Brazilian Journal of Physics最新文献

Tuberculosis (TB) remains a major global health threat, particularly for individuals with diabetes mellitus (DM), whose compromised immune systems heighten susceptibility to infection. Pregnant women with diabetes constitute an especially high-risk subgroup, as the physiological changes during pregnancy can further suppress immune responses, increasing the likelihood of TB infection. In this study, we extend an existing compartmental model of TB dynamics in diabetic populations by introducing a distinct compartment for pregnant diabetic women. This modification enables a more realistic representation of the interactions among susceptible, diabetic, pregnant diabetic, and TB-infected individuals. The resulting system of nonlinear differential equations captures the temporal evolution of disease transmission and progression within this high-risk group. To solve the system and estimate key epidemiological parameters, we employ a Machine Learning-based Physics-Informed Neural Network (PINN) framework, which synergistically combines data-driven learning with the governing dynamical equations. Importantly, our model is informed and validated using real-world epidemiological data obtained from the World Health Organization (WHO), enhancing its practical relevance and predictive accuracy. The findings underscore the urgent need for targeted TB screening and prevention strategies tailored to pregnant diabetic women, aiming to mitigate infection risks and improve maternal and public health outcomes.

A comparative investigation of Li₂ScAuZ₆ (Z = Cl or Br, or I) has been performed using density functional theory. The structural arrangement of perovskites has been optimized using the WIEN2k code, which has also been used to calculate diverse properties such as mechanical, electronic, optical, and transport characteristics. Chemical, as well as structural stability, are predicted by determining the formation energy and tolerance factors. The analysis of the elastic parameters has been demonstrated to evaluate mechanical stability, anisotropy, toughness, mechanical strength, and melting temperature. The electronic properties are calculated by employing the Tran-Balaha modified Becke-Johnson (TB-mBJ) potential and semiconductor nature, as well as indirect band gap values of 1.71, 1.56, and 1.25 eV have been obtained. The optical properties in the 0–6 eV energy band have been investigated, and it was revealed that the incoming photons have been significantly absorbed and transmitted in the visible energy ranges. This ensures that these perovskites are appropriate for use in photovoltaic technologies. These materials have also demonstrated significant figures of merit (ZT), power factors, and electrical conductivity and are effective thermoelectric resources. Finally, these findings would benefit researchers conducting experiments and have revealed the significant potential of these perovskites for energy harvesting applications.

In this work, we investigated fission cross-section and fission yield curves of ²³⁸U for neutron-induced fission reaction process at 1.7 MeV and 14.3 MeV for five different fission fragment models and three yield models. For this reason, we calculated the fission cross-section curves and independent yield (:{Y}_{I}left(Aright)) and primary fission fragment yield (:Yleft(Aright)) for ²³⁸U(n, f) reaction based on the theoretical models. The obtained model results were compared with experimental data in the literature and recommended suitable models for both cross-section and yield calculations. Moreover, neutron emission multiplicity distribution (:Pleft({upnu:}right)), the mass-dependent and the energy-dependent average neutron multiplicities, (:stackrel{-}{nu:}left(Aright)) and (:stackrel{-}{nu:}left(Eright)) were calculated and discussed to provide new data to the literature.

The present manuscript revisits one of the earliest approaches to treating molecular systems within the Schrödinger formalism of quantum mechanics: the Heitler-London (HL) model. Originally proposed in 1927 and based on a linear combination of atomic orbitals, the HL model provided a foundational description of covalent bonds and has served as the basis for numerous variational methods. Focusing on the hydrogen molecule, we begin by revisiting the analytical calculations of the original HL model, from which the qualitative physics of bonding and antibonding states can be obtained. Subsequently, we propose including electronic screening effects directly in the original HL wave function. We then compare our proposal with variational quantum Monte Carlo (VQMC) calculations, whose trial wave function allows us to optimize the electronic screening potential as a function of the inter-proton distance. We obtain the bond length, binding energy, and vibrational frequency of the H(_{varvec{2}}) molecule. Beyond revisiting this foundational approach in quantum mechanics, our proposal can serve as improved input for constructing new, but still analytically simple, variational wave functions to describe dissociation or bond formation.

Quantum mechanics has introduced a new theoretical framework for the study of molecules, enabling the prediction of properties and dynamics through the solution of the Schrödinger equation applied to these systems. However, solving this equation is computationally expensive, which has led to the development of various mathematical frameworks and computational methods designed to balance the available resources with the desired level of accuracy. In particular, quantum computers have emerged as a promising technology with the potential to address these problems more efficiently in the coming decades, whether through reductions in memory, time, and energy consumption, i.e., reductions in computational complexity, or by enhancing precision. This research field is known as quantum simulation. Given the current technological limitations of quantum computers, Variational Quantum Algorithms (VQAs), especially the Variational Quantum Eigensolver (VQE), stand out as a feasible approach to demonstrating advantages over classical methods in the near term. This feasibility arises from their lower demand for quantum gates and the reduced depth of the circuits required for their implementation. In this work, we present the application of quantum mechanics to the study of molecules, provide an introduction to the fundamentals of quantum computing, and explore the integration of these fields by employing the VQE in molecular simulations. Finally, we discuss the spatial and temporal complexity associated with the algorithm, highlighting its implications and challenges.

Acceleration of electrons by a weakly relativistic ponderomotive force, driven by an intense circularly polarized Gaussian laser pulse undergoing self-focusing and self-compression in magnetized plasma, is numerically studied. By calculating the ponderomotive force and modified electron density distribution, sets of coupled differential equations are derived to describe the spatiotemporal evolution of the laser pulse as well as the electron energy in the magnetoplasma. The influence of the laser’s polarization state (right-hand or left-hand circularly) and the magnetic field on the spatiotemporal dynamics and energy gain is investigated. The results showed that, due to the weakly relativistic ponderomotive force, the laser pulse undergoes self-focusing and self-compression, which induce transverse oscillations in the electrons, leading to a significant net energy gain. It is also shown that, for the right-handed polarization, an increase in magnetic field strength enhances both the self-focusing and self-compression of the laser pulse, resulting in a higher intensity as the pulse propagates through the plasma, which subsequently increases the electron acceleration. Conversely, for the left-handed polarization, an increase in the magnetic field strength diminishes the effectiveness of these processes, thereby weakening the electron acceleration mechanism.

Stealth technology has become predominant in modern technology, particularly in military applications. This study presents the development and analysis of 1-bit and 2-bit coding metamaterials for radar cross-section (RCS) reduction in the terahertz (THz) frequency band. Coding metamaterials effectively control electromagnetic (EM) waves in various dimensions, such as amplitude, phase, and polarization. In the 1-bit coding scheme, two distinct unit cells are used, whereas the 2-bit coding approach employs four unit cells. To optimize RCS reduction, five different coding sequences were proposed with four, eight, and twelve lattices per bit. The scattering values were numerically performed using Computer Simulation Technology (CST) software. Coding sequences Sequence 1, Sequence 2, and Sequence 3 demonstrated significant RCS reduction. A certain coding sequence exhibited RCS values as low as − 102.6 dBm². The proposed 1-bit and 2-bit coding metamaterials offer promising solutions for enhancing RCS reduction and advancing THz wave manipulation in various applications.

This study employs the Separate Spin Evolution Quantum Hydrodynamic Model (SSE-QHM) to explore the influence of quantum effects—namely the Bohm potential, exchange interaction, and spin polarization—on the nonlinear dispersion properties and modulational instability growth rates. The analysis focuses on high-frequency Quantum Upper Hybrid Waves (QUHWs) and their nonlinear coupling with Quantum Lower Hybrid Waves (QLHWs), Quantum Ion Cyclotron Waves (QICWs), and Quantum Alfvén Waves (QAWs) in a magnetized quantum electron-ion plasma. Using the standard phasor matching technique, we derive nonlinear dispersion relations for these coupled wave modes, shedding light on three-wave interactions and modulational instabilities. Parametric analysis indicates that instability growth rates are highly sensitive to pump wave frequency, Bohm potential, exchange correlation, and spin polarization. Notably, spin polarization enhances instability growth at shorter wavelengths, whereas at higher wave numbers, the Bohm potential and exchange correlation suppress instability, promoting wave stabilization. Additionally, the growth rates of three-wave decay instability decrease with increasing quantum effects, underscoring the significant role of quantum corrections in wave propagation and instability thresholds. These findings advance the theoretical understanding of quantum plasma dynamics and have important implications for astrophysical plasmas, quantum magnetohydrodynamics, and emerging plasma-based quantum technologies.

We investigate quantum correlations in the two-qubit Heisenberg XXZ model with dipolar interaction and the Dzyaloshinskii-Moriya interaction, focusing on concurrence and measurement-induced disturbance. By varying key parameters such as temperature, exchange couplings, and anisotropy, we analyze their effects on quantum entanglement and non-classical correlations. Our results reveal that thermal fluctuations generally degrade quantum correlations; however, their robustness can be enhanced through proper tuning of interaction parameters. Notably, the competition between exchange interactions and dipolar coupling significantly influences the critical points where entanglement is either suppressed or enhanced. Furthermore, we explore the dense coding capacity in an extended quantum model, considering the impact of temperature, isotropic and anisotropic exchange coupling, dipolar interaction, and the Dzyaloshinskii-Moriya interaction. Our findings demonstrate that while the Dzyaloshinskii-Moriya interaction stabilizes the dense coding capacity against thermal effects, an increased anisotropic exchange coupling accelerates its degradation. Additionally, a strong dipolar interaction mitigates the loss of efficiency, playing a crucial stabilizing role in the system. Overall, our study highlights the intricate interplay between interactions and thermal effects in quantum systems. By optimizing these parameters, it is possible to enhance the stability and efficiency of quantum communication protocols, contributing to the advancement of robust quantum information processing technologies.

Electrode-less surface-wave sustained discharge (SWD) plasma jets operated with noble gases provide a chemically clean and reproducible route to plasma-activated water (PAW) generation, avoiding electrode erosion and metal contamination while enabling long, stable activations. Using an argon SWD jet (70 W), we tracked the time-resolved thermal and physicochemical evolution of PAW over 40 min and assessed antimicrobial efficacy. PAW acidified to pH ~ 3.34, with ORP ~ 230 mV, conductivity ~ 180 µS/cm, and TDS ~ 55 mg L⁻¹. Spectrophotometric/colorimetric analyses showed the accumulation of RONS with H₂O₂ ~ 10–25 mg L⁻¹, NO₃⁻ ~ 10–25 mg L⁻¹, and NO₂⁻ ≤ 1 mg L⁻¹; evaporation during long activations concentrated solutes, and volume-normalized endpoints confirmed that qualitative trends persist after correcting for mass loss. Optical emission and thermal probes indicated that water buffers the heat load yet can drift toward ~ 40 °C under the longest activations, motivating temperature control (≤ 20–25 °C) to preserve thermally labile ROS. Microbiological assays revealed strong bactericidal activity against Staphylococcus aureus and Escherichia coli but limited effect on Candida albicans, consistent with organism-specific cell-wall structure and oxidative defenses. The batch energy input (46.67 Wh for 40 mL) corresponds to EPL ≈ 1.17 kWh L⁻¹, highlighting a purity–energy trade-off relative to some DBD systems; we outline straightforward optimizations (minor O₂/N₂ admixtures, reduced gap, bubbling/recirculation, and active cooling) to enhance RONS yield and energy efficiency without compromising chemical purity. Collectively, these results establish electrode-less SWD as a robust platform for sterile, contamination-free PAW and clarify operational levers that tune performance for biomedical and sanitation applications.