The systematic analysis of user-generated social media content, especially when enriched with geospatial context, plays a vital role in domains such as disaster management and public opinion monitoring. Although multimodal approaches have made significant progress, most existing models remain fragmented, processing each modality separately rather than integrating them into a unified end-to-end model. To address this, we propose an unsupervised, multimodal graph-based methodology that jointly embeds semantic and geographic information into a shared representation space. The proposed methodology comprises two architectural paradigms: a mono graph (MonoGrah) model that jointly encodes both modalities, and a multi graph (MultiGraph) model that separately models semantic and geographic relationships and subsequently integrates them through multi-head attention mechanisms. A composite loss, combining contrastive, coherence, and alignment objectives, guides the learning process to produce semantically coherent and spatially compact clusters. Experiments on four real-world disaster datasets demonstrate that our models consistently outperform existing baselines in topic quality, spatial coherence, and interpretability. Inherently domain-independent, the framework can be readily extended to diverse forms of multimodal data and a wide range of downstream analysis tasks.

It is shown that the Kerr metric represents the nonlinear superposition of self-dual and anti-self-dual Taub-NUT instantons. This promotes the Newman-Janis algorithm to a rigorous derivation of the Kerr metric with a definite physical origin. In the same way, the Kerr-Newman and charged Kerr-Taub-NUT solutions are systems of Taub-NUT instantons and chiral dyons.

Grant-free (GF) access is essential for massive connectivity but faces collision risks due to uncoordinated transmissions. While user-side sensing can mitigate these collisions by enabling autonomous transmission decisions, conventional methods become ineffective in overloaded scenarios where active streams exceed receive antennas. To address this problem, we propose a differential stream sensing framework that reframes the problem from estimating the total stream count to isolating newly activated streams via covariance differencing. We analyze the covariance deviation induced by channel variations to establish a theoretical bound based on channel correlation for determining the sensing window size. To mitigate residual interference from finite sampling, a deep learning (DL) classifier is integrated. Simulations across both independent and identically distributed flat Rayleigh fading and standardized channel environments demonstrate that the proposed method consistently outperforms non-DL baselines and remains robust in overloaded scenarios.

We study overdamped stochastic dynamics confined by hard reflecting boundaries and show that the combination of boundary geometry and an anisotropic diffusion tensor generically generates directed motion. At the level of individual trajectories, the no-flux condition enforces an oblique reflection at the boundary, which produces a systematic drift parallel to the surface. The resulting local velocity takes the general form $v_B(\mathbf{x})=\mathbf{t}(\mathbf{x})^{\!\top}\mathbf{D}\,\mathbf{n}(\mathbf{x})$, determined by the diffusion tensor $\mathbf{D}$ and the local boundary geometry encoded in the normal $\mathbf{n}$ and tangent $\mathbf{t}$. While this boundary-induced drift is local, it can accumulate into a macroscopic response, depending on the statistics of boundary encounters. We illustrate how this local boundary-induced drift gives rise to macroscopic transport using a minimal one-dimensional dimer composed of two particles with unequal diffusion coefficients. The repeated collisions act as reflections in configuration space and lead to sustained center-of-mass motion, including regimes of absolute negative mobility under constant forcing.

We study the effect of a finite volume for pion-pion scattering within Chiral Perturbation Theory (ChPT) and the Inverse Amplitude Method (IAM) in a $L^3$ box (rest frame). Our full ChPT calculation takes into account the discretization not only in the $s$-channel loops but also in the $t,u$- channels and tadpole contributions. Hence, not only the unitarity right-hand cut but also the left-hand one continuum contributions are calculated in the finite volume. A proper extension of the standard Veltman-Pasarino identities is needed, as well as a suitable projection on the internal space spanned by the irreducible representations (irreps) of the octahedral group, based on either a finite set of cubic harmonics or the matrices which represent the irreps properly. From the ChPT we construct the IAM in the internal space, which provides the full volume dependence of the interacting energy levels of two-pions scattering in the finite volume. Our results for various low-energy constants sets show sizable corrections with respect to previous analyses in the literature for $ m_πL \lesssim 2$, being compatible with energy levels lattice data. We expect that our analysis and results will help to optimize the process of determination of energy levels and phase-shifts with higher accuracy.

Polar-structure galaxies (PSGs) host photometrically and kinematically decoupled components oriented at large angles to one another. These systems, which include polar rings, polar disks, polar halos, polar bulges, polar dust lanes, and polar tidal structures, provide valuable insights into galaxy formation and evolution, although their rarity has limited statistical studies. We aim to construct the largest and most homogeneous catalog of PSGs to date in order to enable robust statistical studies of their properties and occurrence rates in the local Universe. Using DESI Legacy Imaging Surveys (DR10) data, we identified PSG candidates in the Siena Galaxy Atlas (SGA) through visual inspection, convolutional neural network classification, and cross-matching with previously reported systems. Each galaxy was assigned a PSG subtype and host morphology. We analyzed general properties of PSGs and compared them with those for all galaxies in the SGA. Simple image simulations were used to evaluate projection effects. The resulting Catalog of Unusual Galaxies with polar Structures in the DESI Legacy Imaging Surveys (COUGS-DESI) contains 2,989 PSG candidates, including 342 previously known objects. Projection effects from random galaxy overlaps are negligible. The sample spans a wide range of polar morphologies, with 1,113 polar rings, 75 polar bulges, 216 polar halos, 185 polar dust lanes, and 1,315 polar tidal structures. PSGs constitute 2.2% of local non-dwarf galaxies, with polar rings representing 0.7%. Approximately 1% of S0 galaxies in the SGA host polar rings, whereas spirals constitute the most common morphological type among the PSG hosts in our catalog. COUGS--DESI increases the number of known PSG candidates by an order of magnitude and provides a foundation for detailed studies of the formation and evolution of polar structures.

We present the spectroscopic confirmation and in-depth analysis of AURORA-LQG1, a low-mass quiescent galaxy at $z_{\rm spec}=2.0834$ with $\log(M_\star/M_\odot)=9.6$ observed with medium-resolution JWST/NIRSpec spectroscopy. The deep medium-resolution spectrum enables the measurement of its stellar velocity dispersion ($σ_\star = 95_{-33}^{+38}\,{\rm km\,s^{-1}}$), the smallest value recorded among spectroscopically confirmed quiescent galaxies at $z\sim2$. Coupled with a compact size ($0.41\pm0.03\, {\rm kpc}$), it yields a dynamical mass estimate of $\log(M_{\rm dyn}/M_\odot)=9.75_{-0.38}^{+0.29}$. Its star formation history suggests that half of the stellar mass was in place $\sim1\,{\rm Gyr}$ before the observed epoch, with quenching occurring $\sim0.2\,{\rm Gyr}$ prior to $z=2.08$. These results confirm that AURORA-LQG1 is genuinely quenched, rather than in a temporary phase of suppressed star formation rate. AURORA-LQG1 is consistent with the mass fundamental plane at $z\sim2$, previously constrained only by massive quiescent systems. Compared with more massive counterparts at the same epoch observed with NIRSpec grating spectroscopy, the time since quenching for AURORA-LQG1 is among the shortest observed. The galaxy resides in a possible dense group-scale ($\sim50$ kpc) environment containing one companion with tentative spectroscopic redshift and five companion candidates, and it is embedded in a known protocluster on Mpc scales. A potential environmental influence on its evolution could explain the outside-in quenching suggested by the positive gradient of size with wavelength. This study demonstrates that deep JWST/NIRSpec spectroscopy enables low-mass quiescent galaxies at Cosmic Noon to be characterized with a level of detail long reserved for massive systems, offering valuable new insights into how quenching operates in these underexplored low-mass systems. [Abridged]

Massive quenched galaxies at z>3 challenge models of early galaxy evolution, as their rapid formation and abrupt quenching require efficient feedback, often linked to active galactic nuclei (AGN). The quiescent galaxy GS10578 at z=3.1 is a key example of this population. Previous JWST/NIRSpec IFU data revealed an AGN outflow and uncovered a compact pair of AGN separated by ~5 kpc. In addition, VLT/MUSE spectroscopy has identified a third AGN candidate at a projected distance of ~30 kpc, associated with a luminous Lya emitter (LAE2) characterised by high-ionisation UV lines, although rest-frame optical diagnostics were not previously available. We aim to confirm the nature of LAE2 using rest-frame optical diagnostics enabled by new JWST data, and to characterise the physical and ionisation properties of both LAE2 and a distinct nearby Lya emitter (LAE1) that lacks any detectable continuum counterpart. We analyse new NIRSpec IFU observations targeting the optical nebular lines of LAE1 and LAE2, complemented with MUSE data, as part of the GA-NIFS project. We extract integrated and spatially resolved spectra, construct emission-line maps, and use standard diagnostic diagrams to determine ionisation sources and kinematics. LAE2 exhibits line ratios fully consistent with an embedded AGN. Its optical lines display a clumpy morphology and irregular kinematics on sub-kpc scales. Except for Lya, LAE1 remains undetected in all nebular lines and in JWST imaging. The similarity of the LAE1 and LAE2 Lya profiles in both velocity and flux suggests that LAE1 traces resonantly scattered emission rather than in-situ star formation. Our analysis reveals that the environment of GS10578 contains both multi-black-hole activity and gas structures on tens-of-kpc scales, offering new insights into how feedback and satellite interactions influence the late evolutionary stages of quenched massive galaxies.

High-quality metallocene single crystals with a low density of impurities and high homogeneity were prepared using the physical vapor transport method. These crystals were then characterized using various spectroscopic tools and X-ray diffraction. Laser-induced breakdown spectroscopy confirmed the presence of metal ions in each freshly grown sample despite all these crystals undergoing physical deformation with different lifetimes. X-ray diffraction analysis confirmed that all our metallocene single crystals retained a monoclinic structure at room temperature. The vibrational properties of our metallocene crystals were examined using Raman and Fourier-transform infrared spectroscopy. The inter- and intra-ring vibrational modes, along with additional modes associated with the crystalline form, were identified as inherent vibrational properties of our metallocene single crystals. Given the increasingly important role of metallocene in organic solar cells, organic light-emitting displays and molecular quantum systems, this research will enhance our understanding of the intrinsic physical properties of cleaner, more crystalline metallocene single crystals.

In this paper, we give a new approach to the Bochner-Riesz summability. As a result, we show that the Bochner-Riesz operator $\mathbf{S}^δ, 0<\Reδ<{1\over 2}$ is bounded on $\mathbf{L}^p(\mathbb{R}^n)$ for ${n-1\over 2n}\leq {1\over p}\leq{n+1\over 2n}$.

A recently developed upscaling technique, the multicontinuum homogenization method, has gained significant attention for its effectiveness in modeling complex multiscale systems. This method defines multiple continua based on distinct physical properties and solves a series of constrained cell problems to capture localized information for each continuum. However, solving all these cell problems on very fine grids at every macroscopic point is computationally expensive, which is a common limitation of most homogenization approaches for non-periodic problems. To address this challenge, we propose a hierarchical multicontinuum homogenization framework. The core idea is to define hierarchical macroscopic points and solve the constrained problems on grids of varying resolutions. We assume that the local solutions can be represented as a combination of a linear interpolation of local solutions from preceding levels and an additional correction term. This combination is substituted into the original constrained problems, and the correction term is resolved using finite element (FE) grids of varying sizes, depending on the level of the macropoint. By normalizing the computational cost of fully resolving the local problem to $\mathcal{O}(1)$, we establish that our approach incurs a cost of $\mathcal{O}(L η^{(1-L)d})$, highlighting substantial computational savings across hierarchical layers $L$, coarsening factor $η$, and spatial dimension $d$. Numerical experiments validate the effectiveness of the proposed method in media with slowly varying properties, underscoring its potential for efficient multiscale modeling.

Motivated by recent reports of ambient-pressure superconductivity in La$_3$Ni$_2$O$_7$ films grown on LaSrAlO$_4$, we investigate the superconducting instability in a one-unit cell thin film using {\it ab initio} and random-phase approximation techniques. Compared to the high-pressure bulk system, the ratio of inter-layer $d_{3z^2-r^2}$ hopping to intra-layer $d_{x^2-y^2}$ hopping is suppressed in the 1UC thin film, and the crystal-field splitting of the $e_g$ orbitals is increased. Our calculation indicates that spin-fluctuation-driven pairing correlations are weak for the stoichiometric case at ambient pressure, but increase significantly under hole doping. The leading pairing symmetry is also found to change by hole doping. Specifically, we obtain a leading $d_{x^2-y^2}$ pairing state at moderate hole doping, followed by a $d_{xy}$ state at higher doping. These states are driven by intra-band spin-fluctuation scattering {\it within} the $γ$ hole pocket centered around the M point, and arise primarily from states in the Ni layer {\it farther} from the substrate. These results strongly suggest that the thin-film superconducting samples are hole-doped and that pairing in this system predominantly arises in the layer, as opposed to the inter-layer pairing in the pressurized bulk system.

We explore the effects of massive neutrinos on the cosmic web using the FLAMINGO simulations. We classify the cosmic web into voids, sheets, filaments, and clusters, and find that massive neutrinos affect the environment by decreasing the volume occupied by clusters and voids. We find that increasing the neutrino mass shifts the volume-weighted density distribution towards higher densities and leads to a more narrow density distribution, which we interpret as neutrinos delaying structure formation. We construct the minimum spanning tree (MST) graph from the subhaloes, adopting a number density chosen to match that expected for DESI-like observations. We show that most MST edges lie in filaments, approximately 70% throughout different simulations, which we link to its sensitivity to neutrino mass. We also link the MST's edge length signal at different scales to different cosmic web environments, with clusters dominating the signal at small scales, voids at longer scales, and filaments at intermediate scales. The strong correlation between MST edges and cosmic web environments reinforces the MST's potential to be used as a classifier for large-scale structure in galaxy surveys. We compare the effects of baryonic physics and massive neutrinos and find that each produces distinct signatures in MST edge lengths. This analysis is performed in 3D space, using the true positions of subhaloes and not accounting for redshift space distortions. Nevertheless, these results emphasise the MST's capability to go beyond two-point statistics, motivating future applications to real observational data.

We present an analysis comparing nulling strategies for reducing the impact of baryon feedback on cosmic shear measurements. We consider three different approaches which aim to `null' the high-$k$ modes using transformations applied to the data vector: the Bernardeau-Nishimichi-Taruya (BNT) transform which operates on the lensing field, a new implementation of an LU factorisation of the discretized Limber integral (LUnul) which operates on the lensing two-point statistics, and finally a method which uses a correlated LSS tracers to suppress contributions from lower redshifts (cross-correlation). We compare these methods to un-nulled (or standard) cosmic shear at the data vector level and assess whether these methods are able to reduce the bias on cosmological constraints using a Fisher forecast. We find that the nulling techniques considered can have a large impact on reducing the bias on $S_8$ and Dark Energy parameters. The cross-correlation method is effective at reducing biases in $S_8$, but requires additional information from galaxy clustering. The LUnul method is the most aggressive of the methods and hence reduces biases most efficiently as $k_{\rm max}$ is increased, although this improvement in accuracy comes at the cost of precision. The BNT approach preserves more information than LUnul, and has a more rigorous theoretical grounding. We demonstrate that all three of these methods are effective at mitigating bias, and can be readily applied in forthcoming lensing analyses.

The stability of geodesic orbits around a regular hairy black hole, in the gravitational decoupling setup, is investigated by employing Lyapunov exponents, which quantify the divergence rate of nearby trajectories in dynamical systems. Both timelike and null geodesics are addressed, probing the effect of the hair parameter on orbital stability. Deviations from the Schwarzschild solution have a significant influence on orbit stability, potentially providing observational signatures. Quasinormal modes of regular hairy black holes are calculated, and their thermodynamic properties are discussed. Both the Rényi and the Bekenstein-Hawking entropies are reported, deepening our understanding of gravitational dynamics in the strong-field regime, contributing to ongoing approaches to modified gravity.

By inferring the gravitational wave background (GWB) from a population of supermassive black hole binaries (SMBHBs), pulsar timing arrays (PTAs) enable the study of massive black holes. In many ways, PTAs manifest the promise of a multimessenger approach to astronomy: they can constrain SMBHB population characteristics that are otherwise difficult to constrain using electromagnetic observations, such as hardening mechanisms at sub-parsec separations. In this work, we quantify this multimessenger promise using Bayesian inference of many realizations of simulated PTA data, while adopting a model for the SMBHBs that has been successfully applied to the 15-year data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). Our analyses of 200 realistic, simulated NANOGrav data sets show that there is a greater than 50\% chance of reducing the prior uncertainty in the SMBHB hardening rate by more than 50\%, and in the SMBHB evolutionary lifetime by 25--75\%. Additionally, there is an 88\% chance that PTA data can reduce the prior uncertainty in the characteristic mass variable of the galaxy stellar mass function (GSMF) by 25--50\%. For $M_{\text{BH}}$--$M_{\text{Bulge}}$ parameters (in a model without redshift evolution) and the overall normalization parameter of the GSMF, PTA data can provide only marginal information gain beyond the constraints from electromagnetic observations. Our work delineates the domains over which electromagnetic and gravitational-wave data constrain the demographics and dynamics of the supermassive black-hole binary population, offering a clearer picture of the impact of population multi-messenger astrophysics probes with PTAs.

Tradable Credit Schemes (TCS) promote the use of public and shared transport by capping private car usage while maintaining fair welfare outcomes by allowing credit trading. However, most existing studies assume unlimited public transit capacity or a fixed occupancy of shared modes, often neglecting waiting time and oversimplifying time-based costs by depending solely on in-vehicle travel time. These assumptions can overstate the system's performance with TCS regulation, especially when there are insufficient public or shared transport supplies. To address this, we develop a dynamic multimodal equilibrium model to capture operation constraints and induced waiting times under TCS regulation. The model integrates travelers' mode choices, credit trading, traffic dynamics, and waiting time, which depend on key operational features of service vehicles such as fleet size and capacity. Besides, most TCS studies assume fixed transport supply, overlooking supply-side responses triggered by demand shifts. Therefore, we further propose integrating adaptive supply management through the deployment of Demand-Responsive Autonomous Shuttles (DRAS) and developing a bi-level optimization framework that incorporates the equilibrium model to jointly optimize TCS design and operational strategies for the DRAS. We apply the framework to a section of the A10 highway near Paris, France, to examine demand-supply interactions and assess the potential benefits of jointly implementing TCS and DRAS. Numerical results demonstrate the importance of modeling operational features within multimodal equilibrium and incorporating flexible supply in TCS policies for mitigating overall generalized cost.

We propose a novel scheme for generating mechanical squeezed states based on the combined mechanism of a two-tone driving and a squeezed vacuum field. This innovative approach achieves a remarkable improvement in mechanical squeezing performance across the entire range of red/blue detuning ratios. Our study reveals that the squeezed vacuum field not only induces position squeezing of the mechanical oscillator but also facilitates momentum squeezing through phase matching. Moreover, the total squeezing degree exhibits nonlinear enhancement with the increasing of squeezing parameter $r$. The mechanical squeezed state exhibits a $2π$-periodic dependence in relation to the squeezing phase $θ$, offering experimental implementation with a high degree of operational flexibility. Notably, the scheme exhibits strong robustness against cavity dissipation and environmental thermal noise, substantially relaxing the strict parameter-matching requirements inherent in conventional approaches.

The ability to precisely control surface charge using charged polymers is fundamental to many nanotechnology applications, enabling the design and fabrication of materials with tailored properties and functionalities. Here, we study the effect of charge regulation (CR) on the interaction between two nanoparticles (NPs) mediated by an oppositely charged polyelectrolyte (PE) in an electrolyte solution. To this end, we employ a hybrid CR Monte Carlo / molecular dynamics simulation framework to systematically explore the effects of pH, salt concentration, and polymer chain length on NP surface charge behavior. For comparison, we also conduct molecular simulations under constant charge (CC) conditions. Our results reveal that CR enhances PE adsorption onto NP surfaces compared to the CC case, where polymer bridging dominates across a wide range of NP intersurface separations. This enhanced adsorption under CR leads to a weak net repulsion driven by osmotic forces. In contrast, the CC model yields a stronger net attraction due to the bridging force. Furthermore, we find that the CR effects are more pronounced at low salt concentration, whereas at high salt concentration, counterion screening dominates in both CR and CC cases, diminishing the CR effect. These findings highlight the importance of incorporating charge regulation in characterizing nanoparticle interactions within a complex biochemical environment, particularly in low salt concentrations.

We study geometric inequalities for the circumradius and diameter with respect to general gauges, partly also involving the inradius and the Minkowski asymmetry. There are a number of options for defining the diameter of a convex body that fall apart when we consider non-symmetric gauges. These definitions correspond to different symmetrizations of the gauge, i.e. means of the gauge $C$ and its origin reflection $-C$.

Ferrimagnets, composed of antiferromagnetically coupled magnetic sublattices whose net magnetisation can be tuned by temperature, offer a unique platform for probing the symmetry of the spin currents they generate and for identifying the sublattice contributions to these currents. Here, we investigate the spin current symmetries produced by GdFeCo ferrimagnet at a fixed concentration and across a broad temperature range, including the magnetisation compensation point. Using complementary techniques based on spin-torque ferromagnetic resonance spectroscopy, we separate the contributions of the spin Hall effect (SHE) and the spin anomalous Hall effect (SAHE). We show that the torques arising from both mechanisms retain their sign across the magnetisation compensation temperature, and that the SAHE-driven damping-like torque has the opposite sign to the SHE-driven term. We suggest that both effects originates from distinct electronic subsystems: the SHE emerging from Gd 5d electrons, and the SAHE from FeCo 3d electrons. Consequently, the SHE sign remains insensitive to the magnetisation state, whereas the SAHE sign does not invert at compensation, reproducing our observations. Together, these insights clarify the interplay between sublattices in ferrimagnetic spin transport and highlight the potential of ferrimagnetic spin currents to generate spin torques in adjacent layers or within the ferrimagnet itself.

Boron aluminum nitride (B$_x$Al$_{1-x}$N) is a promising material for next-generation electronic and optoelectronic devices due to its ultra-wide bandgap, high thermal stability, and compatibility with other III-nitride semiconductors. Despite its potential, the band alignments of B$_x$Al$_{1-x}$N remain largely unexplored, although this information is essential for device design. In this study, we compute the valence and conduction band alignments of nonpolar ($a$-plane) and polar ($c$-plane) B$_x$Al$_{1-x}$N, and compare them with those of AlN and GaN. Using density functional theory, many-body perturbation theory, $GW_0$ method, and a novel passivation scheme, we find that they have near-zero valence band alignments for low-$x$ B$_x$Al$_{1-x}$N/AlN, while higher compositions ($x > $0.333) exhibit type I or II band alignments. The band alignments also show a notable dependence on surface polarity and the tetrahedral distortion of the B$_x$Al$_{1-x}$N structures. Our computed offsets are in good agreement with available experimental data. Due to their low valence band alignments and higher conduction band alignments, the B$_x$Al$_{1-x}$N/AlN heterostructures could be well suited for high-electron-mobility transistors and ultraviolet light-emitting diodes. The band alignments of B$_x$Al$_{1-x}$N determined in this study provide essential design guidelines for integrating these ultra-wide bandgap alloys into advanced semiconductor technologies.

Access control is a security mechanism designed to ensure that only authorized users can access specific resources. Cross-domain access control involves access to resources across different organizations, institutions, or applications. Traditional access control, however, which handles authentication and authorization separately in centralized environments, faces challenges in identity dispersion, privacy leakage, and diversified permission requirements, failing to adapt to cross-domain scenarios. Thus, there is an urgent need for a new access control mechanism that empowers autonomous control over user identity and resources, addressing the demands for privacy-preserving authentication and flexible authorization in cross-domain scenarios. To address cross-domain access control challenges, we propose POLARIS, a unified and extensible architecture that enables policy-based, verifiable and privacy-preserving access control across different domains. POLARIS features a structured commitment mechanism for reliable, fine-grained, policy-based identity disclosure. It further introduces VPPL, a lightweight policy language that supports issuer-bound evaluation of selectively revealed attributes. A dedicated session-level security mechanism ensures binding between authentication and access, enhancing confidentiality and resilience to replay attacks. We implement a working prototype and conduct comprehensive experiments, demonstrating that POLARIS effectively provides scalable, privacy-preserving, and interoperable access control across heterogeneous domains. Our results highlight the practical viability of POLARIS for enabling secure and privacy-preserving access control in decentralized, cross-domain environments.

Artificial spin ice (ASI) systems exhibit fascinating phenomena, such as frustration and the formation of magnetic monopole states, and Dirac strings. However, exploring the wave phenomena in these systems is elusive due to the weak dipolar coupling that governs their interactions. In this study, we demonstrate coherent spin-wave propagation in an hybrid ASI system, which is based on a multilayered ferromagnetic thin film with perpendicular magnetic anisotropy and in-plane magnetized nanoelements embedded within it. We show that this system enables spin-wave transmission over a one-micrometer distance via exchange-mediated coupling between subsystems and evanescent spin-wave tunneling through the out-of-plane magnetized parts. This system overcomes the limitations of purely dipolar interactions in standard ASIs while preserving their fundamental properties. Thus, it provides a platform for studying spin-wave phenomena in frustrated ASI systems and paves the way for exploiting them in analog signal processing with spin waves.

Full spectrum fitting is the prevailing method for extracting stellar kinematic and population measurements from 1D galaxy spectra. 3D methods refer to analysis of Integral Field Spectroscopy (IFS) data where spatial and spectral dimensions are modelled simultaneously. While several 3D methods exist for modelling gas structures there has been less investigation into the more computationally demanding problem of 3D full spectrum fitting for stellar recoveries. This work introduces and compares two algorithms for this task: the Projected Nesterov Kaczmarz Reconstruction method (PNKR) and a version of the Bayes-LOSVD software which has been modified to account for spatial correlations. We aim to understand strengths and weaknesses of both algorithms and assess the impact of 3D methods for stellar inferences. We apply both recovery algorithms to a mock IFS data over a signal-to-noise ratio (SNR) range from 20-200 and evaluate the quality of the recoveries compared to the known ground truth. Accounting for spatial correlations in Bayes-LOSVD significantly improved the accuracy and precision of kinematic recoveries. 3D modelling with PNKR did not provide any significant improvement over 1D fits however, for SNR>40, PNKR did recover the most accurate kinematics overall. Additionally, by modelling the joint distribution over kinematics and populations, PNKR could successfully infer trends between these quantities e.g. inferring local metallicity-velocity trends, albeit with a significant bias on the absolute metallicity. Having demonstrated advantages of (i) 3D modelling with Bayes-LOSVD, and (ii) joint kinematic-population analyses with PNKR, we conclude that both methodological advances will prove useful for detecting and characterising stellar structures from IFS data.

Classical shadows provide a versatile framework for estimating many properties of quantum states from repeated, randomly chosen measurements without requiring full quantum state tomography. When prior information is available, such as knowledge of symmetries of states and operators, this knowledge can be exploited to significantly improve sample efficiency. In this work, we develop three classical shadow protocols for $\mathbb{Z}_2$ lattice gauge theory, where a dual formulation enables a rigorous analysis of resource requirements, including both circuit depth and sample complexity. Our approaches can offer exponential improvements in sample complexity over symmetry-agnostic methods, albeit at the cost of increased circuit complexity. While our analysis is restricted to $\mathbb{Z}_2$ lattice gauge theory, our approach offers a blueprint for similar protocols for more general lattice gauge theory models which are currently at the forefront of quantum simulation efforts.

Magnetar giant flares (MGFs) are rare, extremely bright bursts of gamma-rays from highly magnetized neutron stars. These events are challenging to identify because, at extragalactic distances, they can appear similar to other astrophysical phenomena. Only a handful have been confidently identified to date, limiting our understanding of their origin and physical properties. This study focuses on expanding the sample of known events and enabling a more detailed characterization of their observational features and intrinsic properties, while introducing significant improvements in the methods used to identify and analyze them. When applied to archival data from the Gamma-ray Burst Monitor (GBM) on the \Fermi Gamma-ray Space Telescope, this approach added four previously unidentified events the known sample, expanding the total to 13 MGFs. This demonstrates both the effectiveness of the method and the likelihood that additional MGFs remain hidden in existing gamma-ray burst catalogs. We utilize this expanded sample to gain a deeper understanding of the broader population of MGFs. We develop a statistical modeling framework that combines previously considered data with modern observations from Fermi/GBM. The model accounts for instrumental sensitivity and the expected diversity in event characteristics. We infer a volumetric rate of events above $1.2\times10^{44}\,\rm{erg}$ of $R_{MGF}=5.5^{+4.5}_{-2.7}\times10^5\rm{Gpc^{-3}yr^{-1}}$. The results show that individual magnetars must produce multiple flares throughout their lifetimes, reinforcing the idea that these are recurring phenomena rather than singular explosive events. Expanding the sample of known MGFs improves our understanding of magnetars and their role in other astrophysical phenomena, including possible links to fast radio bursts, gravitational waves, and the creation of heavy elements in extreme astrophysical environments.

Philosophers have spilled much ink over the discovery of ideas in the classical 'context of discovery'. However, there has been little engagement with the question of what constitutes a discovery of 'things in the world'. A much-overlooked answer to this question is provided by T.S. Kuhn. In this paper, I show that discoveries awarded with a Nobel Prize in Physics in the past 53 years accord with a basic premise of Kuhn's account and his distinction between two types of natural kind discoveries. I also draw normative conclusions for credit attribution in science.

In this paper, a novel bio-inspired optimization algorithm is proposed, called Bombardier Beetle Optimizer (BBO). This type of species is very intelligent, which has an ability to defense and escape from predators. The principles of the former one is inspired by the defense mechanism of Bombardier Beetle against the predators, which the Bombardier Beetle triggers a toxic chemical spray when it feels threatened. This reaction occurs in a specialized reaction chamber inside its abdomen and includes a well regulated enzymatic mechanism, which comprises hot water vapor, oxygen, and irritating substances like p-benzoquinones. In addition, the proposed BBO simulates also the escape mechanism of Bombardier Beetle from predator, which it has the ability to calculate its distance from predator and it can fly away. The BBO is tested with optimizing Congress on Evolutionary Computation (CEC 2017) test bed suites. Moreover, it is compared against well-known metaheuristic optimization algorithms includes Chernobyl Disaster Optimizer (CDO), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Bermuda Triangle Optimizer (BTO), Sperm Swarm Optimization (SSO) and Gravitational Search Algorithm (GSA). The outcomes of this paper prove the BBO's efficiency in which outperforms the other algorithms in terms of convergence rate and quality of results.

Multiferroics, which combine ferroelectric and magnetic order, offer a transformative platform for next-generation electronic devices. However, the intrinsic competition between the mechanisms driving ferroelectricity and magnetism in single-phase materials severely limits their performance, typically resulting in weak magnetoelectric coupling at room temperature. Here, we propose a solution to this long-standing challenge through the novel concept of fractional quantum multiferroics (FQMF), where strong magnetoelectric coupling is naturally realized by coupling fractional quantum ferroelectricity (FQFE) with altermagnetism (AM). Symmetry analysis shows that reversing the FQFE polarization necessarily inverts the AM spin splitting under parity-time ($\mathcal{PT}$) or time-reversal ($\mathcal{T}τ$) operations. A minimal tight-binding model reproduces this effect, demonstrating electrically driven spin control without rotating the Néel vector. First-principles calculations further identify a broad family of candidate materials in two and three dimensions including bulk MnTe, Cr$_2$S$_3$, Mn$_4$Bi$_3$NO$_{15}$ and two-dimensional AB$_2$ bilayers such as MnX$_2$ (X=Cl, Br, I), CoCl$_2$, CoBr$_2$, and FeI$_2$. Notably, MnTe exhibits a high Néel temperature ($\sim$300 K) and a large electrically switchable spin splitting ($\sim$0.8 eV), demonstrating room-temperature magnetoelectric performance that surpasses that of conventional multiferroics. To further showcase the technological potential, we propose an electric-field-controlled FQMF tunnel junction based on MnTe that achieves tunneling magnetoresistance exceeding 300\%. This work establishes FQMF as a distinct and promising route to achieving room-temperature strong magnetoelectric coupling, opening a new avenue for voltage-controlled spintronics.