diversity and understanding the evolution of language patterns, akin to phase transitions in physical systems. This interdisciplinary approach not only deepens our understanding of linguistic phenomena but also introduces advanced mathematical and computational techniques to improve NLP tasks.

Enhanced and Efficient Predictions of Dynamic Ionization through Constant-pH Adiabatic Free Energy Dynamics.

Dynamic or structurally induced ionization is a critical aspect of many physical, chemical, and biological processes. Molecular dynamics (MD) based simulation approaches, specifically constant pH MD methods, have been developed to simulate ionization states of molecules or proteins under experimentally or physiologically relevant conditions. While such approaches are now widely utilized to predict ionization sites of macromolecules or to study physical or biological phenomena, they are often computationally expensive and require long simulation times to converge. In this article, using the principles of adiabatic free energy dynamics, we introduce an efficient technique for performing constant pH MD simulations within the framework of the adiabatic free energy dynamics (AFED) approach. We call the new approach pH-AFED. We show that pH-AFED provides highly accurate predictions of protein residue pKa values, with a MUE of 0.5 pKa units when coupled with driven adiabatic free energy dynamics (d-AFED), while reducing the required simulation times by more than an order of magnitude. In addition, pH-AFED can be easily integrated into most constant pH MD codes or implementations and flexibly adapted to work in conjunction with enhanced sampling algorithms that target collective variables. We demonstrate that our approaches, with both pH-AFED standalone as well as pH-AFED combined with collective variable based enhanced sampling, provide promising predictive accuracy, with a MUE of 0.6 and 0.5 pKa units respectively, on a diverse range of proteins and enzymes, ranging up to 186 residues and 21 titratable sites. Lastly, we demonstrate how this approach can be utilized to understand the in vivo performance engineered antibodies for immunotherapy.

Heat and mass transfer analysis in flow of Walter's B nanofluid: A numerical study of dual solutions

AbstractThis study investigates the behavior of Walter's liquid B fluid over a biaxially stretching/shrinking surface for Homann stagnation point flow, focusing on the rheological properties that are crucial for understanding physical phenomena in engineering and industrial processes. The problem is modeled using Buongiorno's model in the presence of a permeable surface subject to heat generation/absorption, Ohmic heating, and chemical reactions influenced by Arrhenius activation energy. The governing partial differential equations are solved numerically using an appropriate similarity transformation, and the results are graphically analyzed via MATLAB's bvp5c solver. The study highlights the importance of characterizing the intricate properties of viscoelastic fluids, with potential applications in biomedical engineering and materials science. The findings reveal the coexistence of two distinct flow regimes and dual solutions are obtained. It is noted that the activation energy parameter is shown to enhance mass distribution in both solutions, while chemical reactions accelerate reactant conversion but reduce mass distribution. Additionally, an increase in viscoelasticity shifts the fluid's behavior towards elasticity, creating greater resistance to shear deformation and reducing both velocity profiles.

Harnessing Machine Learning to Model Intuitive Physics: Insights from Game Engines and Cartoon Simulations

Abstract. This paper explores the application of machine learning (ML) in modeling intuitive physics, focusing on insights derived from game engines and cartoon simulations. Intuitive physics refers to the human capability to predict physical phenomena in everyday situations, a skill that can be replicated and enhanced in machines using ML algorithms. By integrating ML with game engines, which provide dynamic, controllable environments, and cartoon simulations, known for their exaggerated physical scenarios, the research aims to develop models that better understand and predict physical interactions. The study analyzes the efficiency of current ML approaches, including deep learning and reinforcement learning, in capturing the complex, often non-intuitive physics depicted in cartoons, and how these models can be generalized to understand real-world physics. The findings suggest potential improvements in the algorithms' ability to interpret and anticipate physical events, leading to advancements in robotics and AI-driven simulation systems.

Size winding mechanism beyond maximal chaos

The concept of information scrambling elucidates the dispersion of local information in quantum many-body systems, offering insights into various physical phenomena such as wormhole teleportation. This phenomenon has spurred extensive theoretical and experimental investigations. Among these, the size-winding mechanism emerges as a valuable diagnostic tool for optimizing signal detection. In this work, we establish a computational framework for determining the winding size distribution in all-to-all interacting quantum systems, utilizing the scramblon effective theory. We obtain the winding size distribution for the large-q SYK model across the entire time domain, where potential late-time corrections can be crucial for finite-N systems. Notably, we unveil that the manifestation of size winding results from a universal phase factor in the scramblon propagator, highlighting the significance of the Lyapunov exponent. These findings contribute to a sharp and precise connection between operator dynamics and the phenomenon of wormhole teleportation.

Assessing Learning in Mathematical Sensemaking Electromagnetism Instructions among Rwanda Polytechnic Students at Huye College

In the realm of electromagnetic (EM) courses in engineering, many studies have reported students’ learning difficulties related to mathematical frameworks representing physical phenomena. Students’ learning engagement and learning gains are not satisfying. The present study assessed first-year engineering students’ behavioural engagement and perceived learning gains in mathematical sensemaking electromagnetism instructions at RP-Huye College. Within a single-case research design, a six-weeks intervention incorporating mathematical sensemaking instructions, supported by physical experimentation and computer simulations, was implemented to 61 first-year engineering students who were enrolled in the department of electrical and electronics engineering. All enrolled students were purposively recruited to participate because this target population was less than 100. Data were collected through classroom observations, which used the behavioural engagement related to instruction (BERI) and a post-topic evaluation, which used a semi-structured questionnaire. Data analysis involved the use of graphs, descriptive statistics and inductive thematic analysis. Findings revealed that students were mostly engaged during mathematical sensemaking by hands-on and simulation-based activities, particularly in topics related to electromagnets, where engagement levels peaked at 7.5 in average. Conversely, lecture-based tasks, especially on magnetic forces and electromagnetic induction, recorded the lowest engagement at 6.2 in average. The post-topic assessment on perceived learning gains showed that students had highly positive perceptions on their learning experiences (M=4.82, SD=0.48) and recognized the significance of EM in engineering (M=4.85, SD=0.38). These numerical results were complemented by students’ narrations, which indicated that they gained particular attention about specific EM formulas and how they can apply them in engineering. However, the present study also noted that further refinement in instructional design, particularly by incorporating specific dimensions of mathematical sensemaking, could optimize learning outcomes for EM courses in engineering. Additionally, formal assessments of students’ mastery and experimental studies can benefit future work.

Diverse general solitary wave solutions and conserved currents of a generalized geophysical Korteweg–de Vries model with nonlinear power law in ocean science

This article presents an analytical investigation performed on a generalized geophysical Korteweg–de Vries model with nonlinear power law in ocean science. To start with, achieving diverse solitary wave solutions to the generalized power‐law model involves using wave transformation, which reduces the model to a nonlinear ordinary differential equation. A direct integration approach is adopted to construct solutions in the beginning. This brings the emergence of interesting solutions like non‐topological solitons, trigonometric functions, exponential functions, elliptic functions, and Weierstrass functions in general structures. Besides, in a bid to secure more general exact solutions to the model, one adopts the extended Jacobi elliptic function expansion technique (for some specific cases of ). Thus, various cnoidal, snoidal, and dnoidal wave solutions to the understudied model are attained. The copolar trio explicated in a tabular form reveals that these solutions can be relapsed to various hyperbolic and trigonometric functions under certain criteria. Additionally, diverse graphical exhibitions of the dynamical attributes of the gained results are presented in a bid to have a sound understanding of the physical phenomena of the underlying model. Later, one gives the conserved vectors of the aforementioned equation by employing the standard multiplier approach.

Operational matrix method approach for fractional partial differential-equations

Abstract Fractional partial differential equations (FPDEs) have become very popular to model and analyze numerous different physical phenomena in recent years. However, it is generally complicated to find the exact solutions of those FPDEs. The objective of this study is to find the approximate numerical solution of FPDEs by introducing a wavelet-based operational matrix technique. In this study we employ Hermite wavelets (HWs) and the operational matrices of the fractional integration for Hermite wavelets. The sparsity of the obtained operational matrices provides fast and efficient computation of the proposed method. The original FPDE equations are converted to Sylvester equations, which then are solved to obtain the final solution. We provide a few numerical examples to demonstrate the versatility and efficiency of the proposed method.

Mapping the topology-localization phase diagram with quasiperiodic disorder using a programmable superconducting simulator

We explore a topology-localization phase diagram by simulating a one-dimensional Su-Schrieffer-Heeger model with quasiperiodic disorder using a programmable superconducting simulator. We experimentally map out and identify various trivial and topological phases with extended, critical, and localized bulk states. We find that with increasing disorder strength, some extended states can be first replaced by localized states and then by critical states before the system finally becomes fully localized. The critical states exhibit typical features such as multifractality and self-similarity, which lead to surprisingly rich phases with different types of mobility edges and scaling behaviors on the phase boundaries. Our results shed light on the investigation of the topological and localization phenomena in condensed-matter physics. Published by the American Physical Society 2024

Evanescent point sources: application to microsphere-assisted super-resolution microscopy.

In the rigorous electromagnetic simulation of an imaging system, the evanescent waves from a point source or from a sample are naturally mixed with the propagative waves. Therefore, their contributions are difficult to distinguish. We present a point-source model made of only the evanescent waves. To illustrate its potential, the model is applied to the study of the evanescent-wave contribution in microsphere-assisted microscopy (MAM). The contribution of the evanescent waves in the microsphere imaging process is clearly demonstrated. However, we also show that this contribution is not enough to justify the super-resolution. The destructive interference between two close point sources may be the key physical phenomenon.

Atom-Vacancy-Defect-Derived Electric Hysteresis Loops and Stochastic Low-Frequency Noises in Few-Atom Layer MoS2.

Atom-vacancy-defects present in various materials yield numerous interesting physical phenomena, even obstructing high performance in some cases. On the other hand, their valuable applications to novel devices, such as nitrogen vacancy centers in diamond for quantum bits, have gathered significant attention. In particular, these tendencies become more substantial in two-dimensional (2D) (atomically) thin van der Waals layers. However, correlations with various kinds of atom defects are still under exploration. Herein, we find the stochastic behaviors of large hysteresis loops with strong photoresponse in the static electrical properties in few-atom layer semiconductors, molybdenum disulfide (MoS2). The temperature dependence and transmission electron microscopy reveal that they arise from pairs of two neighboring in-plane S-vacancy defects, which predominantly present only around the interface at the MoS2 flake/substrate, with activation energies ∼0.35 eV. The low-frequency (f) (LF) noise measurements clarify a high f shift in the two 1/f2-dependent regimes, implying stochastic behaviors of electric charges through the S-vacancy pairs with high-speed charge(spin) transitions across low kinetic energy barriers between narrow discrete states. The shallow energy sates are formed from the highly uniform S-vacancy pairs interacting with Mo atoms, which act like quantum dots. The observed stochastic operation holds promise for various application, particularly for probabilistic neuromorphic computation in artificial intelligence.

The ‘Universe in a Box’: a hands-on activity to introduce primary school students to cosmology

Abstract Physics Education Research shows that active learning and interdisciplinary strategies can enhance students’ engagement in physics. In primary school, the implementation of active learning pedagogies such as Inquiry-Based Science Education aims to encourage students’ autonomy and participation in their learning process. Indeed, active learning promotes pupils’ creativity, helping them develop the skills that increasingly determine their future employability and personal development, introducing them to STEM. In this regard, stories and storytelling can help improve teaching and students’ physics learning. Telling the Universe and its history can afford this job. The Big Bang, the Cosmic Microwave Background, and the formation of stars and planets are valuable tools for introducing primary school students to physics and the scientific method while fostering their curiosity about science. Moreover, it helps the instructors monitor the development of peculiar misconceptions on these topics, preventing them from fully understanding physics phenomena. In this paper, we present an innovative short-term program (one session of three hours) called ‘The Universe in a Box’ to introduce primary school students (grades 4–5, ages 9–10) to cosmology. We illustrate our design and the educational purposes of the program and present the outcomes from its implementation in five different laboratories in Sardinia, Italy, from 2022 to 2024 (60 students involved). This work can furnish a theoretical and methodological guide for primary school teachers and instructors on integrating formal curricula with contemporary physics topics using interdisciplinary approaches, engaging their students in STEAM (STEM plus Arts).