Models based on variable miscibility among hydrogen, molten silicate, and molten iron, coupled with atmospheric escape, can reproduce the observed occurrence density structure of sub-Neptunes and super-Earths in mass-radius space. The models are also consistent with the radius gap and the observed radius-period relationship exhibited by these planets. The degree of overlap between predicted and observed planetary occurrences suggests that hydrogen-silicate-iron miscibility may serve as a unifying concept for the formation and evolution of these planet classes. The well-defined equilibrium conditions at the boundary between supercritical magma oceans and the overlying hydrogen-rich envelopes are important features of the models. Planets formed with less than ~1 % hydrogen by mass develop discrete, terrestrial-like metallic cores, while those accreting greater hydrogen concentrations are predicted to have fully miscible interiors and no discrete metal cores. Hydrogen-silicate-iron miscibility provides an overarching explanation for the full range of sub-Neptune and super-Earth architectures based on the accreted hydrogen mass fraction and the phase equilibria governing silicate, iron metal, and H$_2$ miscibility.

DAMSA (DArk Messenger Searches at an Accelerator) is a novel short-baseline accelerator/beam dump experiment aimed at probing short-lived physics processes, including searches for evidence of a dark sector of particle physics and well-motivated rare Standard Model signals. Motivated by open questions in neutrino physics and the absence of conclusive evidence for conventional weakly interacting massive particles, DAMSA targets MeV-to-sub-GeV dark-sector messengers with feeble couplings that can be produced in abundance at a beam dump/target. By employing an ultra-short baseline, DAMSA is uniquely positioned to overcome the beam-dump "ceiling" that limits sensitivity to fast decaying particles in longer-baseline experiments. The conceptual design emphasizes a beam-dump production scheme combined with a compact detector optimized for rare decays while mitigating intense neutron-induced backgrounds, inherent to high-power proton beams. To validate the experimental strategy and detector technologies, the DAMSA Path-Finder (DPF) proof-of-concept experiment is also proposed, focusing on axion-like particles decaying to two photons, as the benchmark physics case and operating with 8 GeV electron beams at SLAC Linac-to-ESA (LESA) facility. Successful realization of DPF will establish the feasibility of the DAMSA approach, enabling a broad and powerful program to explore short-lived new physics and precision Standard Model processes in a previously inaccessible regime. This paper outlines the technical details of DAMSA's physics goals, key experimental challenges, and how to overcome them.

Finding the host galaxies of stellar-mass compact binary mergers will open a new window for studying their formation histories and measuring key cosmological parameters, such as the Hubble constant. To date, only one merger, GW170817, has had its host galaxy confidently identified through electromagnetic counterpart observations. The large localization volumes from the LIGO-Virgo-KAGRA (LVK) network, combined with the lack of electromagnetic emission for most events, make host identification challenging. However, as the sensitivity of the gravitational-wave (GW) detector network improves, events are becoming increasingly well localized. Furthermore, galaxy luminosity traces mass or star formation rate, and thus correlates with the probability of hosting a merger. Focusing on the most luminous galaxies within the localization volumes of the best-localized GW events, we estimate the corresponding Hubble constant for each galaxy by combining its redshift with the luminosity distance inferred from LVK observations. For the well-localized LVK events \texttt{S250207bg}, \texttt{GW190814}, and \texttt{S250830bp}, we find only $1$, $1$, and $4$ galaxies, respectively, when restricting the analysis to the most luminous $1\%$ of galaxies above $L_{\rm th} \sim 10^{11} h^{-2} L_{\odot}$ in each event's localization volume and adopting a broad $H_0$ prior. The probability of these galaxies being random, and not associated with the GW events, is $29$-$36\%$ across the three events. We encourage further follow-up observations of these candidate host galaxies. We expect this approach to become increasingly powerful in future LVK observing runs, enabling constraints on merger formation histories and measurements of the Hubble constant.

The RPO4 orthophosphates (R = rare earth element) have recently attracted a wide interest due to the strong coupling between their electronic, orbital and structural ordering parameters resulting in a variety of functional properties. Herein, we demonstrate that NdPO4 phases synthesized via a facile precipitation growth process unveil promise in low-temperature magnetic cooling. The analysis of their structural properties reveals nanorod forms with diameters of 10 to 20 nm and lengths ranging from 200 to 500 nm while the heat treatment transforms their hexagonal rhabdophane-type structure to a monoclinic anhydrous monazite-type symmetry. Magnetization measurements and DFT calculations show strong antiferromagnetic couplings and the absence of any magnetic ordering in the 2-300 K range. On the other hand, the monoclinic phase of NdPO4 exhibits a large magnetocaloric effect of about 19 J/kg K under 5 T near 3 K, outperforming some reference materials containing more expensive rare-earth elements with high magnetic moments.

In this research, starting from a widely accepted definition of risk, we support the idea that risk reduction is a more realistic objective than risk minimization, which represents a theoretical utopia. Furthermore, significant risk reduction can be achieved without relying on risk measurement and risk minimization. To this end, we propose a generalization of the numerical rank and the condition number of a matrix, specifically the return matrix in this application. This generalization considers the entire matrix spectrum instead of focusing only on the smallest eigenvalue, as the condition number does. The approach directly provides an order among a finite number of risky scenarios. Risk reduction is obtained by identifying the riskiest scenarios and reducing investment exposures corresponding to them. The validity of this theoretical proposal is supported by a comprehensive experiment performed on real data. The capacity of the proposed approach to effectively reduce risk is proven by measuring the variability of out-of-sample returns for benchmark portfolios-constructed by minimizing standard risk measures-compared to the strategy of reducing exposure in high-risk scenarios. Finally, preventing large losses with limited active management-thereby controlling the impact of transaction costs-not only reduces risk but also preserves the average return and, consequently, the portfolio's Sharpe ratio.

The Quantum Lattice Boltzmann Method (QLBM) has emerged as one of the most promising quantum computing approaches for the numerical simulation of problems in computational fluid dynamics (CFD). The dynamics is formulated in terms of mesoscopic particle distribution functions governed by a discrete Boltzmann transport equation, comprising local streaming and collision operations. In this work, the resulting macroscopic behavior corresponds to the advection-diffusion equation, which we adopt as a canonical model problem for transport phenomena. Building upon recent progress in QLBM implementations, we advance towards more realistic problem settings that better reflect conventional CFD requirements. We address, for the first time, transport under the action of non uniform velocity fields on quantum hardware. We implement our demonstration using IonQ's trapped-ion systems including Forte generation systems and a 64-qubit Barium development system similar to the forthcoming IonQ Tempo line. We identify the density readout and subsequent reloading of the fluid density as a potential bottleneck of the current algorithm and discuss several approaches to mitigate this bottleneck. We identify the use of MPS shadow tomography as a promising method to efficiently scale the readout to large system with complex density distributions. Lastly, we introduce and simulate a novel method to implement wall boundaries for advection-diffusion in QLBM, and discuss the prospects of scaling to higher-complexity problems.

Polar metals, materials in which electric polarisation and metallicity coexist, are exceptionally rare because itinerant electrons screen long-range dipoles and favour centrosymmetric structures. Engineering polar textures in a conducting magnet holds promise for reconfigurable spin orbit coupling and magnetoelectric functionality. Here we show that releasing epitaxial SrRuO3 films from their substrates drives a hierarchy of ferroelastic domain refinement from micrometre to nanometre length scales, and that this structural reorganisation spontaneously generates two distinct classes of emergent polar texture that are ubiquitous across the freestanding membrane. Using correlative microscopy from mesoscale electron channelling contrast imaging (ECCI) to atomic resolution scanning transmission electron microscopy (STEM), we demonstrate that electric polarisation emerges selectively at translation-inequivalent antiphase boundaries (APBs). At these boundaries multicomponent aac tilt field undergoes Neel-like interpolation that preserves the in-phase tilt component and amplifies roto flexoelectric coupling, while translation-equivalent boundaries remain nonpolar. The Neel like interpolation at hard APBs and Ising like collapse of all tilt components at easy APBs is corroborated with ab initio calculations. While embedded 90 ferroelastic walls provide an additional mechanistically distinct source of electric polarisation resulting in polar nanoclusters (4 nm). These distinct nanotextures at 90 walls from via elastic accommodation of strain mismatch between variants and rotostriction as the tilt field interpolates across the boundaries. These findings show that, in a membrane form, metal oxides provide a robust platform for hosting nanoscale ferroelastic domains that generate polar textures.

We investigate temperature quenches across the reentrant phase transition of the antiferromagnetic Ising model in a magnetic field and show that the strong direct and inverse Mpemba effects arise when quenches terminate in the paramagnetic phase. These anomalous relaxation phenomena originate from the selective excitation of the slowest relaxation mode, which in the paramagnetic phase is purely staggered. Consequently, quenches starting from the paramagnetic phase have zero overlap with the slow mode and exhibit a strong (inverse) Mpemba effect. Quenches from the antiferromagnetic phase excite the staggered mode and display a slow-relaxation tail. By varying the lattice coordination number we show that the strong Mpemba effect disappears in the absence of reentrance. Our results provide the first demonstration of the strong (inverse) Mpemba effect in the antiferromagnetic Ising model based on the pair-approximation, and establish a link between anomalous relaxation and the equilibrium phase behavior.

Denote by $p(k)$ the limit, as $n \rightarrow \infty$, of the probability that a random permutation on a set of size $n$ has an invariant set of size $k$. We give an asymptotic formula for $p(k)$, showing that it is asymptotically $f(\{\log_2 k\}) k^{-δ} (\log k)^{-3/2}$ where $δ= 1 - \frac{1 + \log \log 2}{\log 2} \approx 0.086$ and $f$ is a smooth, positive, function on $\mathbb{R}/\mathbb{Z}$, which we will describe explicitly. The function $f$ satisfies $\frac{\max f}{\min f} < 1 + 2 \times 10^{-7}$ and we conjecture that it is not constant. Estimating $p(k)$ is a model for the more well-known question which asks for an estimation of $M(n)$, the number of distinct elements in the $n$-by-$n$ multiplication table. By elaborating on the techniques in this paper, we will give an asymptotic for $M(n)$ in forthcoming work.

We review the quantization of scalar field theory on $λ$-Minkowski space using the Batalin--Vilkovisky (BV) formalism. We consider $ϕ^3$-theory in two different quantization schemes: standard and braided. While standard BV quantization is based on an ordinary $L_\infty$-algebra, braided BV quantization is based on a braided $L_\infty$-algebra. We compare the tree-level three-point and four-point correlation functions in the two approaches. For the four-point function, standard quantization leads to two inequivalent classes of diagrams with different noncommutative contributions, whereas braided quantization yields only a single class of diagrams with noncommutativity entering solely through an overall phase factor depending on the external momenta.

In this paper, we propose a scaled gradient modified non-monotone line search method for solving constrained minimization problems, and explore several specific properties of this method, namely, its convergence analysis. We discuss the linear convergence rate of the sequence generated by the proposed algorithm to a solution of the constrained minimization problem where the objective function is strongly quasiconvex. We consider numerical examples of large-scale fractional programming and quadratic programming for the function of pseudo convex and strongly quasiconvex and compare the performance of the proposed algorithm with the existing ones for these examples.

This paper introduces a general approximate alternating simulation relation (\emph{$\varepsilon$-gAAS relation}) for continuous-time systems, which relaxes existing simulation relations to tolerate larger mismatches between abstract and concrete models. The definition of gAAS for continuous-time systems is first proposed, and its properties are investigated. Then, a control refinement method is developed to enable hierarchical control for the gAAS relation. Finally, case studies demonstrate the effectiveness of the proposed approach, highlighting its advantages over existing methods.

Zn(imidazolate)$_2$ metal-organic frameworks (MOFs) exhibit a remarkable degree of polymorphism. Because of their promising industrial applications, many research groups have investigated phase transitions, phase diagram and relative stability of these polymorphs. There is now wide consensus in the research community that these MOFs are solvothermally formed via non-classical nucleation mechanisms, in which pre-nucleation clusters are first formed, followed by an intermediate amorphous structure that subsequently reorganizes to yield the final crystalline MOF. However, no study up to date has uncovered which part of the synthesis process determines the final polymorph obtained. In this work, path collective variable metadynamics simulations performed with a partially reactive force field give insights into mechanistic and thermodynamic aspects of the self-assembly of these MOFs. Databases of transient and intermediate synthesis structures are built from the simulations. By developing and applying neural network classifiers over these databases, it is found that both pre-nucleation clusters and the amorphous intermediate structures are polymorph-dependent. These results suggest that polymorph selection happens as early as the pre-nucleation cluster stage.

The realization of bulk metallic altermagnetism has remained elusive despite the growing number of candidate materials. Here, we present evidence that moderate cobalt substitution ($\sim$15%) drives the correlated narrow-gap semiconductor FeSb$_2$ into a metallic altermagnetic state persisting up to room temperature. The infrared optical conductivity reveals low-energy interband transitions near 0.1 eV that emerge upon doping and grow with Co concentration. Density functional theory calculations show that these transitions originate exclusively from altermagnetic spin ordering, with spin split bands ($\sim$0.2 meV) of non-relativistic origin, together with spin-orbit coupling induced band splitting of the order of $\sim$5 meV near the Fermi level. Co substitution further leads to Fano lineshapes and mode mixing in the infrared-active phonons, reflecting enhanced electron-phonon coupling and local inversion symmetry breaking, while leaving the altermagnetic spin symmetry intact. Our results establish carrier-tuned FeSb$_2$ as a platform for exploring metallic $d$-wave altermagnetism and its coupling to lattice degrees of freedom.

We provide a unified framework for independence and mean independence tests based on the Hilbert-Schmidt independence criterion, extending some previous results in the literature to hold in general topological spaces. We also present a complete theoretical analysis of the test statistic asymptotic behavior when the observed sample corresponds to a partial sample path of some stationary and ergodic stochastic process under near epoch dependence assumptions. In particular, we explore the test statistic consistency and limit distribution under both fixed and local hypothesis. The finite sample performance of the test(s) is illustrated with a succinct simulation study involving functional data.

We construct bounded, commuting projections for the three-dimensional de Rham complex with the additional property that the projections preserve the trace of functions/fields if the latter is a piecewise polynomial in the appropriate trace space. The projections are locally defined and stable in the graph norm. More precisely, the part of the graph norm involving the exterior derivative only involves the oscillation of this derivative in a narrow strip of elements touching the boundary and weighted by the local mesh size. Moreover, the projections are $L^2$-stable locally when acting on functions/fields whose exterior derivative is a piecewise polynomial in the appropriate space. We present two salient applications of the present bounded, commuting, discrete-trace preserving projections: the construction of stable liftings of piecewise polynomial data and an optimality result on the discrete versus continuous extension of piecewise polynomial data.

Software development is a sociotechnical and human-centered endeavor in which human factors directly influence quality, productivity, and innovation capacity. In this context, career development in computing goes beyond technical mastery, requiring competencies that enable professionals to deal with continuous change and collaborative demands. Among these, non-technical skills (soft skills) stand out, encompassing social, emotional, and communicational dimensions essential to team effectiveness and the success of software projects. Despite their recognized importance, there is still a need for a systematic mapping of the most relevant soft skills over the past 25 years, a period marked by the adoption of agile approaches in industry. This gap limits the integration of human and technical aspects in software development. This study presents a systematic mapping of the literature, analyzing 97 studies published between January 2000 and May 2025 across major scientific databases. The results identify recurring competencies such as communication, adaptability, teamwork, and leadership, as well as their association with different roles in agile contexts. The main agile approaches adopted, particularly Scrum, are also identified, along with key gaps in the literature, such as the lack of studies on role specific soft skills. The findings can support researchers, educators, and practitioners in designing curricula, training strategies, and organizational practices aligned with human factors, reinforcing the importance of integrating social and technical dimensions in the development of collaborative and innovative professionals.

Sensitive biomarker detection in physiological fluids is often limited by Debye screening, which suppresses electrostatic signals at sensor surfaces. Here we report a sensing approach based on flexoelectric resonance in silicon nanowire field-effect transistors. An applied radiofrequency field induces strain gradients in the nanowires, generating flexoelectric polarization that is amplified at resonant frequencies. This effect enhances the sensitivity of conductance measurements to small surface charge variations associated with biomolecular binding. Using C-reactive protein as a model biomarker, we observe an order-of-magnitude improvement in detection sensitivity compared to conventional operation, with a 62% conductance increase versus 30% without radiofrequency modulation. The high-frequency field also perturbs the electrical double layer, reducing Debye screening in high-ionic-strength environments. These combined effects enable direct biomarker detection without sample dilution. This work establishes flexoelectric resonance as a general strategy for improving nanoscale biosensing performance in physiologically relevant conditions.

The bond-valence model is a standard way to estimate bond strengths in crystals, but its exponential dependence on bond length has lacked a derivation from a specific physical interaction. We show that this form emerges as the leading-order limit of screened Coulomb electrostatics and that the fitted bond-valence softness can be interpreted in terms of an electronic screening length. This turns bond valence from an empirical fitting rule into a transferable descriptor of local screened charge response across coordination environments. The resulting theory predicts how the bond-valence parameters should vary with ionic charge and coordination number, and that prediction agrees with 150 fitted valences from 94 cation-oxygen species, including 68 in fourfold coordination and 82 in sixfold coordination, at an abundance-weighted coefficient of determination of 0.986. A comparison with first-principles charge densities shows that the bond-valence shell radius tracks the electronic screening cloud with coefficients of determination of 0.9998 for ten alkali and alkaline-earth oxides and 0.967 for 21 other binary oxides whose nearest-neighbor environments match the theory's assumptions. The widely used bond-valence model is thus the leading-order expression of screened electrostatics in ionic solids.

Metastable cosmic strings are a common prediction of grand unified theories and act as a source of a gravitational-wave background (GWB) that can explain the 2023 pulsar timing array (PTA) signal. In this paper, we revisit the GWB signal from metastable strings, emphasizing the need to carefully distinguish between two different time scales: (i) t_LB, the time scale of loop breaking because of spontaneous monopole nucleation on closed string loops, and (ii) t_NC, the time scale of network collapse when string segments attached to monopoles begin to enter the Hubble horizon. We discuss under which conditions these two time scales are similar or far apart from each other and illustrate the resulting consequences for the GWB signal. In doing so, we generalize the description of the GWB signal from metastable strings to a three-parameter model in terms of the string tension Gμand the time scales t_LB and t_NC, which allows us to unify the modeling of standard metastable strings with what is known as quasi-stable strings. In the limit of a large t_LB/t_NC ratio, we, moreover, derive a compact analytical expression for the predicted GWB spectrum in excellent agreement with numerical results in the literature. We thus conclude that our new templates for the GWB spectrum from metastable strings can be readily used in the analysis of future PTA data sets.

We propose new graph representations that exploit dense local structure to improve time and space simultaneously. Given an undirected graph $G$, we define a dual clique cover (DCC) representation of $G$ to be the pair $(C, L)$, where $C$ is a collection of cliques that covers the edges of $G$ and $L$ is the incidence dual of $C$. We identify classes of polynomial-time constructible DCC representations that are compact and call them succinct DCC representations. We then develop representation-aware algorithms for several fundamental graph problems. We show that graph primitives such as connected components, breadth-first search forests, depth-first search forests, and maximal matchings can be computed in time proportional to the size of a DCC representation rather than the number of edges. Combined with our succinct DCC representations, these results give a class of algorithms that either match or improve the time and space bounds of their counterparts on standard graph representations. Furthermore, we design several algorithms for constructing succinct DCC representations and establish provable guarantees on their efficiency. We evaluate several graph algorithms on DCC representations against adjacency-list-based implementations on a large collection of real-world and synthetic graphs. All evaluated applications show substantial execution memory savings and total-time speedups; for example, the connected components algorithm achieves about $9\times$ execution memory savings on average, with a maximum of $35\times$, and about $6.5\times$ total-time speedups on average, with a maximum of $35\times$. We also evaluate several DCC construction algorithms and find that the succinctness property plays a key role in making DCC representations effective for algorithmic applications.

Ta$_{3}$N$_{5}$ is among the most intensively studied photoanode materials for solar-driven water oxidation, yet its performance often remains limited by short carrier lifetimes and defect mediated recombination. Although transient absorption spectroscopy is widely used to probe carrier dynamics in photoelectrodes, spectral assignments are frequently ambiguous due to overlapping contributions. Here, microsecond-to-second transient absorption of Ta$_{3}$N$_{5}$ thin films is combined with complementary optical spectroscopies to disentangle contributions from lattice heating, electrostatics, and defect states. Photoreflectance reveals three critical points in the Ta$_{3}$N$_{5}$ band structure, including two anisotropic near-edge transitions at 2.14 eV and 2.27 eV and a higher-lying transition near 2.80 eV, all closely aligned with dominant transient absorption features. A previously unreported photo-induced absorption at 2.80 eV is attributed to pump-induced lattice heating, while potential-dependent measurements reveal that near-edge bleach features arise from pump-induced band flattening and subsequent surface photovoltage relaxation. Fitting transient absorption spectra with independently measured thermal and electrostatic components enables quantification of both thermal and photovoltage dynamics, while the sub-bandgap response provides insight into the redistribution of defect charge states. Thus, this approach to quantifying thermal, electrostatic, and defect-mediated contributions to microsecond-to-second transient absorption provides broadly applicable insights into photoexcitation and relaxation mechanisms in functional semiconductor photoelectrodes.

In 1967 Hajnal and Juh{á}sz showed that the cardinality of a first-countable Hausdorff space with the countable chain condition has cardinality at most $\mathfrak{c}$, the cardinality of the real line. We give an improvement of this celebrated theorem by replacing ``first-countable" with the weaker condition ``each point has a countable centered local $π$-base". Given a point $p$ in a topological space $X$, a \emph{local} $π$-\emph{base} $\scr{B}$ at $p$ acts like a neighborhood base at $p$ except that $p$ may not be in any member of $\scr{B}$. A local $π$-base $\scr{B}$ has the \emph{finite intersection property} if any finite intersection of members of $\scr{B}$ is nonempty. We call this type of local $π$-base \emph{centered}. A centered local $π$-base behaves even more like a neighborhood base in a sense. A space has the \emph{countable chain condition} if every family of pairwise disjoint open sets is countable. We also improve a theorem of Pospi{\v s}il from 1937 using centered local $π$-bases. As is customary, examples are given to demonstrate these improvements are strict. Compact Hausdorff spaces are also explored in this connection, along with variations on the notion of a centered local $π$-base.

The nonlinear Hall effect (NLHE) connects crystalline symmetry to quantum geometry, offering a probe of band topology beyond linear transport. While most studies have focused on the Berry curvature dipole in low-symmetry crystals, mechanisms that directly probe Berry monopoles in higher-symmetry chiral lattices remain unexplored. Here, we report the observations of the NLHE in the chiral Weyl semimetal CoSi, a platform where the Berry curvature dipole is symmetry-forbidden. By employing focused ion beam-fabricated crossbar devices, we detect a robust second-harmonic Hall voltage under zero magnetic field, hosting all key signatures of the NLHE. Theoretical analysis attributes the nonlinear Hall conductivity to skew scattering of self-rotating electron wave packets, whose chirality is dictated by the underlying band topology, a process reminiscent of the classical Magnus effect. Furthermore, the NLHE signal exhibits a temperature-dependent sign reversal, and a strong, linearly field-dependent modulation that grows with carrier mobility, directly reflecting the topological Weyl nodes distribution near the Fermi level. These findings establish CoSi as a platform for Berry monopole-driven nonlinear transport, demonstrating a skew-scattering route to topological nonlinear Hall responses that bypasses conventional symmetry constraints.

This article presents a systematic review of theoretical and experimental findings for bound states of two and several dissipative solitons in fiber lasers. The theoretical basis underlying the formation and stabilization of soliton molecules in the fibers, which is provided by the complex Ginzburg-Landau equations and bound states of such equations, is presented in necessary detail, which is followed by a detailed presentation of experimental findings, including very recent ones. In particular, included are the results for the multi-soliton bound states in the fibers, as well as for the bound states in the temporal and frequency domains, single-component (scalar) and two-component (vector), two- and multi-soliton modes, as well as for bound states of spatiotemporal dissipative solitons in the lasers based on multimode fibers.

Altermagnets host spin-split band structures while exhibiting vanishing equilibrium spin magnetization, making field-induced responses a direct probe of their quantum geometry. A central question, in this regard, is which quantum-geometric mechanism can generate a linear spin magnetization in centrosymmetric systems. Here we develop a unified framework based on a generalized quantum geometric tensor that incorporates both momentum translations and spin rotations of Bloch states, and decompose spin magnetization into equilibrium, electric-field-driven, and magnetic-field-driven contributions. We show that inversion symmetry forbids the linear electric-field response in centrosymmetric systems, while $C_n T$ symmetry further suppresses the equilibrium contribution in altermagnets. Consequently, centrosymmetric altermagnets provide a particularly clean realization in which the magnetic-field-induced spin magnetization emerges as the only symmetry-allowed linear quantum-geometric response. We demonstrate that this contribution originates entirely from the spin-rotation quantum metric, establishing it as the sole linear quantum-geometric mechanism in such systems. Using representative centrosymmetric altermagnets, including the $d$-wave compound $\mathrm{FeSb}_2$ and the $g$-wave compound $\mathrm{CrSb}$, we show that the spin-rotation quantum metric directly controls this response. Crucially, we predict a giant linear spin magnetization of order $10^{-2}μ_B\,\mathrm{nm}^{-3}$ at magnetic fields of $\sim 10\,\mathrm{mT}$, exceeding typical experimental values for conventional magnets by several orders of magnitude. Our results identify a universal quantum geometric mechanism of spin magnetization operative in centrosymmetric systems in general, and establish centrosymmetric altermagnets as an ideal platform for its experimental detection with potential applications in spintronics.

This paper investigates the existence and uniqueness of solutions for a nonlinear evolution equation governed by an m-accretive operator A in a Banach space, presenting a perturbation term that does not satisfy the Lipschitz condition.

In this article we show that the semi log canonical abundance for compact Kähler varieties fails in dimension $3$. More specifically we construct a counterexample of a compact Kähler (irreducible) slc threefold $(X, 0)$ such that $K_X$ is nef and $κ(\tilde X, K_{\tilde X}+\tilde D)=0$, where $μ:(\tilde X, \tilde D)\to X$ is the normalization morphism, but $K_X$ is not semiample. On the other hand, we show that if we start with a compact Kähler semi-dlt pair, then the abundance does hold, i.e., if $(X, Δ)$ is a compact Kähler sdlt pair of dimension $3$ such that $K_X+Δ$ is nef, then it is semiample. We also show that if $(X, Δ)$ is a compact Kähler slc pair of dimension $3$, $K_X+Δ$ is nef, and $κ(X'_i, Δ'_i+D'_i)>0$ for all $i$, where $μ:\sqcup(X'_i, Δ'_i+D'_i)\to (X,Δ)$ is the normalization, then $K_X+Δ$ is semiample.

The rapid electrification and intelligence of modern transportation systems place stringent demands on the electromagnetic compatibility, reliability, and adaptability of automotive power electronics. In electric and autonomous vehicles, electromagnetic interference (EMI) generated by high-frequency switching power converters can compromise safety-critical functions, in-vehicle communications, and system efficiency under dynamic operating conditions. Conventional passive EMI filters, while robust, are often oversized and lack adaptability, leading to increased weight, volume, and energy losses. This paper proposes an intelligent self-tuning active EMI filtering approach for electrified automotive power systems based on reinforcement learning (RL). The EMI mitigation problem is formulated as a Markov decision process, enabling an RL agent to continuously adapt filter parameters in response to time-varying interference characteristics. To improve robustness and generalisation under complex and non-stationary conditions, a variational autoencoder is employed for compact state representation, while a noise-based exploration mechanism enhances learning efficiency and prevents suboptimal convergence. The proposed method is evaluated using experimentally measured EMI spectra from an automotive electric drive unit within a MATLAB/Simulink co-simulation framework. Results demonstrate consistent EMI attenuation improvements of 25-30 dB across a wide frequency range compared with conventional control strategies and passive filtering solutions. By reducing reliance on oversized passive components and enabling adaptive EMI suppression, the proposed framework supports lightweight, energy-efficient, and reliable power-electronic systems for intelligent and green transportation applications.

Semiconductor-based plasmonic nanostructures support localized surface plasmon modes in the infrared region. Unlike metallic nanostructures, they support both free electrons and holes, requiring a two-fluid hydrodynamic Drude equation (HDE) to accurately capture spatial dispersion effects and low-frequency acoustic plasmon modes that cannot be described by single-fluid models. In this work, a volume integral equation (VIE)-based solver is proposed for the analysis of electromagnetic scattering from semiconductor nanostructures. The proposed approach couples the VIE, formulated in terms of the electric flux density and the free-electron and hole polarization currents, with the two-fluid HDE. The coupled system is discretized using a tetrahedral mesh and solved efficiently using a two-level iterative solver. In contrast to finite-element-based methods, the proposed VIE-based approach does not require domain-wide meshing and inherently satisfies the radiation condition, thereby eliminating artificial absorbing boundaries. Numerical results for InSb-type semiconductor nanostructures demonstrate the accuracy and efficiency of the proposed VIE-based solver and its ability to capture unique optical phenomena, such as acoustic plasmon resonances and the blueshift of localized surface plasmon resonances, that cannot be described by the single-fluid HDE or classical Drude-based models.