Papers

The ionosphere and its behaviour critically affects ground-based radio instruments at low frequencies, and radio interferometry has been used as a probe of the ionosphere since the earliest days of radio astronomy. In this chapter, we aim to give an overview of the ionosphere and its salient properties in the mid-latitudes where the SKAO instruments are located. We provide a comprehensive review of its impact on the astrophysical radio signals which traverse it. We then focus on the ionosphere as a phase screen, and the many ways in which the ionospheric structure can be measured using a low-frequency interferometer such as SKA-Low. Our aim here is to provide the broadest possible spectrum of measurement approaches. We place particular emphasis on the wide range of innovative approaches that have been developed for SKA precursors and pathfinders over the last decade, however we also draw attention to other approaches, some untested, that appear in the literature. Next, we consider an innovative approach for deducing the detailed physical conditions in the ionosphere from SKA observables via iterative simulations with a sophisticated physical model from which the interferometric response can be forward-modelled. This approach has proven extremely successful for interpreting large scale observations in the complex polar region of the ionosphere, and we discuss how it can be applied to the SKA-Low. Finally, we provide a summary of the technical requirements which will ensure viability of the various techniques discussed.

We present a theoretical study of the non-linear evolution of cosmic voids – underdense regions that occupy a large fraction of the observable Universe. We model a void as an isolated homogeneous spheroidal (axisymmetric) ellipsoid embedded in a homogeneous $\Lambda$CDM universe. Starting from a small initial density contrast at redshift $z=500$, we numerically integrate the equations of motion for the ellipsoid semi-axes and follow their evolution to the present epoch. We examine the anisotropic expansion of the void and the corresponding change in its shape, characterised by the eccentricity $e$. We find that the void non-sphericity always decreases, but rather slowly: the eccentricity drops from $e\approx0.87$ at $z=500$ to $e\approx0.81$ at $z=0$. Thus the void becomes rounder but remains aspherical throughout the evolution. The evolution and final value of the void underdensity are virtually independent of the void's eccentricity. The nonlinearity of void evolution becomes apparent very early: a ten percent deviation from the linear regime occurs already at $z\simeq8$, when $\varepsilon = \Delta\rho/\rho\sim10\%$. Notably, our calculations show that the majority of voids are not strongly underdense and contain a significant amount of matter, $\mu>0.5$.

We perform a Bayesian analysis of a relativistic mean-field approach, which is an implementation of the chiral confining model with both chiral symmetry breaking and confinement effects, and which was recently proven to reproduce well the ground state properties of finite nuclei. We additionally explore the impact of couplings between $\rho$ and $\omega$ mesons as well as a non-linear $\omega$ coupling. Our models are simultaneously constrained by nuclear matter properties near saturation density, multi-messenger neutron star astrophysical observations, and/or lattice QCD predictions of the nucleon mass. It exhibits tension in simultaneously reproducing the $\sim 2M_{\odot}$ massive NS and the tidal deformability inferred from GW170817. We show that an additional $\omega\rho$ coupling, favored by Bayes factor analysis, substantially alleviates this tension, while adding a non-linear $\omega$ self-interaction is not necessary for the RMF-CC model. Owing to the strong constraints on the scalar sector imposed by chiral dynamics and the softening of the equation of state at high densities induced by our treatment of confinement, the RMF-CC approach favors stiff equations of state. Since we do not consider phase transition in the core of neutron stars, this stiffening is obtained with large values of the incompressibility modulus of about $\sim300$ MeV. We finally compare the well-known RMF model with RMF-CC models with the same constraints, and we obtain a preference for the RMF model in the absence of a phase transition in the core of neutron stars.

We extend Nielsen's geometric approach for quantum complexity from closed to open quantum systems, whose dynamics is governed by Lindbladian evolution. In this framework, complexity is defined through an optimal-control problem on the space of mixed states, with a cost assigned to both unitary and non-unitary generators. We show that the resulting geometric structure differs fundamentally from the Riemannian geometry that emerges in the case of unitary evolution. In the open-system setting, the natural geometry is typically sub-Finslerian. Dissipation makes the geodesics non-reversible, while the admissible tangent directions are restricted by the physically allowed controls. We analyze several physically motivated examples, including a single qubit subject to depolarizing and amplitude-damping channels, as well as the damped harmonic oscillator. We show that, similarly to the unitary case, varying the penalty factors in the cost functional modifies the geometric properties through changes in the flag curvature, the Finslerian analog of sectional curvature. Our results provide a geometric framework for quantifying the abstract notion of complexity in dissipative quantum systems, with potential connections to experimentally realizable setups.

The solar corona exhibits a pronounced temperature inversion, with plasma temperatures increasing by nearly two orders of magnitude from the chromosphere to the corona. We investigate how spatially sparse and temporally intermittent stochastic heating at the base of the transition region shapes the temperature and density structure of coronal loops within a kinetic framework. Stochastic thermal boundary conditions and surface coarse graining are introduced. Analytical solutions are derived in the collisionless limit for heating-event time scales shorter or longer than the particle crossing time, and Coulomb collisions are incorporated through a reduced kinetic model describing the thermalization of suprathermal particles. In the short-time-scale regime, spatial filling factor and temporal intermittency combine into a single effective parameter controlling the suprathermal population, producing a transition region and a hot corona both within individual loops and after coarse graining. Collisions preserve this thermal structure while reducing the coronal density through progressive thermalization. In the long-time-scale regime, individual loops are nearly isothermal and the temperature inversion emerges only after coarse graining, depending solely on the spatial filling factor. Here, Coulomb collisions and optically thin radiative losses have only minor effects, while density and temperature profiles remain broadly consistent with coronal observations. These results show that sparse, intermittent heating naturally generates suprathermal particle distributions and reproduces the observed thermal structure of the solar corona within a kinetic framework, highlighting the different sensitivity of the two regimes to collisional effects.

We introduce a family of quantum circuits that possess standard indicators of classical simulation hardness including high entanglement entropy, magic, and non-Gaussianity, yet admit efficient classical simulation via matrix product states (MPS). Our construction uses logical circuits of high-rate Calderbank-Shor-Steane (CSS) codes with enhanced symmetries. Using code automorphisms and transversal diagonal gates from higher levels of the Clifford hierarchy, we realize nonlocal logical Clifford and non-Clifford gates, showing how error-correcting codes can compile complex logical circuits into simple physical operations. Simulation efficiency rests on two properties: (i) diagonal transversal gates do not increase bond dimension, and (ii) permutations are tracked classically via on-the-fly relabeling, avoiding costly SWAP networks. Unlike Clifford or matchgate simulation, our method accepts a broad class of initial states, including dense entangled, magic, and non-Gaussian inputs, provided the encoded state retains an efficient MPS representation. We also release an exact phase-polynomial backend for monomial subfamilies, whose cost is set by higher-degree phase terms rather than entanglement growth. We demonstrate the method on an infinite polar CSS code family, showing bond dimension stays bounded by the encoding cost regardless of circuit depth. These results show that for some circuit families, standard resource measures are individually insufficient to indicate simulation hardness. As a near-term application, we use the compiled MPS as a classical reference for direct fidelity estimation of a quantum device running nontrivial logical circuits. Pauli sampling on the encoded reference, with a Clifford pushback through the known encoder, provides the ideal expectation values, so the logical output fidelity can be estimated from local Pauli readout alone, without costly state tomography.

Inspired by biological systems, extensive research has explored how fluid-structure interactions in compliant channels and confined geometries control fluid transport. While local nonlinearities can be induced by individual components, arranging these elements into larger architectures gives rise to increasingly complex, collective responses. Predicting these collective behaviors, however, remains largely restricted to steady-state characterization, as the dynamic coupling between time-varying flows and multiple interacting structures is difficult to model. In this paper, we investigate numerically the collective interaction of multiple asymmetric leaflets within a channel at low-Reynolds number. By utilizing symmetrically oscillating plates rather than a pressure-driven flow to isolate the system from background asymmetries, we characterize how these interacting structures generate a net fluid transport. We develop an analytical framework to evaluate transport in the steady limit, which we subsequently extend to account for time-dependent channel oscillations, providing a complete dynamic description of the coupled fluid-structure system. Our results demonstrate that high leaflet densities maximize collective interactions and net transport. Furthermore, we define an elastoviscous number comparing viscous hydrodynamic forces to the restorative elastic forces of the leaflets, and uncover an optimal value that maximizes the net flow. This framework establishes a foundation for analyzing how collective slender structures interact dynamically within viscous environments, laying the groundwork for future studies on flow control in biological fluid transport and microfluidic design.

Optical multilayer coatings are used in imaging optics, lasers, telecommunications, solar cells, and radiative cooling, where the spectral response required by each application is achieved by a well-designed layer structure. However, existing design methods have limitations. Local methods refine a starting design efficiently but depend on its quality, and global searches require up to millions of transfer-matrix evaluations per target. Existing deep-learning inverse-design models are fast, but they are trained for a fixed set of materials and a fixed wavelength band, and they either optimize the thicknesses for a fixed material sequence or choose them from a discrete grid. In this paper, we present IrisFlow, a generative model that addresses these limitations by taking each candidate material as its optical constants and the target spectrum together with its wavelengths as input. It generates the material and the continuous thickness of every layer jointly, by coupled discrete and continuous flow matching in a single network. We demonstrate its performance through design with materials outside the training library and on bands beyond the training range, and through comparisons with classical optimizers and an existing deep-learning model. We also demonstrate its usability in a practical design workflow by designing four colored solar-reflective coatings with the calibrated optical constants of an existing deposition system. Combined with a local refinement of its ten best designs, it reduces the number of transfer-matrix evaluations about 500-fold relative to needle optimization at comparable accuracy. The code, trained model, and training and test data are publicly available.

Solar filament eruptions are central to coronal mass ejections and space weather, yet their triggering mechanisms remain a fundamental open question. In particular, the early-stage that drives a magnetic flux rope toward instability and its observable signatures are poorly understood. Here, combining multi-instrument observations, we report successive coronal jets impacting a filament, causing its gradual rise and oscillations with growing amplitude and period. When the filament reaches the height where the decay index exceeds the torus instability threshold, the rapid filament eruption commences. This filament eruption is reproduced by magnetohydrodynamic simulations, in which successive thermal jets disturb a stable filament in a magnetic flux rope and excite oscillations together with the eruption of the filament. As the filament rises to erupt, the restoring forces for the oscillation progressively weaken, which naturally leads to an increase of the oscillation amplitude and period. Our results demonstrate the growing oscillations as one of the observable precursors for filament eruptions, enhancing our ability to predict solar eruptions.

A novel parallel approach is proposed for QEC decoding based on Belief Propagation with Ordered Statistics Decoding. The main idea is to pre-process the error vectors obtained from Belief Propagation by applying Singular Value Decomposition locally to sub-regions of the lattice. The proposed approach is applied to distributed quantum computers and evaluated in terms of complexity, accuracy, and scalability.

We revisit one-zero and two-zero textures of the neutrino mass matrix under current experimental and cosmological constraints. We identify the phenomenologically viable texture structures using the latest results on neutrino oscillation parameters, the cosmological bound on the sum of neutrino masses, the kinematic bound on the effective electron-neutrino mass, and limits from neutrinoless double-beta decay. For two-zero textures, several structures are still allowed if only the CMB bound on the neutrino mass sum is imposed. Among them, the $B$-series textures show a characteristic prediction for the Dirac CP phase, with $\delta_{\rm CP}$ lying around $\pi/2$ and $3\pi/2$, and are within the reach of future neutrinoless double-beta decay searches. When the stronger CMB+BAO constraint is included, however, only the $A$-series textures remain viable. Therefore, we also analyze one-zero textures by using machine learning techniques, particularly flow matching. It turns out that some of the texture structures are already excluded by current data, while the allowed ones give distinct predictions for $\sum_i m_i$, $m_{\nu_e}^{\rm eff}$, $\langle m_{ee}\rangle$, and $\delta_{\rm CP}$. We further discuss how the one-zero texture structures can arise from non-invertible selection rules.

We present an investigation of multiple stellar populations along the asymptotic giant branch (AGB) in 22 globular clusters (GCs), exploiting APOGEE spectroscopy combined with AGB selection based on Gaia color-magnitude diagrams. Using light-element abundances ([C/Fe], [N/Fe], [Mg/Fe], and [Al/Fe]), we disentangle first- (1P) and second- (2P) populations along the AGB. We derive their fractions in the AGB for the largest sample of GCs to date, finding that the 1P fraction decreases with cluster mass, as in other evolutionary phases. By comparing AGB and red giant branch (RGB), we define a quantitative criterion to identify clusters affected by the AGB-manque phenomenon. We find that in nine GCs the most chemically extreme 2P stars are underrepresented along the AGB, indicating that they fail to ascend this phase. Our classification is in agreement with previous studies and provides the first spectroscopic characterization of AGB multiple populations in eight GCs. We derive, for the first time, the radial distribution of AGB 2P stars in four clusters. While NGC5024 and omegaCentauri show trends consistent with the RGB, NGC2808 and NGC7078 may exhibit an unexpected increase of the AGB 2P fraction at large radii, opposite to the RGB stars. We present the first detailed spectroscopic characterization of anomalous AGB populations in NGC6656 and omegaCentauri, i.e. the populations enhanced in heavy elements compared to the bulk of 1P and 2P. In both clusters, anomalous stars show a more pronounced AGB-manque signature than 2P stars, with the fraction of the most Mg-poor and Al-rich AGB dropping compared to the RGB, possibly due to enhanced He and/or increased RGB mass loss. We report the first detection of iron inhomogeneities among 1P AGB stars in NGC5272, with a spread consistent with the RGB one. This extends the presence of iron variations to the most evolved stellar phase studied so far.

The search for novel silver(II) fluorides is driven by their potential as electronic and magnetic analogues to high temperature cuprate(II) superconductor precursors. Here, we explore the previously uncharted Be Ag(II) F chemical space using global structure prediction algorithms combined with first principles calculations. Focusing on the AgBeF4 stoichiometry, we identify the five lowest enthalpy polymorphs crystallizing in the C2, P minus 1, and P 21/c space groups. All polymorphs show an antiferromagnetic ground state, with AgBeF4_4 and AgBeF4_5 exhibiting unprecedented strong superexchange interactions of J equal circa to minus 460meV and J equal circa to minus 359meV respectively. Those high J values are due to the presence of either [Ag2F7] for AgBeF4_4, or related infinite [AgF2/2+2/1]2 minus chains for AgBeF4_5. Although the phases are found to be metastable with respect to binary difluorides, the thermodynamic analysis suggests that they could be targeted via synthetic routes employing fluorine radicals, with reaction enthalpies reaching minus 370 kJ/mol.

Dissipatively stabilized cat qubits provide a promising route toward fault-tolerant quantum computation, exhibiting exponential suppression of bit-flip errors with increasing phase-space separation of the logical states, while incurring only a linear increase in phase-flip errors. Existing implementations rely on engineered two-photon dissipation via nonlinear coupling to a lossy environment, an approach largely confined to superconducting platforms and limited by spurious decay channels and finite dissipation rates. Here, we propose a fundamentally different stabilization paradigm based on repeated interactions with an auxiliary two-level system mediated by a quadratic Hamiltonian, enabling dissipative stabilization without reservoir engineering. Our approach overcomes key limitations of existing schemes and is compatible with a wider class of experimental platforms. Furthermore, it preserves the noise bias and extends to squeezed cat qubits, rendering single-photon loss errors partially correctable.

The development of organic ferroelectric materials through scalable and simplified fabrication routes remains a major challenge for next-generation energy-harvesting technologies. Here, polycrystalline croconic acid (CA) thin films are fabricated by vacuum sublimation onto Ar plasma-treated flexible substrates and stabilized by in situ encapsulation with an adamantane-based remote plasma polymer. This solvent-free strategy effectively suppresses surface degradation under ambient conditions, providing long-term stability. Piezoresponse force microscopy confirms robust ferroelectricity with an oblique polarization orientation, well-defined domains, and low nanoscale coercive fields. The films were integrated into multilayer piezoelectric and pyroelectric devices. The piezoelectric performance strongly depends on film thickness, while embedding the CA layer between dielectric polymeric films significantly improves the macroscopic response, reaching power densities of up to 37 microW m-2 for ca. 2 micrometer CA films. Despite the common assumption that high crystallinity is required to sustain ferro-, piezo-, and pyroelectricity, these polycrystalline CA films exhibit remarkable RT pyroelectricity, a property not previously demonstrated in CA-based devices. A pyroelectric coefficient of ca. 10 microC m-2 K-1 highlights a functional response comparable to that of well-established organic and inorganic pyroelectric materials, demonstrating the potential of CA thin films for thermal energy harvesting. Beyond their functional performance, the proposed low-T fabrication route combines deposition and encapsulation in a single in situ process, simplifying device fabrication. Its compatibility with scalable vacuum technologies, flexible substrates, and further process optimization makes this approach highly promising for developing low-cost, lead-free, multisource energy-harvesting systems.

Integrated photonic neural networks require optical operators that are simultaneously compact, matrix-general and compatible with task-level reconfigurability. Here we introduce a meta processing unit (MPU), an inverse-designed near-field photonic device that implements local complex matrix transformations within a shallow-etched silicon region. Each 2x2 operator occupies 9.6 umx4.8 um and is designed as a reusable passive matrix primitive that can be combined with reconfigurable MZI neurons. We demonstrate a 3-bit quantized MZI-equivalent unitary device library with an effective reconstruction precision of 3.32 bits. Beyond unitary operators, we validate arbitrary complex 2x2 matrix fitting and a cascaded 4x4 matrix operation with 92.7% fidelity. We further integrate the MPU with active photonic components and hardware-in-the-loop training, achieving test accuracies of 83.5% and 80.9% on dual-task vowel recognition. In large-scale EMNIST simulations, a fine-grained neuron-level MPU replacement strategy reaches 87.64% average accuracy at 90% shared-MPU replacement, outperforming a layer-level baseline by 7.26 percentage points. These results establish inverse-designed MPUs as compact passive matrix operators for heterogeneous, hardware-adaptive photonic neural networks.

Magnetic van der Waals semiconductors such as CrSBr host an intricate exciton landscape. Quasiparticle self-consistent GW theory with electron-hole ladder vertex corrections (QSGWc) has established the gap and the character of the bright XA (1.34 eV) and XB (1.8 eV) excitons. Why these bright excitons coexist, within a few tens of meV, with companions orders of magnitude darker has remained unexplained. Here we show that brightness is fixed by a symmetry of the structure: a mirror-glide exchanges the two Cr atoms of each layer, every exciton has a definite parity under it, and bright and dark partners are its even and odd members. The even sector carries the b-axis dipole; the odd sector is suppressed by about three orders of magnitude. The dark partners of XA and XB occupy the same region of k-space as the bright states, and dark states such as the one at 1.50 eV are dipole-forbidden by inversion symmetry. Frenkel and Wannier-Mott labels describe what an exciton is made of, but brightness is decided by symmetry and by the coherent addition of transition dipoles. This bare structure is the reference for magnon, phonon and photon couplings.

Obtaining definitive evidence of exciton superfluidity in electron-hole bilayers in zero magnetic field remains a major longstanding challenge since the condensate is electrically neutral, making its phase coherence difficult to detect directly. We show that the Anderson-Bogoliubov sound velocity provides a dynamical signature of exciton superfluidity. Across the BCS-BEC crossover, the velocity is known to discontinuously drop to zero at the Berezinskii-Kosterlitz-Thouless (BKT) transition. The magnitude of the drop has a strong density dependence. We compute this behavior, with the inclusion of finite-temperature screening, and determine the BKT transition using a renormalization-group approach. We further identify a temperature window which is experimentally accessible, where vortex-antivortex excitations strongly renormalize both the sound velocity and the transition temperature.

Foundation machine-learning interatomic potentials (MLIPs) are rapidly replacing density-functional theory (DFT) for modeling structure and nuclear dynamics, making their fidelity in strongly correlated systems an urgent question. We test three foundation potentials on the low-temperature order of three correlated, isostructural ABO3 perovskite oxides: LaMnO3 (d4), LaCoO3 (d6), and NdNiO3 (d7). We run molecular dynamics for 1 ns on 80- and 160-atom supercells from 50 to 300 K with no system-specific training. These oxides expose three distinct classes of low-temperature order that define a hierarchy of difficulty for the potentials. The scalar class, represented by NdNiO3, has a simple geometric fingerprint and is captured. The vector class, represented by LaMnO3, requires identifying which Cartesian axis carries the long bond at each site, and is captured in magnitude but not in symmetry. The on-site class, represented by the low-spin to high-spin crossover in LaCoO3, is a purely local multiplet population shift with no spatial order parameter and remains inaccessible to present-day MLIPs.

Grokking, the delayed transition from memorization to generalization, is a fundamental phenomenon in gradient-based learning, yet its dynamics within variational quantum machine learning (QML) remain largely unexamined. In this work, we report the empirical observation of both the grokking transition and epoch-wise double descent in a two-qubit quantum neural network (QNN) under a complete parameterization of the SU(4) manifold. We demonstrate that overparameterization via increased circuit depth improves the probability of successful generalization. Notably, these architectures frequently exhibit an epoch-wise double descent in test error, degrading at a critical epoch before recovering into a generalizing state. Crucially, we identify a generalization decay in late-stage training, where the test error increases significantly despite a stagnant training loss. Bridging this behavior with algorithmic stability theory, our analysis reveals that this decay correlates with an unconstrained increase of the weight-norm, drifting away from sparse, phase-aligned harmonic solutions toward overfitted solutions in the Hilbert space. We analyze the underlying temporal dynamics of this transition, demonstrating how the onset of generalization is linked to optimization hyperparameters such as learning rate and weight decay. Finally, to mitigate late-stage decay, we introduce a weak explicit weight-norm regularization into the loss function. We demonstrate that this structural anchor stabilizes the post-grokking phase and permanently preserves generalization gains, providing a robust framework for training overparameterized quantum circuits.

Quantum computing research increasingly depends on complex software stacks, yet the reproducibility of published results does not receive the priority and longevity mandated by recommendations of large international scientific bodies and best practices in software-centric systems research. In this paper, we present a combined manual and automated large-scale analysis of the reproducibility landscape in quantum computing research, quantify shortcomings, and derive actionable steps forward. We manually evaluate a curated sample of 127 papers using a five-question framework that covers code availability, environment specification, documentation, hardware description, and executability. To place these findings in a broader context, we conduct an automated large-scale screening of nearly 5000 quantum computing papers for the same reproducibility indicators. Our manual analysis reveals that only 24.4% of the sampled papers provide code artefacts, and among those, 64.5% fail to execute successfully in a clean environment. This assessment is corroborated by a large-scale automated analysis that yields a consistent code availability rate of 26.8%. Further, it shows that approximately one-third of the papers with accessible code lack machine-readable environment specifications. The results in this paper indicate that reproducibility is not yet consistently achieved in quantum computing research. In response, we outline a set of practical recommendations that address the observed failure modes and illustrate how reproducibility can be improved in practice.

We show that a toroidal superfluid interrupted by $n$ tunneling barriers realizes a compact Josephson gyroscope with an $n$-enhanced response to rotation. In the small-amplitude regime, we derive analytically the normal mode spectrum of the coupled population-phase oscillations. In the absence of rotation, pairs of modes are degenerate: a finite angular velocity $\Omega$ lifts this degeneracy through a Doppler shift, producing a frequency splitting that grows linearly with both $\Omega$ and $n$. Full numerical simulations confirm this prediction and reveal long-lived two-frequency beatings, in sharp contrast with the monochromatic Josephson oscillations of the nonrotating system. These beatings provide a direct rotation signal with estimation uncertainty scaling as $\Delta\Omega \sim n^{-3/2}$, while remaining robust against imperfections and dynamical excitations. These results identify multi-junction toroidal superfluids as scalable, micrometer-size rotation sensors compatible with current experimental platforms.

A covariant reconstruction framework for Kantowski–Sachs (KS) geometries sourced by Chaplygin-type and polytropic fluids in teleparallel $F(T)$ gravity is developed using the coframe–spin-connection formalism and the teleparallel invariant approach. The matter sector is modelled by nonlinear equations of state, including the generalized Chaplygin gas $p=-A/\rho^{\alpha}$ and a polytropic law $p=K\rho^{\Gamma}$. The corresponding conservation laws determine the dependence of the fluid density on the anisotropic KS volume $V=A_2A_3^2$. These source scalings are then inserted into the symmetric part of the covariant teleparallel field equations and used to reconstruct the functional form of $F(T)$ directly from the KS dynamics. Power-law and exponential ansätze generate distinct invariant reconstruction branches. In the power-law sector, the Chaplygin fluid produces mixed constant-plus-power source terms, while the polytropic sector generates density powers controlled by the polytropic index. In the exponential sector, the natural reconstruction variable is the shifted invariant $X=T_0-T$, leading to shifted teleparallel de Sitter branches. The reconstructed models are interpreted as local anisotropic cosmological sectors and, for contracting angular KS scale factors, as local Kantowski–Sachs black-hole-interior reconstruction branches. The analysis is local and branch-dependent; leading-order viability is assessed through \(F_T>0\) and \(F_{TT}>0\), while a complete perturbative stability analysis is left for future work. The reconstruction is entirely driven by nonlinear matter conservation laws, thereby reversing the standard reconstruction strategy in which the gravitational Lagrangian is prescribed a priori.

Searches for Milky Way analogues traditionally rely on a limited set of present-day global properties. However, galaxies with similar morphology, stellar mass, star-formation rate, luminosity, and bulge-to-total ratio may have experienced substantially different assembly, secular, nuclear, and environmental histories. We introduce Milky Way Near Twins (MWNeTs) as galaxies resembling the Milky Way (MW) in their present-day properties and exhibiting observational signatures consistent with broadly similar evolutionary pathways. We aim to extend parameter-based searches towards evolutionary similarity. We propose seven stages: local environment, isolation criterion, and cosmic-web context; morphological and structural constraints; a MW-compatible nuclear state; global spectrophotometric and dynamical constraints; panchromatic spectral-energy-distribution similarity; rotation-curve similarity; and evolutionary fingerprints and fossil tracers. Each stage adds physically motivated constraints, progressively refining the candidate population and strengthening its assessment. For the first time, we formulate MWNeTs as a physically motivated class and establish a hierarchy explicitly distinguishing present-day compatibility from evidence for evolutionary similarity. A companion paper presents the observational application to NGC~3521, NGC~2903, UGC~11487, and CGCG~047-026. The framework is inherently iterative: the MW provides the reference, while near twins offer external laboratories for investigating aspects of Galactic formation and evolution inaccessible from our internal viewpoint. It connects Galactic astronomy, extragalactic astronomy, and cosmology through a comparative approach to testing broadly similar evolutionary pathways.

We study linear gravito-electromagnetic perturbations of a slowly rotating 4-derivative corrected Kerr-Newman (KN) black hole (BH), using a perturbative approach beyond the KN geometry up to first order in angular momentum, first order in the higher-derivative parameters ci, i = 1,2...8, and 14th order in the BH electric charge. We derive the corrected coupled radial master equations for both axial and polar perturbation sectors. We extend the asymptotic iteration method (AIM) to apply to coupled second-order ordinary differential equations (ODEs) and employ it to compute the quasinormal frequencies (QNFs) of the system.Our results show pronounced isospectrality breakings between the two parity sectors, induced by c6,c7 and c8,particularly for high charge BH.This indicate the equations for the two parity sectors lose the transformation symmetry that relates them in the KN case.The very tiny frequency shifts induced by c4 support the interpretation that this parameter represents a redundant degree of freedom in the effective field theory.Finally, we parameterize the QNFs via a analytical fitting procedure for broader applicability.

We consider the zero-temperature stochastic Ising process describing $\pm 1$ spin-flip dynamics on an infinite one-dimensional quasi-transitive graph $G=(V,E)$ with finite interaction range $K$. We prove that the zero-temperature limit of the Glauber dynamics for this Ising model exhibits a Type $\mathcal{I}$ behavior (infinite fluctuations of all vertices) if and only if the graph possesses the so-called shrink property. For graphs lacking this property, we introduce an algorithmic framework based on an auxiliary spatial automaton to distinguish, in finite time, between Type $\mathcal{F}$ behavior (almost sure local fixation) and Type $\mathcal{M}$ behavior (a mixed regime characterized by the presence of blinkers). We prove that the classification among these three regimes is algorithmically decidable. Furthermore, we provide a constructive example of a graph supporting blinkers of arbitrarily large size.

The electric and magnetic carrollian limits of $N=1$ supergravity in $D=4$ spacetime dimensions are explicitly derived. The approach is general and applies also to extended supergravity models

Bismuth vanadate (BiVO$_4$) is a prototypical oxide photocatalyst that occurs in both tetragonal and monoclinic scheelite phases with markedly different photocatalytic and photoelectrochemical activities. Accurately identifying the monoclinic phase as the ground state and explaining the origin of its symmetry-breaking distortion are unusually challenging from a theoretical perspective, with various levels of theory and associated physical interpretations for this behaviour reported in the literature. Here, we resolve these discrepancies by systematically assessing the role of exact exchange with and without spin-orbit coupling, demonstrating that an accurate treatment of electronic localization is essential to stabilize the monoclinic scheelite structure. Using this framework, we compute the electronic band structure through dense sampling of the Brillouin zone and show that the band edges in monoclinic and tetragonal BiVO$_4$ lie far from conventional high-symmetry paths, leading to substantial differences in band gaps and carrier effective masses. Choosing the exchange-correlation functional that best reproduces the crystal structure leads to excellent predictions of the band gap once excitonic and thermal effects are taken into account. In addition, we show that the monoclinic distortion is driven by charge transfer between non-equivalent oxygen sites, which breaks the lattice symmetry and is suppressed by self-interaction errors when using semi-local DFT. These results establish a direct connection between the exchange-correlation functional, electronic localization, chemical bonding, and structural stability in BiVO$_4$, providing a foundation for robust ab initio descriptions of phase stability and optoelectronic properties in such complex oxides.

In multiscale chaotic systems, a central question for closure is how much of an unresolved fine-scale target can be inferred from a simultaneous coarse observation. For a specified observation-target pair, we quantify instantaneous recoverability under the invariant snapshot measure as the fraction of target variance explained by conditioning on the retained coarse variables. Evaluating this quantity across scales produces a scale-resolved recoverability map. Applied to the Lorenz-96 system across a range of forcings, the maps reveal a strongly nonuniform landscape: lower-wavenumber targets have little variance explained by the retained lower modes, while a finite band of higher modes exhibits partial recoverability once the retained scales reach the energetically active intermediate range. Recoverability onset is organized around a reference cutoff at which two retained modes can directly couple to the target through the quadratic nonlinearity, although its precise location depends on attractor statistics. Across the tested forcings, this qualitative onset structure persists while recoverability decreases, leaving a larger fraction of target variance unexplained in more strongly driven regimes. This definition identifies the maximal explained-variance fraction attainable by instantaneous deterministic models under squared loss; the estimated maps provide a scale-dependent diagnostic for closure modeling.

In this paper, we consider a broad class of continuum two-scale Hamiltonians \begin{align*} H_\varepsilon:=T(-i\nabla_x+\mathbf A(x,\varepsilon x))+V(x,\varepsilon x),\qquad x\in \mathbb{R}^d \end{align*} where $T$ represents either a Dirac operator or a Schrödinger operator, and $x\mapsto \mathbf A(x,X)$ and $x\mapsto V(x,X)$ are $\mathbb L$-periodic with respect to some lattice $\mathbb L\subset\mathbb{R}^d$. No periodicity assumption is imposed on the second variable $X$. Let \begin{align*} \mathbb{R}^d\times \mathbb{R}^d\ni (k,X) \mapsto h(k,X):=T(-i\nabla_x+k+\mathbf A(x,X))+V(x,X) \end{align*} be a family of operators acting on $L^2(\mathbb{R}^d/\mathbb{L})$ with periodic boundary conditions. We assume only local spectral information near one point $(k_0,X_0)$: an isolated $J$-dimensional Bloch bands at energy $e_0$, possibly with internal crossings, and a Hermitian matrix-valued homogeneous function of degree $m\in\{1,2\}$. From these data we derive an effective Hamiltonian $\mathfrak{h}$. Then every sufficiently localized eigenpair $(\vec v,\mu)$ of $\mathfrak{h}$ gives an approximate eigenfunction $\Theta_\varepsilon$ such that for $\varepsilon$ small enough, \[ \|\Theta_\varepsilon\|_{L^2(\mathbb{R}^d)}=|\Omega|^{-1/2}+O(\varepsilon^{1/2}),\qquad \|(H_\varepsilon-e_0-\varepsilon^{m/2}\mu)\Theta_\varepsilon\|_{L^2(\mathbb{R}^d)} =O(\varepsilon^{m/2+1/4}). \]