Gaia has the potential to deliver several tens of new dormant black holes (BHs) with low-mass stellar companions (hereafter, Gaia BHs) in the upcoming fourth data release. Three Gaia BHs are already known, but their formation pathways remain uncertain. Here, we perform a large parametric study to explore the formation of Gaia BHs from isolated binary systems with the population-synthesis code SEVN and compare our models with the properties of the three already reported Gaia BHs. Specifically, we explore the impact of accretion efficiency, mass transfer stability, natal kicks, angular momentum transport, and core-collapse supernova prescriptions. We find that models in which stable mass transfer is highly non-conservative and angular momentum is lost as a wind from the donor surface (Jeans mode) maximize the probability of forming dormant systems that match the properties of the observed Gaia BHs in terms of both orbital period and eccentricity, because such assumptions prevent the initial orbit from shrinking too much when the BH progenitor fills its Roche lobe. If we allow for common-envelope evolution, we find that models with common-envelope ejection efficiency $α < 1$ predict dormant systems with orbital periods that are too short compared to the observed Gaia BHs. The eccentricity of the observed Gaia BHs, when combined with information about orbital period and BH mass, favors relatively large natal kicks, similar to those inferred from Galactic neutron stars. Finally, models in which the natal kicks are low - e.g. because they are modulated by fallback - result in the formation of a large population of dormant BHs with long orbital periods ($P_{\rm orb}>10^4$ days) and low eccentricity, which will be tested soon by the fourth Gaia data release.

Inverse scattering focuses on recovering unknown scatterers from wave measurements. A fundamental challenge is determining whether an inverse obstacle problem can be resolved from a single far-field measurement, a task particularly demanding for non-convex polytope obstacles under generalized impedance boundary conditions and closely linked to the long-standing Schiffer problem. In this paper, we develop a novel \emph{Artificial Test Domain} (ATD) framework for single-measurement inverse scattering of impenetrable polytope obstacles. Based on microlocal analysis near exterior-visible flat boundary patches, this approach transcends traditional methods reliant on observable corners. The ATD framework establishes two primary conceptual advancements: a unified \emph{generalized impedance hyperplane (GIH) exclusion mechanism}, which clarifies the structural role of uniqueness mechanisms, and a unified \emph{qualitative--quantitative principle} for the generalized impedance setting. Quantitatively, the method yields a \emph{far-field--geometry relation} where geometric discrepancy is controlled by far-field error, scaled by a leading ATD coefficient. Qualitatively, the non-vanishing of this coefficient reduces to the exclusion of exterior generalized impedance hyperplanes. Once uniqueness is established, this relation produces sharp stability estimates. Within this framework, the classical stability estimates for the sound-soft and sound-hard cases are recovered as special instances of a much more general stability theory. At the same time, we obtain several new sharp stability results that are of significant importance. These results unify currently available single-measurement uniqueness regimes for polytope geometry and provide new insights into the Schiffer problem across multiple generalized impedance settings.

In this paper, we apply the Taylor--Wiles--Kisin patching method to the coherent cohomology of modular curves at minimal level. We establish a multiplicity-one result for the patched module by the $q$-expansion principle and show that a certain partial normalization of the crystalline deformation ring is Cohen--Macaulay. As applications, we prove new cases where crystalline deformation rings are Cohen--Macaulay, establish a Zariski density result for crystalline points in characteristic $p$, and prove a multiplicity-one result for Serre's mod-$p$ quaternionic modular forms.

In this work, we introduce a unifying Bregman-based majorization-minimization (MM) framework for solving nonconvex nonsmooth optimization problems. The proposed approach leverages Bregman divergences, possibly varying across iterations, to construct tailored surrogate functions that majorize the objective. We establish the convergence of the iterates of the resulting variable Bregman MM algorithm to critical points under the Kurdyka-Lojasiewicz property, relaxing standard assumptions such as the Lipschitz smoothness of the nonconvex objective function. We derive a constructive methodology to build a broad class of variable Bregman majorants with tractable minimizers. Our study encapsulates various existing majorization techniques, in particular those derived for Poisson data fidelity terms in imaging inverse problems. Numerical experiments on Positron Emission Tomography (PET) image reconstruction with a nonconvex regularizer showcase the practical feasibility of the proposed scheme.

We report the temperature-dependent synchrotron based X-ray diffraction analysis of NASICON type Na$_3$FeCr(PO$_4$)$_3$ sample, which undergoes a symmetry-lowering structural transition from a monoclinic ($C2/c$) phase with long-range Na-vacancy order to a rhombohedral ($R\bar{3}c$) phase with statistical disordered Na ions. The [FeCr(PO$_4$)$_3$] polyanionic framework remains essentially unchanged, confirming that the transition is governed by redistribution of the Na sublattice rather than by reconstruction of the host framework. The structural evolution is accompanied by a discontinuous increase in the $c$-axis and the unit-cell volume, reflecting the progressive depopulation of the Na(1) sites and transfer of Na ions toward the Na(2) sublattice. The temperature dependence of superstructure intensity found to deviate from mean-field critical behavior, instead, the experimental evolution is accurately captured by a sigmoidal phase-fraction model. The calorimetric measurements show that the enthalpy change for the first transition around 350~K is significantly larger than that of the anomaly around 445 K, indicating the dominant configurational rearrangement of Na ions occurs within the lower-temperature interval. Overall, the diffraction and calorimetric results demonstrate that Na ordering proceeds through an order-disorder transition involving intermediate Na configurations and a finite coexisting regime. The quantitative correlation between Na-vacancy ordering, lattice strain, and symmetry lowering reveals the central role of configurational interactions within the Na conduction channels in governing the phase stability of NASICON-type materials.

In studying primate vision, a large body of work focuses on the first feedforward sweep. During this initial time window, information is thought to pass through ventral stream regions in a stage-like fashion in an effort to extract high-level information from the retinal input. Consequently, electrophysiological analyses commonly focus on spatial response patterns, either by averaging data in time, or by applying decoders in a temporally local fashion. By analysing data recorded simultaneously across multiple arrays placed along the macaque ventral stream, we here show that this prior approach may be missing key aspects of information encoding. First, time-resolved, multivariate analyses of information transfer between V4 and IT reveal temporally and semantically varied information content as being exchanged within the first 100ms of processing. Second, by employing recurrent neural network (RNN) decoding techniques that extend across the temporal domain, we demonstrate that the neural pattern dynamics themselves carry categorical information far beyond the spatially encoded information available at any given time point. These findings challenge the prevailing view of a single, stage-like feedforward process and suggest that even the earliest parts of visual processing are better characterised as a spatiotemporally evolving process that encodes information in its dynamics rather than purely spatial response patterns.

All-optical generation of pure spin current -- the flow of spin in the absence of a corresponding charge flow -- relies on a symmetry based compensation of valley charge. The 2d $d$-wave altermagnets, ideal spintronics materials due to a very low spin-orbit coupling, possess a magnetic point group and highly anisotropic valley manifolds that would appear to preclude such current compensation, excluding them as materials for the ultrafast generation of pure spin current. Here we show that infra-red valley excitation combined with a THz pulse envelope allows the generation of large and nearly 100\% pure spin currents in the altermagnet Cr$_2$SO. Our approach is based on a valley selection rule coupling linearly polarized light to spin opposite valleys, along with the intrinsic momentum shift that a co-occurring THz pulse imbues a valley spin excitation with. These results thus provide a practical and all-optical route to the generation of pure spin current in $d$-wave 2d altermagnets, opening a route to lightwave control of spin in an environment with very low intrinsic spin mixing.

In this article, we find a theorem that gives a relation between the maximal fidelity of teleportation and the concurrence of the inseparable $X$ state used as a quantum channel in this process. Furthermore, we evaluate the concurrence of the output states generated by the local and nonlocal asymmetric broadcasting of entanglement and prove that the concurrence is greater in the case of nonlocal broadcasting. We analyze the possibility of using the output states obtained by the broadcasting of entanglement as quantum channels in quantum teleportation. We prove, with the help of the above-mentioned theorem, that all the inseparable states given by the local and nonlocal asymmetric broadcasting of entanglement are useful for quantum teleportation. Finally, we show that the maximal fidelity of teleportation is greater in the case when the second scenario is used, i.e., when the quantum channel is generated by the nonlocal asymmetric broadcasting of entanglement.

This paper proposes SU(2)-gauge-invariant field equations involving interaction with a scalar field. A connection with the Dirac equation is discussed.

Intellectual humility (IH)-a recognition of one's own intellectual limitations-can reduce polarization and foster more understanding across lines of difference. Yet little work explores how IH can be systematically defined, measured, evaluated, and enhanced in spaces that often lack it the most: online political discussions. In this paper, we seek to bridge these gaps by exploring two questions: 1) how might preexisting levels of IH influence future expressions of IH during online political discourse? and 2) can online interventions enhance IH across different political topics and conversational environments? To pursue these questions, we define a codebook characterizing different dimensions of IH and intellectual arrogance (IA) and have researchers use it to annotate several hundred Reddit posts, which we then use to develop and validate a classifier to support IH analysis at scale. These tools subsequently enable two key contributions: i) an observational data analysis of how IH varies across different political discussions on Reddit, which reveals that more/less IH environments tend to contain future posts of a similar nature, and ii) a randomized control trial evaluating strategies for nudging discussion participants to demonstrate more IH in their posts, which reveals the possibility of enhancing IH in online discussions across a range of contentious topics. Our findings highlight the possibility of measuring and increasing IH online without necessarily reducing engagement.

Difference-in-Differences (DiD) is a widely used research design that often relies on a conditional parallel trends (CPT) assumption. In contrast to settings with unconfoundedness, where causal graphs provide powerful frameworks for reasoning about valid conditioning variables, general-purpose graphical tools for CPT are missing. We introduce transformed Single World Intervention Graphs (SWIGs), the $Δ$-SWIGs, and prove that they enable us to read off conditional independencies via $d$-separation that imply CPT. Using $Δ$-SWIGs, we study valid conditioning strategies for DiD in complex settings with multiple periods and time-varying covariates. We show that when time-varying covariates affect the outcome, controlling for post-treatment variables is required for identification. However, even when such controls are included, pre-treatment parallel trends are only informative about a subset of the assumptions required for unbiased post-treatment effects, highlighting the limitations of purely empirical justifications of CPT.

The so-called SAGA-LD algorithm is used for efficient sampling from high-dimensional distributions in machine learning. Its intricate dynamics resists standard approaches of Markov chain theory. We prove, using a model-specific method, that SAGA-LD converges to a limiting distribution and a law of large numbers holds.

Quantum thermodynamics addresses the dynamics of heat flow in quantum devices driven out of equilibrium. Although mesoscopic circuits at low temperatures provide a flexible platform to explore this dynamics, experimental studies are wanting because thermal timescales in nanodevices are often too fast. Here we engineer and investigate with noise thermometry a mesoscopic thermal circuit where heat flows between electron, phonon and nuclear systems can occur on slower timescales. The central constituent of this device is a micrometer-scale metallic island electrically connected to large cold electron reservoirs through two to four ballistic quantum Hall channels, a component frequently used for exploring stationary thermal currents. We uncover a two-step thermalization process specific to the mesoscopic scale, involving a fast initial temperature step followed by a much slower rise extending over minutes. This observation is quantitatively accounted for by the balance between heat flows through electronic quantum channels, to cold phonons, and to the nuclear spins in the metallic island. The disclosed mesoscopic thermalization takes a step into the field of quantum thermo-\emph{dynamical} phenomena, highlighting their distinctive nature on a central constituent of quantum circuits. The implications for the thermal engineering of nanodevices include the thermal characterization of exotic states at high magnetic field.

Spatiotemporal chaotic systems are difficult to characterize in a model-free manner because of their high dimensionality, strong nonlinearity, and sensitivity to initial conditions. Coupled map lattices, as a representative class of extended nonlinear systems, exhibit diverse regimes such as frozen random pattern, defect chaotic diffusion, and fully developed turbulence. In this work, we propose an ensemble version of multiplexing local reservoir computing for the data-driven characterization of spatiotemporal chaos. By constructing multiple base learners with randomized hyperparameters and combining their outputs, the method improves prediction robustness and quantifies predictive uncertainty through ensemble spread. More importantly, we show that this uncertainty contains direct dynamical information. It identifies frozen positions in frozen random pattern, supports the estimation of defect diffusion coefficients in defect chaotic diffusion, and provides an effective indicator of chaotic intensity in fully developed turbulence. Analyses of the spatial power spectrum and Lyapunov exponent spectrum further support the consistency between the uncertainty field and the intrinsic dynamical properties of the system. These results show that ensemble reservoir computing can serve not only as a prediction tool but also as a data-driven framework for the dynamical characterization of high-dimensional nonlinear systems.

We study the distinguishability of quantum states under local operations with classical communication (LOCC), separable, and positive-partial-transpose (PPT) measurements, focusing on locally diagonal orthogonally invariant (LDOI) states -- those invariant under local diagonal orthogonal twirling. This class includes many important families such as Werner states, isotropic states, X-states, and Dicke states. We show that optimal PPT and separable measurements for distinguishing LDOI states can always be taken to be LDOI, and the LOCC supremum can be approached by LDOI LOCC POVMs, enabling a dimensional reduction from $n^4$ to $O(n^2)$ in the associated optimization problems. We establish efficiently computable bounds on the distinguishability of orthonormal LDOI bases and prove that for a broad class of such bases -- including all two-qubit cases -- the LOCC supremum equals the PPT and separable optima. More generally, we show the gap between PPT and LOCC distinguishability is at most $(n-2)/(2n^2)$ for local dimension $n$.

Bounding causal effects analytically, rather than numerically, is appealing for its interpretability and conceptual clarity. Existing sharp methods rely on optimization-based approaches such as the Balke-Pearl framework, whose computational complexity grows rapidly. An alternative line of work derives bounds heuristically using probability laws and generic inequalities, and some recent papers have claimed or conjectured that this approach can yield sharp analytical bounds with substantially lower complexity. In this paper, we show that this perceived advantage is illusory. In particular, in a discrete instrumental variable setting, we show that any sharp analytical bound for the average treatment effect must be expressible as a maximum (minimum) over a collection of linear terms whose cardinality grows exponentially in the number of values taken by the outcome. In parallel, we show that the number of instrumental variable inequalities itself also grows exponentially. Consequently, bounds and inequalities expressed using only polynomially many such terms cannot be sharp. As a constructive complement, the paper is accompanied by codes implemented in python and R to derive sharp analytical bounds and sharp inequalities with optimal efficiency, matching the lower bounds proven in this paper. These codes are available online.

The symmetric subrank of homogeneous polynomial is the largest number of terms in a diagonal form to which it can be specialized by a (typically non-invertible) linear variable substitution. Building on earlier work by Derksen-Makam-Zuiddam and Biaggi-Chang-Draisma-Rupniewski for ordinary tensors, we determine the asymptotic behavior of symmetric subrank and symmetric border subrank of degree-d forms as the number of variables tends to infinity. Furthermore, by using results from geometric invariant theory we show that for cubic (resp. quartic) forms the symmetric subrank and symmetric border subrank coincide if the latter is at most three (resp. two).

The emergence of precision gravity simulators in quantum and fluid systems is opening new avenues for probing curved-spacetime physics and black-hole phenomenology under controlled laboratory conditions. In parallel, advances in understanding how fundamental physics can be probed in the spectral signatures of black holes and exotic compact objects motivate the development of modern spectroscopic techniques within analogue-gravity experiments. In this work, we model the spectral properties of analogue black holes sourced by broadband stochastic noise, a crucial aspect in realistic experiments that poses substantial challenges for established data-analysis techniques. Using simulation-based inference, we demonstrate that the physical parameters encoded in noisy spectra can be reliably extracted, showing that these techniques provide a powerful tool for studying both spacetime properties and boundary effects in gravity simulators.

We investigate the Sobolev regularity required for almost everywhere convergence to the initial datum of solutions to the linear Schrödinger equation along certain tangential curves. In the regime $α<\tfrac12$, we analyze maximal estimates for expressions of the form $e^{itΔ}f(x+γ(t))$ over specific $α$-Hölder curves $γ$ and initial data $f\in H^s(\mathbb{R}^n)$. For the model family $γ(t)=(t^{α_1},\ldots,t^{α_n})$, where $α=\min_j α_j$, we show that the critical regularity is $s=\max\left\{\frac{1-2α}{2},\frac{n}{2(n+1)}\right\}.$

Neural operators have been increasingly used as data-driven surrogates for time-marching predictions of turbulent flows. However, long-horizon autoregressive prediction is sensitive to error accumulation and the choice of prediction interval. Excessively small time increments may increase temporal redundancy and lengthen rollouts, which can degrade the stability of neural operators in turbulence forecasting. This work pursues a unified objective: stable long-horizon autoregressive prediction at fine temporal resolution for three-dimensional turbulence. We propose a multi-stepsize mixture-of-experts (Ms-MoE) neural operator built on an implicit factorized Transformer (IFactFormer) backbone. The model conditions on a requested relative stride and uses a time-step router to activate scale-specific routed experts together with a shared expert, yielding a single architecture that represents a family of stride-parameterized time-advancement operators. We evaluate the approach on forced homogeneous isotropic turbulence (HIT) and turbulent channel flow using filtered direct numerical simulation datasets. Relative to sampling intervals used in previous studies, we construct training datasets with up to 20 times finer temporal resolution and report long-horizon autoregressive rollouts using qualitative time-slice comparisons and long-time-averaged statistics. Ms-MoE-IFactFormer yields more stable long-horizon rollouts and improved agreement with long-time-averaged statistics on both HIT and turbulent channel flow, suggesting potential for stable time-marching at fine temporal resolution in more complex turbulent flows.

Current discourse on Artificial Intelligence (AI) ethics, dominated by "trustworthy" and "responsible" AI, overlooks a more fundamental human-computer interaction (HCI) crisis: the erosion of human agency. This paper argues that the primary challenge of high-stakes AI systems is not trust, but the preservation of human causal control. We posit that "bad AI" will function as "bad UI," a metaphor for catastrophic interface failures that misrepresent system state and lead to human error. Applying Marshall McLuhan's media theory, AI can be framed as a technology of "augmentation" that simultaneously "amputates" the user's direct perception of causality. This places the interface as the critical locus where a "double uncertainty"--that of the human user and that of the probabilistic model--must be mediated. We critique current Explainable AI (XAI) for its correlational focus and failure to represent uncertainty. We conclude by proposing a rigorous, nested Causal-Agency Framework (CAF) that integrates causal models, uncertainty quantification, and human-centered evaluation to restore agency at the interface.

Persistent radio sources (PRSs) are (sub-)parsec-scale compact non-thermal continuum sources associated with some repeating fast radio bursts (FRBs). Their nature is debated, but their properties provide insights into the FRB environment and progenitors. We measure the spectrum of the recently confirmed PRS associated with FRB 20190417A. Spectral features such as the self-absorption and cooling break can be used to constrain the age and size of PRSs and test theoretical models. We present observations made with the 1.26 GHz upgraded Giant Metrewave Radio Telescope (uGMRT) and observations from the 6 GHz Karl Jansky Very Large Array (VLA). With complementary archival data and the LOw Frequency ARray Two Meter Sky Survey (LoTSS), we characterise the spectrum of the PRS between 144 MHz and 6 GHz. The spectrum follows a power-law behaviour at gigahertz frequencies. The source is not detected at 144 MHz down to a $2σ=170 \; {\rm μJy}$ sensitivity. We modelled the spectrum with a broken power law, obtaining a spectral index $α= 0.20 \pm 0.05$ between 1-6 GHz. We placed a lower limit on the turn-over frequency of $> 370$ MHz ($95\%$ confidence). The flat spectrum and low-frequency turn-over of the target are consistent with the spectral properties predicted for magneto-ionic nebulae, inflated behind the supernova ejecta by a flaring young magnetar. Considering the multi-zone magnetar wind nebula scenario, we estimate an age of $t< 250$ yr and a radius of $R< 0.4$ pc for the target, which would thus be slightly older than the PRSs associated with FRB 20121102A and FRB 20190520B.

In this paper we analyze a model for electroporation, a biological process in which a cell membrane exposed to an external voltage becomes permeable due to the formation and growth of nanoscale membrane pores. We prove a local stability result for asymptotic self-similar solutions with a power-law tail. Our method relies on the analysis of an equation for the first moment as well as comparison of solutions of the full problem to solutions of a corresponding transport problem. In particular this shows that the transport term drives the long-time behaviour.

This study investigates Chinese primary school students' acceptance of a social robot for English-as-a-foreign-language (EFL) speaking practice through a sequential explanatory mixed-methods design. Integrating the Technology Acceptance Model (TAM) and the Computers Are Social Actors (CASA) paradigm, the research explores both functional and social factors influencing learners' behavioural intention to use the robot. Quantitative data from 436 students were analysed using structural equation modelling, followed by qualitative interviews with twelve students to interpret the findings. Results show that perceived enjoyment and ease of use are the strongest predictors of acceptance, while social attributes such as warmth, anthropomorphism, and social presence significantly enhance enjoyment. Perceived intelligence affects usefulness but not ease of use. The findings suggest that emotional and social engagement are central to young learners' acceptance of educational robots, highlighting the importance of designing socially intelligent technologies that promote motivation and speaking confidence in EFL learning contexts.

We report on the shape taken by the interface of a liquid bath when hit by a smooth oblique steady jet. When the angle between the jet and the bath decreases below $50^\circ$, a cavity is formed in front of the jet. In the inertial regime we explore, the jet boundary layer detaches in the impact region, thereby delimiting a core jet region outside of which the liquid is mainly in hydrostatic equilibrium. The shape of the outer meniscus is shown to be related to the one outside a tilted fiber piercing the fluid interface. In order to unravel the flow features and separation, we perform direct numerical simulations and show that the flow detachment displays an asymmetry, which results in the acceleration of the liquid below the surface, thereby creating a depression. With this observation, we propose a model balancing the suction force of this depression with the weight of the displaced water and the surface tension force to obtain a prediction for the typical width of the cavity.

The observed unusual behaviors of the orbits of Trans-Neptunian objects as well as the gravitational anomalies detected by the Optical Gravitational Lensing Experiment can be explained by assuming the existence of a ninth planet in the Solar System, having a mass of the order of $5-10M_{\oplus}$, and located at the distance of 300-1000 AU from the Sun. Since no optical counterpart of Planet 9 was observed, it is reasonable to assume that it has a very low luminosity. Various proposals on the nature of Planet 9 have been advanced, including the possibility that it is a black hole, an axion or a dark matter star. We propose that dark matter heating of Planet 9 could generate a thermal radio flux that could allow its observational detection, even if Planet 9 is a very dark object. We estimate the dark matter impact parameter, the mass and the kinetic energy deposition rates, as well as the surface temperature of Planet 9. By adopting a specific model for the time evolution of the planet, and assuming a long time capture of dark matter, the surface temperature of Planet 9, and the spectral features of the emitted radiation are obtained. Our results indicate that dark matter capture may provide an efficient mechanism for the heating of Planet 9, and also provide a specific observational signature of the planet. The numerical evaluations depend on the unknown value of the dark matter-ordinary matter interaction cross-section, with the estimates obtained as a function of its ratio and the saturation cross section for dark matter to deposit its entire energy. For a value of this ratio of $10^{-10}$, and for a dark matter density of the order of $1.32\times 10^{-17}$ g/cm$^3$, in a few Gyrs the surface temperature of Planet 9 can reach values of the order of 200 K, or even higher, with a maximum wavelength of around $λ_{max}=1.44\times 10^{-3}$ cm, situated in the infrared domain.

We establish global-in-time decay estimates for the multi-phase Muskat problem in the case where the density takes exactly n+1 distinct constant values. We first linearize the system around a flat stable configuration, followed by the study of associated linearized operator. The asymptotic behavior at low frequencies of eigenvalues yields the decay rate of (1+t)^{-s/2-1/4} for Wiener norm \|f\|_s, which is slower than the classical case, where the decay rate is (1+t)^{-s+ν}. Afterwards we bound the nonlinear term to close the argument.

Recent years have witnessed tremendous progress in developing a fine-grained low-dimensional holographic correspondence, specifically the construction of quantum mechanical boundary theories as holographic duals of two-dimensional gravity. In these developments, quantum chaos played a crucial role, both as source of universality and as a guiding principle for the matching of bulk and boundary signatures of gravity. In this article we review the construction of the chaos-assisted low-dimensional holographic correspondence for non-experts. We open with an introductory discussion of the two main protagonists of the theory, the SYK model and two-dimensional Jackiw-Teitelboim gravity. Within this framework we will discuss two independent 'bridges' between bulk and boundary physics, one pertaining to early time chaotic instabilities, the other to late time quantum chaos up to and including time scales of the order of the gravitational quantum level spacing. We will demonstrate that the resolution of these fine-grained quantum scales requires the extension of semiclassical gravity by elements of string theory. We conclude with an outlook towards higher dimensional generalizations of the chaotic holographic correspondence.

The temporal and spatial coincidence between the gravitational wave (GW) event GW190425 and the fast radio burst (FRB) event FRB 20190425A raises the intriguing possibility of a physical connection between the two. The widely discussed possibility invoking the collapse of a supermassive neutron star as the merger product suffers the inconsistency between the model prediction and the measured inclination angle of the system. Here, we propose a novel physical mechanism to account for the association. We envisage a magnetar located at about 2.5 light hours away from the binary neutron star merger site. The kiloherz GWs generated by the merger are converted into kiloherz electromagnetic (EM) radiation via the Gertsenshtein-Zeldovich (GZ) effect near the magnetar. Subsequent inverse Compton scattering off the kilohertz EM waves by relativistic particles generates the observed gigahertz FRB emission. Our calculation reveals that, with appropriate parameter choices, the properties of FRB 20190425A can be reproduced.

In this paper, we study the mass-constrained fractional Choquard equation \( (-Δ)^s u = λu + α(I_μ* |u|^{\frac{2N-μ}{N}})|u|^{\frac{2N-μ}{N}-2}u + (I_μ* |u|^p)|u|^{p-2}u \) in \( \mathbb{R}^N \), under the constraint \( \int_{\mathbb{R}^N} |u|^2 \, dx = c^2 > 0 \), where \( N > 2s \), \( s \in (0,1) \), \( μ\in (0,N) \), \( α> 0 \), and \( 2 + \frac{2s-μ}{N} \le p < \frac{2N-μ}{N-2s} \). We first establish a nonexistence result in the \( L^2 \)-critical case \( p = 2 + \frac{2s-μ}{N} \). Then, in the \( L^2 \)-supercritical range, we prove the existence of normalized ground states in two complementary regimes determined by the quantity \( \mathcal{M}_1(c) \). Our approach is based on constrained variational methods, a min-max construction, and refined estimates for the associated fiber maps.