We present validated and forward-modelled galaxy luminosity functions and photometric predictions for the Vera C. Rubin Observatory Legacy Survey of Space and Time using the ASTRID cosmological hydrodynamical simulation. Galaxy magnitudes are computed by combining stellar population synthesis modeling with a physically motivated dust attenuation prescription in which the optical depth scales with metal surface density. The dust model is calibrated at z = 0 using SDSS luminosity functions and tested at intermediate redshifts (z = 0.5, 1.0, and 1.5) in rest-frame B, V , R, and I bands. We find that the attenuated luminosity functions reproduce observed galaxy statistics across multiple wavelengths and redshifts. Using this calibrated framework, we construct LSST-ready mock photometric catalogs over 0 <= z <= 2 in steps of Delta z = 0.1, containing ~378 million galaxies. We provide predicted apparent-magnitude luminosity functions in the LSST ugrizy bands, derive best-fit Schechter parameters as a compact analytic representation, and compute differential and cumulative galaxy number counts as a function of survey depth from Year 1 to Year 10.

Low-surface-brightness galaxies (LSBGs) are vital for understanding galaxy formation, but their diffuse nature makes them challenging to detect. Upcoming large-scale surveys are expected to uncover large numbers of LSBGs, requiring robust automated methods to identify them across heterogeneous datasets. As a precursor to the Legacy Survey of Space and Time (LSST) and Euclid, we explore domain adaptation techniques for cross-survey LSBG identification. Using models trained on the Dark Energy Survey (DES), we search for LSBGs in the Kilo-Degree Survey Data Release 5 (KiDS DR5). We used an ensemble consisting of one convolutional neural network (CNN) and two transformer models trained on DES cutouts and applied to KiDS DR5 imaging data. Structural parameters were estimated with galfitm, and photometric redshifts and stellar population properties were estimated through spectral energy distribution fitting with CIGALE. We identify 20,180 LSBGs and 434 ultra-diffuse galaxies (UDGs) in KiDS DR5. Their structural parameters are similar to known LSBGs from DES and the Hyper Suprime-Cam SSP Survey (HSC-SSP). The KiDS-LSBGs follow a continuous size-luminosity relation connecting classical dwarf galaxies and UDGs, and their colours are bimodal ($\sim73\%$ blue, $\sim27\%$ red). Cross-matching with spectroscopic and cluster catalogues provides redshifts for 4,913 systems, enabling a systematic characterisation of the star-forming main sequence of LSBGs. Strong environmental trends are evident, with cluster LSBGs and UDGs exhibiting redder colours and reduced star formation compared to non-cluster systems. We demonstrate that domain adaptation enables robust cross-survey LSBG identification with deep learning models, providing a scalable pathway for constructing homogeneous LSBG catalogues for the LSST and Euclid era.

While the interplay of correlations and geometric frustration in doped Mott insulators provides a fertile ground for exotic quantum phases, the nature of the metallic state emerging upon particle doping remains poorly understood. In this work, we investigate the triangular-lattice Hubbard model with particle doping and provide compelling evidence for an intrinsic, interaction-driven quantum state, which we term the Nagaoka supermetal. This state is characterized by a sublinear temperature dependence in the DC resistivity, along with singular behaviors in the charge compressibility and zero-frequency spectral weight. To understand the origin of these singular properties, we derive an effective low-energy model and demonstrate that a higher-order Van Hove singularity emerges from the reconstructed dispersion. This singularity gives rise to a power-law divergence in the density of states, capturing the anomalous properties observed in the supermetallic regime. Our findings offer a new perspective on non-Fermi liquid states in geometrically frustrated systems and are directly accessible in current ultracold atom experiments.

We solve an open problem in entanglement theory posed by Yu et al., {\it Nature Communications 12, 1012 (2021)}. The problem is to show, via an entanglement witness, that the $14$-qubit state $Φ_{\text{E8}}$ is entangled. Inspired by a method from quantum codes, we combine symmetric extension with moment matrices to prove that $Φ_{\text{E8}}$ is entangled. The proof has the form of a rational infeasibility certificate for a semidefinite program, yielding an explicit entanglement witness. Our approach unifies and extends several earlier methods that involve the Lovász theta number of the Pauli anti-commutativity graph, promising scalability and flexibility in further applications.

Rare-earth gain media form the foundation of modern optical communications, emerging quantum hardware, and ultrafast optics. While chip-scale integration can enable fiber-like, and potentially beyond-fiber, functionality with unprecedented scalability, development in the visible and near-infrared remains in its early stages. Here, we demonstrate ytterbium-based optical gain integrated into an aluminum oxide photonic platform, achieving both single-mode lasing and optical amplification in the near-infrared regime. This platform delivers optical amplification with output powers exceeding 0.5 W, an optical-to-optical conversion efficiency above 70%, and a noise figure of 3.3 dB, approaching the quantum limit for phase-insensitive amplification. Furthermore, we achieve femtosecond pulse amplification to a record peak power of 14 kW, enabling supercontinuum generation with visible dispersive waves extending from 780 to 476 nm in conjunction with nonlinear photonic devices. This platform is compatible with heterogeneous integration into standard photonic circuits, laying the foundation for scalable visible-near-infrared photonic systems, including coherent laser arrays, mode-locked lasers, optical clocks, and microwave oscillators.

Scientific machine learning reports predictive performance. It does not report whether the same prediction would survive a different draw of training data. Across $9$ chemistry benchmarks, two classifiers trained on independent bootstraps of the same training set agree on aggregate accuracy to within $1.3\text{--}4.2$ percentage points but disagree on the class label of $8.0\text{--}21.8\%$ of test molecules. We call this gap \emph{cross-sample prediction churn}. The standard parameter-side techniques (deep ensembles, MC dropout, stochastic weight averaging) do not reduce this gap; two data-side methods do. The first is $K$-bootstrap bagging, which cuts the rate $40\text{--}54\%$ on every dataset at no accuracy cost ($K{\times}$-ERM compute). The second is \emph{twin-bootstrap}, our proposal: two networks trained jointly on independent bootstraps with a sym-KL consistency loss between their predictions, which at matched $2{\times}$-ERM compute reduces churn a further median $45\%$ beyond bagging-$K{=}2$. Cross-sample prediction churn deserves a column alongside predictive performance in scientific-ML benchmark reports, because without it the parameter-side and data-side methods are indistinguishable on the metric they actually differ on.

A search is performed for the electroweak pair production of charginos and associated production of a chargino and neutralino, each of which decays through an $R$-parity-violating coupling into a lepton and a $W$, $Z$, or Higgs boson. This search targets the Higgs boson decay channel of the charginos and neutralinos, using events with three or more $b$-tagged jets and one or two electrons or muons. The analyzed data corresponds to an integrated luminosity of 140 fb$^{-1}$ and 56 fb$^{-1}$ of proton-proton collision data produced by the Large Hadron Collider at center-of-mass energies of $\sqrt{s}=13$ TeV and $\sqrt{s}=13.6$ TeV respectively, collected by the ATLAS experiment between 2015 and 2023. The data are found to be consistent with predictions from the Standard Model. The results are interpreted as limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model. Limits are also set on the production of charginos and neutralinos for a Minimal Supersymmetric Standard Model with an additional $B-L$ gauge symmetry that is spontaneously broken. Charginos and neutralinos with masses between 150 GeV and 1100 GeV are excluded at 95% confidence level for a scenario in which they decay via Higgs bosons, assuming equal decay branching fractions to each lepton flavor. Additional limits are derived for flavor-specific decay scenarios.

We consider the ``metric-affine-like'' generalization of the Yang-Mills theory (mal-YM) which we first proposed earlier. In this model, the connection is no longer assumed to be compatible with the Hermitian form in the fibers. As a consequence, along with the usual YM potential $\boldsymbol{A}_a$ and the field strength tensor $\boldsymbol{F}_{ab}$, it contains non-trivially interacting fields $\boldsymbol{B}_a$, $\boldsymbol{h}$, and $\boldsymbol{G}_{ab}$, $\boldsymbol{N}_a$, forming a non-Abelian generalization of Stückelberg theory. Due to the spontaneous symmetry breaking $GL(n,\mathbb{C}) \to U(n)$, these new fields can be made massive and the limit $M\to\infty$ restores the standard YM theory. We perform a detailed analysis of this theory on the classical level. We discuss in detail geometric motivation for the model, field transformations, gauge symmetry and its spontaneous breaking, action, equations of motion, Noether identities, gauge fixing, and other issues.

Neural-network quantum states have emerged as a powerful variational framework for quantum many-body systems, with recent progress often driven by massively parallel architectures such as transformers. Recurrent neural network quantum states, however, are frequently regarded as intrinsically sequential and therefore less scalable. Here we revisit this view by showing that modern recurrent architectures can support fast, accurate, and computationally accessible neural quantum state simulations. Using autoregressive recurrent wave functions together with recent advances in parallelizable recurrence, we develop variational ansätze, called parallel scan recurrent neural quantum states (PSR-NQS), which can be trained efficiently within variational Monte Carlo in one and two spatial dimensions. We demonstrate accurate benchmark results and show that, with iterative retraining, our approach reaches two-dimensional spin lattices as large as $52\times52$ while remaining in agreement with available quantum Monte Carlo data. Our results establish recurrent architectures as a practical and promising route toward scalable neural quantum state simulations with modest computational resources.

Despite extensive research on chirality-driven spin selectivity, most studies have focused on static magnetic properties, while the influence of chirality on the dynamic magnetic response remains largely unexplored. Here, we investigate how chiral molecular interfaces affect magnetization dynamics in thin Co/Ni multilayers with perpendicular magnetic anisotropy using broadband ferromagnetic resonance spectroscopy. A comparison between bare (reference) films and molecule-functionalized (hybrid) samples reveals no measurable changes in either the resonance field or the linewidth that could be attributed to the presence of the chiral environment. Motivated by our findings we develop a macrospin description that distinguishes equilibrium modifications of the magnetic free-energy landscape (MIPAC-type effects) from non-equilibrium, CISS-induced spin torques. Our analysis shows that equilibrium modifications primarily shift the resonance condition via changes to the free energy landscape and thereby the effective field, whereas damping-like non-equilibrium torques provide a distinct channel for varying the effective damping rate. This approach establishes clear criteria for disentangling chiral-interface-induced energy modifications from torque-driven dynamical effects in ferromagnetic resonance experiments.

We consider non-Fuchsian monodromy preserving deformations on a Riemann sphere. The associated isomonodromic deformation parameters on this surface comprise the positions of the singularities, together with the Birkhoff (spectral) invariants owing to the presence of irregular singularities. Our first main result is the derivation of the Loewner evolution of these isomonodromic deformation parameters. Using this result, we construct martingale observables for Schramm-Loewner evolution (SLE(4)) processes in the presence of double poles. Geometrically, the expressions contain the pre-Schwarzian and Schwarzian of the Loewner evolution, arising from conformal covariance of the observable. Furthermore, we characterize these SLE(4) observables uniquely in terms of confluent BPZ equations of a CFT with central charge c=1.

The event PS16dtm, which occured in the center of the Narrow Line Seyfert 1 (NLS1) galaxy SDSS J015804.75-005221.8 (z = 0.080440), is one of the few candidates for a tidal disruption event in an already-acretting active galactic nucleus (AGN). We aim to shed light on the character of the tidal disruption event in this source since it exhibits unusual peculiarities, such as the double-peak optical/UV light curve and a low blackbody temperature with a lack of X-ray emission. We perform spectral analysis of the source before and during the event. We model the time evolution of the luminosity profile using a numerical code that describes the viscous evolution of the flow. From the combined spectral and timing studies, we interpret the event as the disruption of a $\sim 0.3 M_{\odot}$ main-sequence star, or gradual partial disruption of the low-mass giant star. The star is likely on a circular orbit, embedded in the accretion disc. The discussion of the evolution of the star rather suggests that the orbit is counter-rotating. We observe the system at a sufficiently large viewing angle that the actual disruption process is not directly observed. The disrupted star and inner disc are shielded from the observer by a gaseous envelope. Further observations of the system returning to the previous NLS1 state, particularly in the X-ray band, are needed to confirm the proposed scenario and to put constraints on the return to a regular NLS1 state.

We investigate the structure and emission properties of a thin accretion disk around a rotating charged black hole described by an effective higher-curvature-inspired spacetime, constructed as a phenomenological deformation of the Kerr Newman geometry. In this framework, the deformation is introduced through a modification of the metric function $Δ$ by an effective Gauss-Bonnet-like parameter $α$, such that the spacetime reduces to the standard Kerr Newman solution in the limit $α\to 0$. Adopting a kinematical approach, we use test-particle motion to derive the specific energy, specific angular momentum, and angular velocity of circular orbits, and analyze the effects of the parameters $α$ and charge $Q$ on the innermost stable circular orbit (ISCO), radiative efficiency, radiation flux, temperature, and differential luminosity of the disk. We find that increasing $α$ shifts the ISCO inward and enhances the disk's radiation flux and temperature, while the presence of charge suppresses these quantities due to electrostatic effects. Our results demonstrate that effective higher curvature deformations of rotating black hole spacetimes can lead to observable deviations from the Kerr case, highlighting accretion disks as sensitive probes of strong-gravity effects without relying on a specific underlying gravitational theory.

Variational quantum algorithms (VQAs) are a central paradigm for noisy intermediate-scale (NISQ) quantum computing, yet their reliance on predesigned and pretrained variational quantum circuits (VQCs) introduces critical security vulnerabilities, particularly backdoor attacks. These attacks embed hidden malicious behaviors that remain dormant under normal conditions but are activated by specific triggers, leading to adversarial outcomes such as incorrect predictions or manipulated objective values. This paper presents a survey of backdoor attacks in VQCs, covering data-poisoning, compiler-level, and quantum-native mechanisms. We formalize key terminology and threat models, and review existing attack strategies along with their empirical characteristics. We also analyze current detection and defense approaches, highlighting their limitations, especially against quantum-specific threats. By synthesizing recent advances, this survey outlines the evolving security landscape of VQCs and identifies key challenges and future directions for developing robust, quantum-aware defenses in hybrid quantum-classical systems.

We investigate the description of quark confinement in terms of confining strings or flux tubes. We show that compact QED with a topological $θ$-term, in the dyon condensation phase, is described by a massive two-form field $B_{μν}$ that gives rise to a string theory with an IR Brazovskii-Lifshitz fixed point at strong coupling. This corresponds to a quantum consistent "free string" in (3+1) dimensions, representing the dual of asymptotic freedom in the UV. Contrary to critical strings, which correspond to trivial Gaussian fixed points, this string is stabilized by a finite thickness, determined by the mass of the $B_{μν}$ field, instead of living in a higher-dimensional space. It correspondingly contains a massive world-sheet resonance, in addition to the Nambu-Goto phonons, that improves fitting with data. We compute the confining potential and show that it reproduces a generalized Arvis potential $V(L) = aL \sqrt{1 - c/L^2}$ with running parameters $a(L), c(L)$. We compute the mass difference ratios for the heaviest quarkonium and find 2.5 percent agreement with experiment already at the infrared fixed point. We also compute the intercept of Regge trajectories and find that the thickness of Brazovskii-Lifshitz strings tends to increase it from the Nambu-Goto value $α_0 = 1/12$. Overall, our findings strongly support Polyakov's longstanding conjecture on universality of confining gauge theories in the IR.

Planet-encircling dust storms fundamentally reshape Martian weather and the near-surface electrostatic environment. We investigate the generation and evolution of electric fields during global dust storms using bimodal dust size distributions from the NASA Ames Mars Global Climate Model, coupled with a triboelectric charging and electrostatic diagnostic scheme that links collisional charging to the local dynamical state of the atmosphere. Focusing on the dust-lifting and buildup phase and its subsequent evolution, we quantify the electric-field energy density and discharge characteristics, including onset thresholds, event frequency, and spatial clustering. The simulations reveal broad storm-active belts of enhanced electrification, with the most frequent threshold exceedances occurring in southern low-to-mid latitudes and secondary activity in northern low-to-mid latitudes. Modeled near-surface electric fields reach $10^{2}$--$10^{3}\ \mathrm{V\,m^{-1}}$ comparable to values inferred for smaller-scale dust phenomena. The results indicate that electric-field generation is controlled by the interplay between dust loading, turbulence-driven collisional activity, and conductivity-dependent charge relaxation, with diurnal conductivity variations strongly suppressing daytime electric-field buildup and most events remaining in the weak glow or Townsend discharge regime. While the model captures the large-scale distribution of electrically favorable conditions, the predicted spatial extent of activity likely represents an upper bound, as small-scale turbulent structures are not fully resolved. These results provide a quantitative framework to identify regions where electrostatic discharges are most likely during GDSs and to inform instrument design, power-system protection, and operations planning for future robotic and human missions.

Using techniques from the theory of von Neumann algebras, we propose a framework for addressing questions of controllability of bilinear systems on infinite dimensional Hilbert spaces. In the setup, we assume only that the drift and control terms arising in a bilinear control system are affiliated with a von Neumann algebra of finite type acting on the same Hilbert space. When the control terms satisfy basic norm bound conditions, we prove existence of time-optimal controls. In the more general setting where all operators may be unbounded, we show how the dynamical Lie algebra for the system is still well-defined and may be used to check approximate controllability of the system in question. We discuss how this approach can be applied to classical dynamical systems through the Koopman operator formalism, and investigate potential candidates for the von Neumann algebra which may guide the choice of controls. We illustrate how an affiliation relation naturally arises in both classical and quantum control systems with a few examples.

The Edelstein effect in magnetic systems enables magnetization switching via the coupling between current-induced spin accumulation and intrinsic magnetic order, and is therefore highly promising for next-generation spintronic devices. Realizing and manipulating the Edelstein effect in two-dimensional (2D) magnetic systems is particularly desirable for achieving high-efficiency and multifunctional spintronic applications. In this work, based on first-principles calculations and symmetry analysis, we demonstrate that the Edelstein effect can intrinsically arise in the 2D in-plane ferromagnetic semiconductor 2H-VTe2, with its behavior strongly dependent on the magnetization orientation. For monolayer 2H-VTe2 with D3h crystal symmetry, under an applied current along the +x direction, only the time-reversal-even z component and the time-reversal-odd y(x) component of the spin accumulation are allowed when the magnetization is aligned along +x (+y). For ferromagnetic bilayer 2H-VTe2 in AB or BA stacking, where the crystal symmetry is reduced to C3v, additional spin components emerge with the presence of in-plane magnetization. Specifically, for magnetization along +x (+y), besides dSz_even and dSy_odd (dSz_even and dSx_odd), extra components such as dSy_even and dSz_odd (dSy_even) become allowed. Notably, these additional components can be reversibly switched by changing the stacking configuration from AB to BA via interlayer sliding. Our results not only deepen the understanding of current-induced spin accumulation in 2D magnetic systems from both symmetry and first-principles perspectives, but also identify 2H-MX2 materials as a promising platform for realizing intrinsic and tunable Edelstein effects in high-efficiency spin-orbit torque devices.

Monolithic active pixel sensor (MAPS) developments have pushed the detection performance in various directions, especially relative to timing where nanosecond-level precision is now considered. This evolution calls for a simultaneous upgrade of the simulation tools. We have developed a simulation flow that covers steps from the signal creation in the sensitive volume to the output of the pixel digital logic that performs the time-of-arrival and time-over-threshold (ToA/ToT) measurements. This approach adds several new features to the traditional use the of the TCAD - Allpix Squared duo, among which : the integration of the pixel wells from the layout in order to precisely describe the pixel key characteristics such as leakage and punch-through currents and the coupling of Monte Carlo simulations (Allpix Squared) with high precision electrical simulations (SPICE). The first (Allpix Squared) for the precise description of the current induced at the collection electrode and the second (SPICE) to guarantee high precision simulation of the front-end electronics using realistic signal events. Irradiation is also modeled, both from the charge propagation side (charge trapping) and from the front-end response side (high input signal discharge). We have applied this methodology to the MAPS developed in the context of the Belle II vertex detector upgrade. In this contribution, we detail the key features of the exhaustive simulation flow, present the outcome of the comparison with the TJ-Monopix2 measurements and discuss the interest of the methodology for the development of modern MAPS.

We study the fully generalized Grover's algorithm to find the optimal phase changes for each step of the iteration to maximize gain in probability of observation of the target, and when phase matching is required. We find that classical Grover's algorithm and phase matching remains to be optimal till the target probability gets close 1. However, as the probability of observation approaches 1, the optimal phase changes differ from $π$ and no longer observe phase matching. We provide the optimization statement to find the optimal phase changes given the current amplitude vector and the size of the set. To analyze this formula, we approach it from a numerical and analytical perspective, with the analytical perspective focusing on special cases that simplify the optimization and allow for general statements about its behavior. Finally, we provide an example of a 5 qubit system and show that for the final iteration the optimal phase changes differ from traditional Grover's algorithm and do not observe phase matching, but lead to an increase in the probability of the target.

Costly cooperation and costly signaling are both difficult to reconcile with simple fitness maximization, yet both are common in biological and social systems. We study a model in which agents emit costly signals and condition their actions on the signals they observe. Across the Prisoner's Dilemma (PD), Snowdrift (SD), and Stag Hunt (SH) games, we ask when this coevolutionary process can sustain cooperation and how it changes across well-mixed populations, spatial lattices, and fluctuating strategic environments. The simulations show that signals are selected less by their raw production costs than by the cooperative responses they currently elicit. In well-mixed populations, the mechanism sustains partial cooperation in PD and SD and drives near-complete cooperation in SH. On lattices, cooperation is strengthened further by local assortment. A reduced mean-field analysis explains why average population feedback is already sufficient in SD and SH, but not in the PD. To account for the PD dynamics, the reduced theory must include transient correlations associated with rare signals, inheritance, or spatial clustering. Our results therefore delineate a class of settings in which costly signals persist because they transiently organize cooperative responses and thereby reshape the effective strategic environment.

Enhancing quantum illumination with highly entangled probes remains an active area of research. In this context, non-Gaussian operations provide an effective route for engineering probe states that can surpass the standard two-mode squeezed state (TMSS). In this work, we investigate a specific nonlocal non-Gaussian operation protocol and show that the engineered state using this protocol outperforms previously considered local non-Gaussian scenarios, engineered based on photon catalysis, addition, and subtraction under realistic conditions, including photon loss. Furthermore, by employing a $50{:}50$ beam splitter with photon-number difference detection, we demonstrate a significant enhancement in the signal-to-noise ratio (SNR) for target detection relative to the TMSS. Thus, our protocol exhibits improved performance, highlighting a resource-efficient and experimentally feasible probe for enhanced quantum illumination.

A key science target of the Large Interferometer Space Antenna (LISA) is to carry out multi-messenger observations of massive black hole binaries, observing the merger simultaneously in gravitational waves and with electromagnetic observatories. Identifying that a merger is happening and providing an updating estimate of the sky location in the hours, days and weeks before the merger is critical to enable electromagnetic observations of the merger event. In this work we demonstrate and compare two methods for premerger identification of massive black hole binaries; a zero-latency filter approach and, for the first time, an approach using an ``inpainting'' technique. We apply these methods to the LISA Data Challenge dataset 2a--Sangria-HM--and demonstrate the successful recovery of the 14 signals in the dataset that we expected to be identifiable at least half a day before merger. We show that the inpainting method can identify premerger signals even when gaps are present in the data, demonstrating the recovery of a signal even when 3 day-long data gaps are added to the 14 days preceding merger. Finally, we explore the challenge of overlapping signals, using a region of overlapping signals in the Sangria-HM dataset, all of which merge within a 10-day window, and show how removing signals that have been confidently identified from the data allows us to identify quieter signals in the same period.

We consider perturbations in the isotropic and homogeneous cosmological model with the spatially flat Friedmann-Lemaitre-Robertson-Walker metric in the framework of the theory of gravity with non-minimal derivative coupling. The Lagrangian of the theory contains the coupling term $ηG^{μν}\nabla_μϕ\nabla_νϕ$ and represents the particular example of a general Horndeski Lagrangian, which results in second-order field equations. It is known that the non-minimal derivative coupling crucially changes scenarios of the Universe evolution on early times. In particular, the $η$-term is dominating on early times and leads to a primary quasi-de Sitter (inflationary) stage which needs no fine-tuned potential. On late times the influence of non-minimal derivative coupling on the Universe evolution completely disappears, and this naturally leads to the transition to the standard cosmological evolution (post-inflationary stage). We have derived a complete set of equations which describe an evolution of scalar, vector and tensor modes of perturbations. All modes are analyzed analytically in two asymptotic cases, and then we construct exact numerical solutions which describe an entire evolution of the modes. We show that all modes, including vector ones, are amplified in the quasi-de Sitter (inflationary) stage, and such the behavior is cardinally distinct from that in Friedmann cosmology.

Quasi-periodic fast propagating (QFP) wave trains observed in the solar corona after some energetic events (solar flares, coronal mass ejections, jets) open possibilities for diagnostics of spatial and temporal scales of the impulsive energy release processes, that are absent in the standard model of a solar flare. Besides, the dynamics of the wave trains and their characteristic spatial and temporal signatures allow to localize the initial energy release volume magenta and to perform fine diagnostics of the transverse structures of plasma inhomogeneities in the solar corona. However, the small number of such events registered significantly limits their promising diagnostic potential. The aim of this paper is to perform an automatic search for fast wave trains in radio data. We apply classifying neural network/machine learning methods. Dynamic radio spectra obtained by HiRAS radio spectrographs within the 20 MHz -- 2.5 GHz frequency band during 2011 were used. We consider 50 global coronal EUV waves as marker events for more a targeted search in HiRAS data. Our automatic detector revealed 50 independent QFP-candidates events with the temporal signatures similar to that of the fast wave trains, with 13 candidates connected with the global waves.

Hybrid superconductor-semiconductor nanostructures are a central component for research spanning condensed matter physics and quantum information processing. Continued progress relies critically on the ability to characterize, control, and optimize several intrinsic material properties including spin-orbit coupling, band offsets, and disorder in a device-relevant stack that necessarily couples the electronic states of a superconducting metal film and a semiconductor. Here we report a new method to extract fundamental material parameters utilizing simple Shubnikov-de Haas (SdH) oscillation measurements in heterostructures in which metallic electronic states are coupled to a two-dimensional electron gas (2DEG) residing in an InAs quantum well beneath an aluminum thin film. Proper analysis of the full magnetoresistance data facilitates extraction of the quantum well carrier density, spin-orbit coupling strength, and both transport and quantum scattering times. Most importantly, the extracted scattering times in the 2DEG are impacted by the metal-semiconductor coupling strength allowing us to quickly gain information on proximity-induced superconducting gap without any fabrication or mK measurements. The wealth of information that is accessed with these simple measurements positions this methodology as an important tool for hybrid materials optimization.

We introduce the Dreaming $L$-directional Associative Memory (DLAM), a multi-layer Hebbian architecture in which off-line dreaming and supervised heteroassociative coupling coexist within a single energy function, placing our approach within the framework of energy-based models (EBMs). The replica-symmetric free energy, derived via the Guerra interpolation scheme, yields self-consistency equations governing the order parameters across the control-parameter space. The effective local field decomposes into signal, intra-layer dreaming noise, and inter-layer noise. Dreaming improves retrieval by differentially attenuating high-eigenvalue interference modes of the empirical correlation matrix, suppressing inter-pattern crosstalk while preserving the signal. Dreaming and inter-layer coupling prove synergistic, opening retrieval regions unreachable by either mechanism alone, as confirmed by Monte Carlo simulations for $L=3$. Their interplay is most pronounced on pattern disentanglement: given a mixture state as input, the network splits the constituent patterns one-per-layer, recovering each modality-specific pattern from a common cue that simultaneously blends noisy evidence from all sensory channels. Phase diagrams are planar projections of the hyperspace $(α,β,ρ,t)$-where $α$ is the storage load, $β$ the fast-noise inverse temperature, $ρ$ the dataset entropy, and $t$ the sleeping time. In the $(ρ,t)$-plane, the diagrams reveal a data-computation trade-off: off-line consolidation substitutes for additional training data, extending to heteroassociative architectures a phenomenon previously established for autoassociative networks. Enriching the standard Hopfield model with heteroassociativity and dreaming gives rise to EBMs capable of complex tasks beyond classical pattern recognition, contributing to a modern theory of neural information processing.

GW170817 remains the only binary neutron star merger detected through multimessenger emission. Its afterglow has been monitored for nearly a decade, offering an unprecedented opportunity to probe the properties of the outflow. The shallow decay of the very late-time afterglow challenges the prediction of a collimated structured jet. Motivated by recent general-relativistic magnetohydrodynamic simulations, we propose that the GW170817 afterglow is powered by a wobbling jet that drags a ring on the sky. This structure predicts a post-break decay rate shallower than that of a collimated jet, as observers will see a progressively longer emitting arc after the break. A misaligned ring-shaped jet can therefore self-consistently explain the multimessenger data without invoking any extra component. Through a Bayesian analysis of the multimessenger data, we find a ring-shaped jet is favored over a collimated jet at a significance level of 4.8$σ$. Our results imply a wobbling angle of $\sim 27^\circ$. Such a large angle points to a significant disk tilt, potentially arising from disk-infalling gas interaction or asymmetric angular momentum ejection. Similar shallow decays have also been found in other GRB afterglows, raising the possibility that wobbling jets are common among GRBs.

In a recent series of papers we developed a first-principle and gauge invariant approach to black hole perturbation theory valid to any order. We included back reaction effects to tackle the situation of evaporating black holes and obtained an explicit expression for the dynamics of the reduced phase space to second order. The physics of evaporating black holes is in particular encoded by apparent horizons, an observer dependent generalisation of the event horizon. We determine the shape of the apparent horizon to second order in the perturbations. The area of the apparent horizon is an interesting observable which is expected to decrease in the quantum theory due to Hawking evaporation. We show how the full four dimensional metric can be reconstructed in terms of the reduced phase space variables. In the quantum theory, taking expectation values of this metric, we obtain an effective classical metric, whose causal structure can then be visualised in a quantum corrected Penrose diagram. We conclude with an outlook into the quantisation procedure in the reduced phase space formalism and the implications on the area of the apparent horizon.

We demonstrate that the near-field thermal radiation between subwavelength SiC nanowires with square cross sections is dominated by multiple corner and edge resonances rather than the single surface-phonon-polariton channel of planar surfaces. Fluctuational electrodynamics simulations reveal that these resonances lie within the SiC Reststrahlen band, redshift for thinner nanowires, and yield a four-fold enhancement of thermal conductance. This maximum enhancement occurs when the separation gap nearly matches the nanowire thickness, balancing dimensional confinement and interwire coupling. These findings establish square nanowires as a versatile platform for geometrycontrolled near-field heat transfer in nanoscale heat management and energy conversion.