Search Results (156)

We present a unified description of dense matter and neutron star structure based on simple but physically motivated models. Starting from the thermodynamics of degenerate Fermi gases, we construct an equation of state for cold, catalyzed matter by combining relativistic fermion statistics with the liquid drop model of nuclear binding. The internal stratification of matter in the outer crust is described by the $\beta$-equilibrium, neutron drip and a gradual transition to supranuclear matter. Short-range repulsive interactions inspired by Quantum Hadrodynamics are incorporated at high densities in order to ensure stability and causality. The resulting equation of state is used as input in the Tolman–Oppenheimer–Volkoff equations, yielding self-consistent neutron star models. We compute macroscopic stellar properties including the mass–radius relation, compactness and surface redshift that can be compared with recent observational data. Despite the simplicity of the underlying microphysics, the model produces neutron star masses and radii compatible with current observational constraints from X-ray timing and gravitational-wave measurements. This work demonstrates that physically transparent models can capture the essential features of neutron star structure and provide valuable insight into the connection between dense-matter physics and astrophysical observables; they can also be used as easy-to-handle models to test the impact of more complicated phenomena and variations in neutron stars. Full article

We present a detailed derivation of the quantum and quantum–thermal effective action for non-relativistic systems, starting from the single-particle case and extending to the Gross–Pitaevskii (GP) field theory for weakly interacting bosons. In the single-particle framework, we introduce the one-particle-irreducible (1PI) effective action formalism, taking explicitly into account the choice of the initial quantum state, its saddle-point plus Gaussian-fluctuation approximation, and its finite-temperature extension via Matsubara summation, yielding a clear physical interpretation in terms of zero-point and thermal contributions to the Helmholtz free energy. The formalism is then applied to the GP action, producing the 1PI effective potential at zero and finite temperature, including beyond-mean-field Lee–Huang–Yang and thermal corrections. We discuss the gapless and gapped Bogoliubov spectra, their relevance to equilibrium and non-equilibrium regimes, and the role of regularization. Applications include the inclusion of an external potential within the local density approximation, the derivation of finite-temperature Josephson equations, and the extension to D-dimensional systems, with particular attention to the zero-dimensional limit. This unified approach provides a transparent connection between microscopic quantum fluctuations and effective macroscopic equations of motion for Bose–Einstein condensates. Full article

Accurate equilibrium-line altitude (ELA) estimates are a valuable proxy for evaluating glacier mass balance conditions and interpreting climate-driven change in the Canadian high Arctic, where sustained in situ observations are limited. A scalable remote-sensing framework is evaluated to extract the snow cover ratio (SCR) and snowline altitude (SLA) on White Glacier (Axel Heiberg Island, Nunavut) and to assess the agreement with in situ ELA measurements. Ten-metre Sentinel-2 imagery (2019–2024) is processed with a hybrid pipeline comprising the principal component analysis (PCA) of four bands (B2, B3, B4, and B8), unsupervised K-means for pseudo-label generation, and a Random Forest (RF) classifier for snow/ice/ground mapping. SLA is defined based on the date of seasonal minimum SCR using (i) a snowline pixel elevation histogram (SPEH; mode) and (ii) elevation binning with SCR thresholds (0.5 and 0.8). Validation against field-derived ELAs (2019–2023) is performed; formal SLA precision from DEM and binning is quantified ($\pm 4.7$ m), and associations with positive degree days (PDDs) at Eureka are examined. The RF classifier reproduces the spectral clustering structure with >99.9% fidelity. Elevation binning at $\mathrm{SCR}\ge 0.8$ yields SLAs closely matching field ELAs (Pearson $r=0.994$, $p=0.0006$; RMSE $=30$ m), whereas SPEH and lower-threshold binning are less accurate. Interannual variability is pronounced as follows: minimum SCR spans 0.46–0.76 and co-varies with SLA; correlations with PDDs are positive but modest. Results indicate that high-threshold elevation-bin filtering with machine learning provides a reliable proxy for ELA in clean-ice settings, with potential transferability to other data-sparse Arctic sites, while underscoring the importance of image timing and mixed-pixel effects in residual SLA–ELA differences. Full article

We briefly review the early development of the mean-field dynamics for cooperatively interacting quantum many-body systems, mapped to pseudo-spin (Ising-like) systems. We start with (Anderson, 1958) pseudo-spin mapping the BCS (1957) Hamiltonian of superconductivity, reducing it to a mean-field Hamiltonian of the XY (or effectively Ising) model in a transverse field. Then, we obtain the mean-field estimate for the equilibrium gap in the ground-state energy at different temperatures (gap disappearing at the transition temperature), which fits Landau’s (1949) phenomenological theory of superfluidity. We then present in detail a general dynamical extension (for non-equilibrium cases) of the mean-field theory of quantum Ising systems (in a transverse field), following de Gennes’ (1963) decomposition of the mean field into the orthogonal classical cooperative (longitudinal) component and the quantum (transverse) component, with each of the component following Suzuki–Kubo (1968) mean-field dynamics. Next, we discuss its applications to quantum hysteresis in Ising magnets (in the presence of an oscillating transverse field), to quantum heat engines (employing the transverse Ising model as a working fluid), and to the quantum annealing of the Sherrington–Kirkpatrick (1975) spin glass by tuning down (to zero) the transverse field, which provides us with a very fast computational algorithm, leading to ground-state energy values converging to the best-known analytic estimate for the model. Finally, we summarize the main results obtained and draw conclusions about the effectiveness of the de Gennes–Suzuki–Kubo mean-field equations for the study of various dynamical aspects of quantum condensed matter systems. Full article

Understanding the microscopic interaction between agricultural tillage tools and soil is essential for improving wear resistance. In this study, molecular dynamics (MD) simulations are employed to investigate the tribological behavior of the Fe–SiO₂ interface under varying loads and sliding velocities. The results demonstrate that the coefficient of friction increases with both normal load and sliding velocity, accompanied by a clear running-in stage. Under high loads, significant plastic deformation occurs, characterized by asymmetric atomic pile-up, expansion of the strain field, and heterogeneous von Mises strain distribution. Energy analysis reveals intensified kinetic and potential energy variations, indicating enhanced defect accumulation and interfacial non-equilibrium states. Temperature distributions are highly localized at the interface, with thermal saturation observed under high-velocity conditions. Mean square displacement (MSD) results confirm that higher loads and velocities promote atomic migration and plastic flow. This study provides atomic-scale insights into wear mechanisms under extreme mechanical conditions, offering theoretical support for the design of durable soil-engaging components in agricultural machinery. Full article

This paper reports a novel effort to estimate and evaluate the coefficients of Hg transfer across the water/air interface in lakes such as Cane Creek Lake (CCL, Cookeville, TN, USA). This was accomplished by calculating the coefficients (k_w) using the Two-Thin Film (TTF) Model for Hg transfer together with the field-measured data of Hg emission flux (F), dissolved gaseous mercury concentration (DGM), air Hg concentration (C_a), and water temperature for Henry’s coefficient (K_H) obtained from a separate field study at the CCL. The daily mean k_w values range from 0.045 to 0.21 m h⁻¹, with the min. at 0.0025–0.14 and the max. at 0.079–0.41 m h⁻¹, generally higher for the summer, and from 0.0092 to 0.15, with the min. at 0.0032–0.033 and the max. at 0.017–0.31 m h⁻¹, generally lower for the fall and winter, exhibiting an apparent seasonal trend. The highest k_w values occur in August (mean: 0.21, max.: 0.41 m h⁻¹). Our k_w results add to and enrich the aquatic interfacial Hg transfer coefficient database and provide an alternative avenue to evaluate and select the coefficients for the TTF Model’s application. The k_w results are of value in gaining insights into the Hg transfer actually occurring across the water/air interface under environmental influences (e.g., wind/wave, solar radiation). Our k_w results do not show a clear, consistent correlation of k_w with wind/wave effect, nor sunlight effect, in spite of some correlations in sporadic cases. Generally, the k_w values do not exbibit the trends prescribed by the model sensitivity study. The comparisons of our k_w results with those obtained using wind-based transfer models (the Liss/Merlivat Model, the Wanninkhof Model, and the modified linear model) show that they depart from each other. The findings of this study indicate that the TTF Model has limitations and weaknesses. One major assumption of the TTF Model is the equilibrium of the Hg distribution between the air and water films across the water/air interface. The predominant oversaturation of DGM shown by our DGM data evidently challenges this assumption. This study suggests that aquatic interfacial Hg transfer is considerably more complicated, involving a group of factors, more than just wind and wave. Full article

Oxidative and glycolytic metabolism produce energy in the form of ATP and produce intermediates for biomass production. Oxidative metabolism predominates under normoxic conditions and in quiescent or slowly proliferating cells. On the other hand, under hypoxic or pseudohypoxic conditions and in rapidly proliferating cells, glycolysis becomes the predominant pathway. The balance between oxidative and glycolytic metabolism is finely tuned in physiological conditions and becomes dysregulated in many pathological conditions, most notably cancer. In this article we summarize the evidence that has been gathered over the last few years on the mechanisms underlying this balance and the consequences of their dysregulation. We discuss first the non-metabolic factors (mitochondria, cell cycle, cell type, tissue type), then molecules that are at the intersection between glycolytic and oxidative metabolism and those molecules that are inherent to oxidative or glycolytic metabolism that affect the equilibrium between the two energy-producing pathways. Eventually, we discuss pharmacologic or genetic means that allow manipulating this equilibrium. As will be seen, lactic acidosis has taken center stage in this field and lactate has been shown to fuel oxidative metabolism. This suggests that if glycolytic metabolism predominates, as has often been shown in cancer, mechanisms come into work that reestablish a metabolic heterogeneity. Thus, while one pathway may be predominant over the other, it seems as if fail-safe mechanisms are at work that avoid the possibility that it becomes the only energy-producing pathway. Eventually, we discuss possible therapeutic consequences that may derive from this expanding knowledge, in particular, as regards tumor therapy. Full article

We develop a symmetry-based variational theory that shows the coarse-grained balance of work inflow to heat outflow in a driven, dissipative system relaxed to the golden ratio. Two order-2 Möbius transformations—a self-dual flip and a self-similar shift—generate a discrete non-abelian subgroup of $\mathrm{PGL}(2,\mathbb{Q}\left(\sqrt{5}\right))$. Requiring any smooth, strictly convex Lyapunov functional to be invariant under both maps enforces a single non-equilibrium fixed point: the golden mean. We confirm this result by (i) a gradient-flow partial-differential equation, (ii) a birth–death Markov chain whose continuum limit is Fokker–Planck, (iii) a Martin–Siggia–Rose field theory, and (iv) exact Ward identities that protect the fixed point against noise. Microscopic kinetics merely set the approach rate; three parameter-free invariants emerge: a $62\%:38\%$ split between entropy production and useful power, an RG-invariant diffusion coefficient linking relaxation time and correlation length ${\mathcal{D}}_{\alpha }={\xi }^z/\tau$, and a $\vartheta ={45}^{\circ }$ eigen-angle that maps to the golden logarithmic spiral. The same dual symmetry underlies scaling laws in rotating turbulence, plant phyllotaxis, cortical avalanches, quantum critical metals, and even de-Sitter cosmology, providing a falsifiable, unifying principle for pattern formation far from equilibrium. Full article

For densities beyond nuclear saturation, there is still a large uncertainty in the equations of state (EoSs) of dense matter that translate into uncertainties in the internal structure of neutron stars. The MUSES Calculation Engine provides a free and open-source composable workflow management system, which allows users to calculate the EoSs of dense and hot matter that can be used, e.g., to describe neutron stars. For this work, we make use of two MUSES EoS modules, i.e., Crust Density Functional Theory and Chiral Mean Field model, with beta-equilibrium with leptons enforced in the Lepton module, then connected by the Synthesis module using different functions: hyperbolic tangent, generalized Gaussian, bump, and smoothstep. We then calculate stellar structure using the QLIMR module and discuss how the different interpolating functions affect our results. Full article

Carbon is one of nature’s basic elements, hosting a tremendous number of allotropes benefiting from its capacity to generate $sp$, $s{p}^2$, and $s{p}^3$ hybridized carbon–carbon bonds. The exploration of novel carbon architectures has remained a pivotal focus in the fields of condensed matter physics and materials science for an extended period. In this paper, we, by using first-principles calculation, carry on a detailed investigation an an all-$s{p}^3$ hybridized carbon structure in a 20-atom tetragonal unit cell with $P{4}_3{2}_{1}2$ symmetry ($D_4^8$, space group No. 96), and call it T20 carbon. The equilibrium energy of T20 carbon is −8.881 eV/atom, only 0.137 eV/atom higher than that of diamond, indicating that T20 is a superstable carbon structure. T20 is also a superhard carbon structure with a large Vicker’s hardness about 83.5 GPa. The dynamical stability of T20 was verified by means of phonon band spectrum calculations. Meanwhile, its thermal stability up to 1000 K was verified via ab initio molecular dynamics simulations. T20 is an indirect band-gap insulator with approximately 5.80 eV of a band gap. This value is obviously greater than the value in the diamond (5.36 eV). Moreover, the simulated X-ray diffraction pattern of T20 displays a remarkable match with the experimental data found in the milled fullerene soot, evidencing that T20 may be a potential modification discovered in this experimental work. Our work has given a systematical understanding on an all-$s{p}^3$ hybridized superstable and superhard carbon allotrope with large band gap and provided a very competitive explanation for previous experimental data, which will also provide guidance for upcoming studies in theory and experiment. Full article

This work shows a three-dimensional (3D) layerwise model for static and free vibration analyses of functionally graded piezomagnetic materials (FGPM) spherical shell structures where magnetic and elastic fields are completely coupled. The 3D magneto-elastic governing equations for spherical shells are made of the three equations of equilibrium in three-dimensional form and the three-dimensional divergence equation for the magnetic induction. Governing equations are written in the orthogonal mixed curvilinear reference system ($\alpha$, $\beta$, z) allowing the analysis of several curved and flat geometries (plates, cylindrical shells and spherical shells) thanks to proper considerations of the radii of curvature. The static cases, actuator and sensor configurations and free vibration investigations are proposed. The resolution method uses the imposition of the Navier’s harmonic forms in the two in-plane directions and the exponential matrix methodology in the transverse normal direction. Single-layered and multilayered simply-supported FGPM structures have been investigated. In order to understand the behavior of FGPM structures, numerical values and trends along the thickness direction for displacements, stresses, magnetic potential, magnetic induction and free vibration modes are proposed. In the results section, a first assessment phase is proposed to demonstrate the validity of the formulation and to fix proper values for the convergence of results. Therefore, a new benchmark section is presented. Different cases are proposed for several material configurations, load boundary conditions and geometries. The possible effects involved in this problem (magneto-elastic coupling and effects related to embedded materials and thickness values of the layers) are discussed in depth for each thickness ratio. The innovative feature proposed in the present paper is the exact 3D study of magneto-elastic coupling effects in FGPM plates and shells for static and free vibration analyses by means of a unique and general formulation. Full article

This paper investigates Mean Field Game methods to solve missile interception strategies in three-dimensional space, with a focus on analyzing the pursuit–evasion problem in many-to-many scenarios. By extending traditional missile interception models, an efficient solution is proposed to avoid dimensional explosion and communication burdens, particularly for large-scale, multi-missile systems. The paper presents a system of stochastic differential equations with control constraints, describing the motion dynamics between the missile (pursuer) and the target (evader), and defines the associated cost function, considering proximity group distributions with other missiles and targets. Next, Hamilton–Jacobi–Bellman equations for the pursuers and evaders are derived, and the uniqueness of the distributional solution is proved. Furthermore, using the $ϵ$-Nash equilibrium framework, it is demonstrated that, under the MFG model, participants can deviate from the optimal strategy within a certain tolerance, while still minimizing the cost. Finally, the paper summarizes the derivation process of the optimal strategy and proves that, under reasonable assumptions, the system can achieve a uniquely stable equilibrium, ensuring the stability of the strategies and distributions of both the pursuers and evaders. The research provides a scalable solution to high-risk, multi-agent control problems, with significant practical applications, particularly in fields such as missile defense systems. Full article

Generative diffusion models have achieved spectacular performance in many areas of machine learning and generative modeling. While the fundamental ideas behind these models come from non-equilibrium physics, variational inference, and stochastic calculus, in this paper we show that many aspects of these models can be understood using the tools of equilibrium statistical mechanics. Using this reformulation, we show that generative diffusion models undergo second-order phase transitions corresponding to symmetry breaking phenomena. We show that these phase transitions are always in a mean-field universality class, as they are the result of a self-consistency condition in the generative dynamics. We argue that the critical instability arising from these phase transitions lies at the heart of their generative capabilities, which are characterized by a set of mean-field critical exponents. Finally, we show that the dynamic equation of the generative process can be interpreted as a stochastic adiabatic transformation that minimizes the free energy while keeping the system in thermal equilibrium. Full article

This paper presents a new algorithm for assessing the reliability of three-dimensional (3D) slope stability considering the spatial variability of soil based on the Particle Swarm Optimization (PSO) algorithm. First, a 3D random field is generated using the Karhunen–Loève (K-L) expansion method. Then, the simplified Bishop method of limit equilibrium is coupled with the PSO algorithm to calculate safety factors of the slope. Finally, the failure probability of the slope is determined using the Monte Carlo Simulation method. After validating the rationality of the proposed method through a typical case study, this paper offers an in-depth examination of how soil spatial variability affects the stability of 3D slopes. It is observed that, given identical soil correlation lengths, slope geometric parameters, and failure surface widths, the failure probability is positively correlated with soil spatial variability parameters, while the mean safety factor demonstrates an inverse relationship with these variability parameters. Additionally, the failure probability tends to increase as the soil correlation lengths increase, and it also escalates with the expansion of the failure surface width. In contrast, the mean safety factor exhibits an upward trend with the augmentation of the horizontal correlation length, while it diminishes progressively as the vertical correlation length grows, and it also shows a decline with the widening of the failure surface width. The proposed algorithm significantly improves computational efficiency while ensuring accuracy, making it suitable for the reliability analysis of three-dimensional slopes. Full article

To explore the coupling relationship between information propagation behaviors and evolution dynamics in swarm systems, this paper establishes the SEBAR model based on mean field theory with a macroscopic view of information dissemination. Then, the balance points and basic reproduction number are calculated and a proof of equilibrium stability from the point of view of system stability is given. In addition, the influence of model parameters on propagation behaviors is also analyzed. To stimulate the emergence of cooperative behaviors in a swarm system, a repeated “prisoner’s dilemma” game based on controllable individuals is proposed under the framework of bionic “soft control”. The combination of information propagation and game strategies is used to realize information regulation. The simulation results show that the proposed models and methods can reflect the information communication patterns and evolution characteristics. It also illustrates the viability and effectiveness of regulating information through the evolutionary game. Full article