Roblox is among the most popular online gaming platforms, used by hundreds of millions of users every day. A substantial portion of these users are underage, who are at a greater risk, where abusive users may utilize Roblox's real-time chat interface to make the initial contact with potential victims. Roblox employs automated chat moderation mechanisms to detect potentially abusive messages; however, to date, their effectiveness has not been independently investigated. Toward this goal, we collected approximately 2 million chat messages from four games across multiple age groups and analyzed them to evaluate the moderation system. These messages were collected from public game servers following ethical and legal norms as well as Roblox's terms of service. We use this corpus to qualitatively study which types of unsafe chats escape the moderation system and how policy-violating users evade the moderation system. Given the dataset's scale, it is prohibitively expensive to conduct qualitative content analysis manually. Therefore, we adopt a two-step approach. First, we manually labeled safe and unsafe messages (n=99.8K) and used them as a ground truth to evaluate four locally hosted state-of-the-art large language models (LLMs). Next, the best-performing LLM was applied to the entire corpus to identify potentially unsafe messages, which we manually categorized using iterative open and axial coding methods until thematic saturation was reached. Overall, our findings reveal a troublesome reality: numerous instances of unsafe chat messages related to grooming, sexualizing minors, bullying, & harassment, violence, self-harm, and sharing sensitive information, etc., escaped the current moderation. Our analysis of users whose messages were previously flagged revealed that they continue to send harmful messages by employing a wide range of techniques to evade the moderation system.

This study derives the unitary dynamics of a four qubit Heisenberg XXX chain with tunable next nearest neighbor coupling $α$, starting from a Bell type initial state, and analyzes the evolution of quantum resources under the phase $ϕ= (α+ 1)t$. We provide closed form expressions for fidelity $F(ρ(0),ρ(t))$, coherence $C_{l_1}(ρ(t))$, and two qubit entanglement of formation $E_F(t)$ for subsystems $12$ and $34$, all of which are governed by $ϕ$. Fidelity exhibits periodic behavior with $F = \lvert \cos(ϕ/2) \rvert$ and a frozen regime at $α= -1$ where $F \equiv 1$. Coherence follows $C_{l_1}(ρ(t)) = \sin^2(ϕ/2)$, showing increasing sensitivity with $\lvert α+ 1 \rvert$ and vanishing at $α= -1$. Entanglement of formation $E_F(t)$ is an entropic function of $ϕ$, displaying banded oscillations and freezing at $α= -1$. The phase $ϕ$ unifies the behavior of all diagnostics, linking faster dynamics to larger $\lvert α+ 1 \rvert$ and revealing maximal sensitivity at $(α+ 1)t = π/4 + kπ/2$. This integrated framework provides exact benchmarks for small quantum devices and a clear pathway to noise, finite temperature, and larger system extensions.

AI chatbots already function as de facto mental health support tools for millions of people, including people in crisis. Yet, they lack the clinical validation, shared standards, and coordinated oversight that their societal role demands. This primer was developed in conjunction with a multistakeholder workshop hosted by Partnership on AI in 2026, convening AI labs, mental health practitioners, people with lived experience, and policymakers, to provide a common cross-sector reference point for the current state of the field of AI and suicide prevention. It begins with an overview of clinical best practices, then turns to how frontier AI systems (as of winter 2026) detect and respond to suicide and non-suicidal self-injury (NSSI) queries. Together, these provide insight into what it would take to design and implement AI tools that not only better prevent suicide and NSSI, but also promote overall well-being. Drawing on clinical literature, publicly available AI lab policies, an emerging landscape of evaluation frameworks, and conversations with leaders across the AI and mental health fields, we map challenges posed by general-purpose AI chatbots for mental health across model, product, and policy layers, ultimately highlighting priority areas where cross-industry alignment is both urgently needed and achievable.

Given an issue on a software repository, a reproduction test confirms its presence in the code before it gets fixed and its absence after. Reproduction tests provide crucial execution-based feedback for diagnosis and validation during software development. Unfortunately, they are usually missing. Therefore, recent work has introduced both benchmarks and a thriving literature on solutions for reproduction test generation from issues. However, that work has focused on Python and neglected other languages such as Java, which is important for enterprise software. This paper introduces both a benchmark and a solution for Java repository-level reproduction test generation. The benchmark, TDD-Bench-Java, is the first to model this problem and comprises 250 instances sourced from popular open-source repositories. The solution, e-Otter++ for Java, adapts a state-of-the-art reproduction test generator for Python to yield high performance on Java. To evaluate in an industry setting, besides empirical results with TDD-Bench-Java, this paper also presents results with a contamination-free proprietary dataset. Overall, we hope that this paper contributes to bringing better diagnosis and validation to Java software development.

The main aim of the present work is to demonstrate that the analogue gravity phenomena are not an artifact of linear perturbation, rather gravity-like effects emerge through the non linear higher order perturbation of transonic fluid as well. To establish that fact, a spherically accreting astrophysical system has been considered where the hydrodynamic accretion with a relativistic, multi-component equation of state with position dependent adiabatic index onto compact astrophysical objects has been considered. By extending the acoustic metric formalism beyond the linear regime, it has been shown that the aforementioned perturbations satisfy a covariant wave equation in an effective acoustic spacetime with non-linear corrections, making the analogue geometry dynamical. As a consequence, the acoustic horizon can shift (inward or outward), depending on the relative amplitudes of density, temperature, and mass accretion-rate fluctuations. This provides a more realistic framework to investigate the dynamics of the non-linear analogue spacetime in astrophysically relevant accretion flows.

Understanding protein conformational dynamics is essential for elucidating biological function but remains challenging due to the wide range of timescales and the complexity of collective motions. Enhanced sampling methods overcome timescale limitations of conventional molecular dynamics, yet their effectiveness depends on the choice of collective variables (CVs), which are often difficult to define and may lack physical interpretability. In particular, collective variables derived from machine learning or collective vibrational modes can efficiently capture slow dynamics but are not easily mapped onto intuitive structural descriptors. Here, we present a fully automated framework that transforms enhanced sampling trajectories into human-readable representations of protein dynamics. Our approach combines enhanced sampling along CVs derived from frequency-selective anharmonic mode analysis with a post hoc analysis of biased trajectories using weighted dynamic cross-correlation matrices. From these, we identify residue pairs and domains exhibiting correlated and anti-correlated motions, yielding simple domain-domain distances that serve as physically interpretable CVs. We apply this method to five proteins, including KRAS and HIV-1 protease, and show that it consistently identifies biologically relevant domains and motions without prior system-specific knowledge. Projection onto these distances produces free energy surfaces that reproduce known conformational states with low statistical uncertainty while maximizing independent dynamical information. This workflow enables systematic recasting of complex CVs into simple geometric descriptors without loss of essential dynamics. Its generality and automation make it broadly applicable for interpreting enhanced sampling simulations and generating interpretable conformational ensembles for integration with emerging machine learning approaches.

We solve an equation of motion for the axial-vector field under boundary conditions of the bulk-to-boundary propagator in the framework of the hard-wall model of AdS/QCD. The equation is reduced to the form of a homogeneous ordinary differential equation with varying coefficients. We solve conjugate equations and find fundamental solutions. This allows us to establish main relations and necessity conditions. The integral equation has both Volterra and Fredholm terms and was solved by the iteration method. We apply a new scheme to solve the equation, since all linearly independent necessary conditions for the existence of a solution were defined and used to establish a sufficient condition for Fredholm solvability of the problem.

Long-period cyclic reversals of the large-scale magnetic field are a prominent feature of the dynamo associated with the magnetorotational instability (MRI) in accretion disks, but their physical origin remains unclear. We develop a quasilinear theory (QLT) of the MRI dynamo where the electromotive force (emf) is computed from the linear eigenfunctions under the WKB approximation. The emf depends on the mean field $\mathbf{B}$ more generally than standard mean-field closures allow. In the unstratified case, the leading order contribution to the large-scale dynamo is the shear-current effect: the emf depends on the current $\mathbf{J}$ as $\pmb{\varepsilon} = \pmbβ\cdot\mathbf{J}$, with a tensor $\pmbβ(\mathbf{B},t)$ that oscillates with time $t$ and whose off-diagonal components generate the mean field. The oscillations arise from beats between the two branches of eigenfrequencies. Since the beat frequency varies only weakly with wavenumber, the beats remain coherent and drive the long-period butterfly cycle seen in local shearing box simulations. We predict a dominant cycle period $\sim 30{\left(1+a^2\right)}^{1/2}\,t_{\rm orb}$, with $a$ the vertical-to-radial aspect ratio and $t_{\rm orb}$ the orbital period, and an amplitude scaling $\sim a^2$ before saturation at $a\gtrsim 5$. Both trends agree with zero-net-flux unstratified shearing box simulations with Athena++. A carrier-envelope analysis of the simulation spectra shows that the same interference mechanism extends beyond strict QLT, through higher-order linear combinations of the eigenfrequencies, with observed cycles arising from pairwise beats within this spectral network. These results identify coherent interference between nearly degenerate eigenfrequencies as a key mechanism behind large-scale cyclic dynamos, with implications for magnetic variability in protoplanetary disks, X-ray binaries, and AGNs.

Speech encodes multiple simultaneous attributes -- linguistic content, speaker identity, dialect, gender --that conventional single-vector embeddings conflate. We present a factor-partitioned embedding framework that maps each utterance into a single vector whose subspaces correspond to distinct axes of variation. A shared acoustic encoder feeds per-axis linear projection heads, each trained via distillation from a specialist teacher or a contrastive objective over shared-label pairs. The resulting embeddings support attribute-conditioned retrieval: similarity is computed as a signed weighted sum over per-axis cosine scores, allowing retrieval that jointly considers what was said and how -- or explicitly suppresses one attribute to surface another. We evaluate on cross-corpus retrieval over corpora sharing the Harvard sentence prompts, demonstrating that signed axis weighting can suppress same-speaker bias and surface semantically matched utterances across recording conditions. Code is available at: https://github.com/jimregan/spoken-sentence-transformers

Recent Large Language Models (LLMs) have shown strong performance on automated program repair across standard benchmarks. However, these benchmarks evaluate models on a single canonical form of buggy code and do not reflect the syntactic variations commonly observed in real-world software, leaving robustness largely unexamined. In this work, we construct HEJ-Robust, a robustness benchmark built from HumanEval-Java-Bug using eight semantics-preserving code transformations, resulting in 1,450 transformed instances. We evaluate five fine-tuned LLMs on this benchmark and show that model performance drops by over 50% under several transformations, indicating that current LLM-based repair models lack robustness to minor syntactic variations.

Large Language Models (LLMs) have achieved remarkable success in automated code translation. While prior work has focused on improving translation accuracy through advanced prompting and iterative repair, the reliability of the underlying evaluation frameworks has received less attention. In this paper, we demonstrate that a significant number of reported failures in code translation are not due to incorrect logic, but rather evaluation-induced errors stemming from improper compilation flags, missing library links, and unconfigured runtime environments. We conduct a large-scale empirical study across five programming languages (C, C++, Java, Python, Go) and three benchmarks (Avatar, CodeNet, EvalPlus), covering 6,164 translations generated by GPT-4o, DeepSeek-Coder, and Magicoder. Our analysis identifies and categorizes common false negatives, distinguishing pipeline-induced failures that affect any model from model-dependent behaviors that vary across LLMs. Our findings highlight the necessity for transparent, configuration-aware evaluation standards to accurately assess progress in LLM-based code translation.

The considerable difference between early and late universe measurements of the Hubble constant, called the Hubble tension, poses a potential challenge to the standard $Λ$CDM cosmological model. We examine an interacting dark matter-dark energy model, $Λ_s$CDM, characterized by a gauge-invariant coupling $Q = ξHρ_{\mathrm{de}}$ and an effective pressure dynamically induced within the dark matter fluid. Using the CLASS Boltzmann code modified in this work, we analyze both the background and perturbation observables and compute an extensive Markov Chain Monte Carlo analysis with the latest cosmological datasets, including observational Hubble parameter data, Planck 2018 CMB compressed likelihood, BAO (from DESI DR2), Pantheon+ Type Ia supernovae, and redshift-space distortion measurements. The model predicts $H_0 = 71.8_{-0.3}^{+0.4}\mathrm{kms^{-1}Mpc^{-1}}$, reducing the tension with the SH0ES local measurement from about $5σ$ in $Λ$CDM to $1.2σ$ in $Λ_s$CDM. In contrast to the early dark energy model, the resolution emerges from late-time modification of the expansion history induced by the energy transfer from dark matter to dark energy. Moreover, the model suppresses late-time structure growth, providing $σ_8 = 0.744 \pm 0.0185$, lying below the $Λ$CDM value and moves in the direction preferred by weak lensing surveys. Since the interaction term is suppressed at high redshift, the pre-recombination sound horizon departs by less than $1\%$ from its $Λ$CDM value, suggesting that the alleviation of the tension dominantly originates from the late-time expansion rather than early-universe effects. We conclude that $Λ_s$CDM constitutes a phenomenologically viable interacting dark sector framework that addresses key cosmological tensions while remaining consistent with current precision data. }

Diversity and multiplexing are the two fundamental gains of multiple-input and multiple-output (MIMO) communications, enabling systems to simultaneously achieve increased reliability and higher data rates. The intricate interplay between these two metrics is captured by the celebrated diversity-multiplexing tradeoff (DMT). With the rapid evolution of wireless technologies, low-latency integrated sensing and communication (ISAC) has emerged as a key enabler for 6G applications, including extended reality (XR) and massive digital twins. Consequently, understanding the DMT within MIMO ISAC systems becomes critical. In this paper, we investigate the communication DMT in a mono-static MIMO ISAC system under Rayleigh fading, specifically when the transmitter is constrained to emit sensing-optimal waveforms. By unveiling the geometric properties of generalized Stiefel manifolds and employing large-deviation analysis, we characterize the asymptotic outage probability of this typical ISAC channel. This formulation yields an elegant converse bound on the sensing-constrained DMT. Ultimately, our work provides an answer to a pivotal unanswered question in ISAC system design: How much MIMO gain is fundamentally sacrificed in communication to integrate optimal sensing capabilities?

We study the nonresonance phenomenon for complex rank-one local systems on complements of hyperplane arrangements. We refine the method of Cohen, Dimca, and Orlik and obtain a combinatorial sufficient condition for nonresonance. As an application, we strengthen a theorem of Bailet, Dimca, and Yoshinaga by removing one of its conditions. We also develop restriction and lifting techniques to prove a nonresonance theorem for line arrangements.

We develop a stochastic game-theoretic model for intraday dispatch of grid-scale battery energy storage systems (BESSs). We assume that each BESS operator competitively manages her state-of-charge to maximize energy arbitrage revenues, driven by the endogenized electricity price that depends on the sum of the charging rates. We characterize the Nash equilibrium of the resulting finite-player linear-quadratic differential game with a shared stochastic driver, obtaining semi-explicit representations of equilibrium feedback controls and equilibrium prices both in the general heterogeneous and the simplified homogeneous BESS setting, via a system of Riccati equations. We then analyze competitive effects, including the marginal externality of additional BESS entering the market, the benefit of coordination and the corresponding market power of large operators, and supply effects from hybrid-type BESSs. We further study the asymptotic regime as the number of agents grows large. Our model provides a quantitative testbed to study the impact of decentralized BESS deployment on the grid and the resulting reduction in daily price spreads.

The synergy of non-Hermitian and topology renders the bulk-boundary correspondence (BBC) even more elusive. Here we study a non-Hermitian Creutz ladder that incorporates both gain-loss and nonreciprocity, and construct multiple BBCs involving scale-free, normal and anomalous skin modes, as well as topological zero-energy modes. In the presence of spatial inversion (P) symmetry, the parity-time (PT) phase transition is characterized by an average winding number,whereas a hidden chiral symmetry guarantees that topological phase transitions can be detected via a Z 2 invariant. The gain-loss breaks the P symmetry but preserves the combined PT symmetry, and then the previous BBC version only requires minor modifications. Intriguingly, sublattice symmetry enables the precise calculation of non-Bloch spectra, based on which a hybrid spectral winding can encode the localization (or delocalization) information of two counterintuitive bulk modes that coexist with normal skin modes. One type exhibits exponential boundary accumulation in the opposite direction to nonreciprocity. The other exemplifies a surge of Bloch-wave states in nonreciprocal lattices. These results reveal a series of unexpected phenomena governed by symmetry, thereby expanding our fundamental understanding of the BBC mechanism in non-Hermitian topological systems.

It is usually assumed that a healthy EFT should not allow superluminal propagation. In the presence of gravity, however, the notion of superluminality becomes subtle, since there is no invariant way to compare with an underlying Minkowski light cone. One can instead resort to an asymptotic criterion: whether the EFT can induce signal propagation faster than what allowed by the asymptotic structure of spacetime. In this work we study the asymptotic causal structure of gravitational EFTs by analysing signal propagation in black-hole backgrounds in the presence of higher-derivative operators. We show that in spacetime dimensions D>4 the effective light cones can lead to genuine asymptotic superluminality, which can be used to constrain the regime of validity of the EFT. By contrast, in D=4 the asymptotic causal structure is universally identical to that of Schwarzschild: prompt null curves remain insensitive to higher-derivative corrections and no asymptotic time advance is possible. We first study the representative operator $R_{μνρσ}F^{μν}F^{ρσ}$, then show that this conclusion is true for any EFT, as it relies only on the asymptotic behaviour of the metric. Finally, we discuss two ways to define superluminality in D=4 spacetimes: introducing a covariant cut-off by putting the theory in an asymptotically-AdS background, or imposing a hard cut-off by working at finite distance.

Degenerate quantum eigenspaces can support substantial changes in nodal geometry at fixed energy. We show that, for the two-dimensional isotropic harmonic oscillator, this restructuring is organized by the Hermite-constrained algebraic curve \(P_N(x,y)=0\) associated with each real shell state, $ψ_N(x,y)=e^{-αr^2/2}P_N(x,y)$. Finite singularities, \(P_N=\nabla P_N=0\), together with projective degeneracies of the leading homogeneous part, identify the strata where topology-changing events can occur. We combine these algebraic criteria with three information diagnostics: the nodal-domain entropy \(S_{\rm dom}\), the Cartesian mutual information \(I(x;y)\), and the entropic uncertainty sum \(S_r+S_p\). The first three shells reveal a clear hierarchy. The \(N=1\) shell only rotates a nodal line; the \(N=2\) shell exhibits a conic transition at \(b^2=2ac\), sharply detected by \(S_{\rm dom}\) but not by global entropies; and the \(N=3\) shell supports cubic close-branch regimes organized by the projective discriminant, with enhanced responses in \(S_{\rm dom}\) and \(I(x;y)\). Thus algebraic stratification, rather than spectral ordering, organizes nodal geometry inside a degenerate eigenspace, while entropy diagnostics quantify the associated probability redistribution and coordinate correlations. The same stratification defines experimentally testable signatures in real-phase Hermite--Gaussian structured light and approximately isotropic trapped motional systems, and suggests a geometry-sensitive verification primitive for fixed-shell bosonic-qudit gates.

This work investigates minimal parametric networks in hyperspaces of closed subsets of metric spaces endowed with the Hausdorff distance. It is shown that the problems of finding such networks are nontrivial only within finiteness classes, where all Hausdorff distances between elements are finite. It is demonstrated that when studying the properties of minimal parametric networks, it is convenient to view their interior vertices as solutions of the Fermat--Steiner problem on the adjacent vertices. In this connection, already within the framework of the Fermat--Steiner problem, the structure of solution classes in hyperspaces of closed subsets of metric spaces is described. Results on the existence of $d$-far points in the case of convex boundary sets are also generalized. Namely, conditions are shown under which realizing one-sided Hausdorff distances holds.

Cygnus X-3 is a microquasar composed of a compact object of unknown nature closely orbiting around a Wolf-Rayet star. The particularities of this source make it a unique case among microquasars. This fact, together with its recent establishment as a PeV particle accelerator, makes Cygnus X-3 a very interesting target for the investigation of the physical processes leading to gamma-ray production. In this work, the TeV and GeV gamma-ray emission of Cygnus X-3 is studied in order to determine its origin and constrain the properties of the system. For that purpose, a point-like analysis of 130 h of data taken with the MAGIC telescopes between 2013 and 2024 was performed, which represents the largest available sample for Cygnus X-3 at $\sim$TeV energies. Additionally, contemporary data from Fermi-LAT were also analysed to better contextualize the MAGIC observations. For a more detailed investigation of the source physics, the data were divided into three subsets according to the flaring state of the source and orbital phase. No significant detection of Cygnus X-3 is found between 0.1 and 7 TeV for any of the datasets, and differential and integral flux upper limits are reported over the long-term monitoring of the source. The Fermi-LAT fluxes can be considered compatible with previous results, taking into account the different data samples used across studies. The MAGIC upper limits presented in this work represent the most constraining ones up to date at $\sim$TeV energies. An eventual detection of Cygnus X-3 at these energies would significantly constrain the source properties, and is not unreasonable to expect given that the source has already been detected in both the GeV and PeV regimes during flaring states. Further observations of Cygnus X-3 at energies above tens of GeV would be valuable for this purpose.

In this paper, we study the geometry of bounded domains with piecewise smooth boundary. Specifically, we obtain the relationship between the squeezing function corresponding to polydisk and Levi flatness on bounded generic convex domains. As an application, we prove that a two dimensional bounded generic convex domain with piecewise $C^2$-smooth boundary that admits a finite volume quotient is biholomorphic to bidisk. Moreover, we show that any Teichm$\ddot{\operatorname{u}}$ller space $\mathcal{T}_g$ with $g\geq2$ can not be biholomorphic to a bounded generic domain with piecewise $C^2$-smooth boundary.

Mesogenesis provides a path for generating the baryon asymmetry of the Universe, using only the CP violation furnished by the Standard Model in the decay of $B$ mesons. While this is an intriguing possibility, it is largely constrained by the data on $B$ meson branching fractions into baryons and missing energy carried into the dark sector. We point out that it is possible to make this branching fraction dominant only in the early Universe, through an ultralight scalar coupled to the dark sector and the Standard Model leptons. A scenario is examined where the thermal density of muons in the early Universe temporarily lowers the mass of a dark fermion, allowing for efficient $B$ meson decays. This `dark' decay channel is shut off later when the muon number density falls, making the scenario compatible with flavor data. Our model can be consistent with the LHC constraints on color-charged heavy bosons required to implement Mesogenesis; such states may be discovered in the future runs as their masses cannot be far above the current bounds. We also outline other possible signals, which can arise in future displaced vertex searches, long range force searches, and observations of neutron star binary mergers.

The first evidence for the decay $B^+\toπ^+ e^+ e^-$ is reported using proton-proton collision data recorded by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb$^{-1}$. A signal excess with a significance of 3.2$σ$ is observed and the branching fraction is measured to be $\cal{BR}(B^+\toπ^+ e^+ e^-) = (2.4\,{}^{+0.9}_{-0.8} \,{}^{+0.4}_{-0.2}) \times 10^{-8}$, where the first set of uncertainties is statistical and the second is systematic. The result is consistent with the Standard Model expectation.

We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractors, which are extractors that remain sound even when a small number of points violate the min-entropy constraint. Using such objects, we show that for a broad range of sampling models (e.g., low-depth circuits, small-space sources, etc.), every output of the model has distance $1 - o(1)$ from our target distribution, qualitatively recovering essentially all previously known hardness results. Our work extends that of Viola (SICOMP '14), who developed an earlier unified framework based on traditional extractors to rule out sampling with very small error. As a further application of our technique, we leverage a recent extractor construction of Chattopadhyay, Goodman, and Gurumukhani (ITCS '24) to present the first explicit distribution with distance $1 - o(1)$ from the output of any low-degree $\mathbb{F}_2$-polynomial source. We note that a similar bound was obtained concurrently and independently by Khodabandeh and Shinkar (ECCC '26). We also describe a potential avenue toward proving a similar hardness result for $\mathsf{AC^0}[\oplus]$ circuits.

Lifetime prediction of reactor pressure vessel (RPV) steel requires bridging atomistic degradation mechanisms with service-scale spatial and temporal regimes, from Angstroms and picoseconds to meters and decades. Existing engineering-scale models provide long-range reach but rely on fitted degradation laws, while recent atomistic kinetic Monte Carlo (AKMC) advances still fail to achieve year-and-meter-scale coverage. We present AtomWorld, an atomistic world-modeling framework for RPV steel lifetime simulation co-designed with leadership-scale supercomputing through three tightly coupled layers: (1) algorithm: AtomWorld recasts classical AKMC as an atomistic world model that learns consequence-aware state transitions over the ab initio energy landscape; (2) HPC: it co-designs this formulation with modern supercomputers, yielding a compute-dense, synchronization-light, and communication-efficient execution pipeline; and (3) application: it extends atomistic world modeling to engineering-scale simulation through a physically grounded voxel-parallel framework, offering a scalable pathway from local atomistic dynamics to engineering-scale degradation evolution. We demonstrate a paradigm shift in atomistic simulation: AtomWorld enables atomistic simulation of RPV steel across year-and-meter scales for the first time, extending direct atomistic modeling to ten-quintillion-atom systems and achieving a time-to-solution of 1.71 days for one simulated service year. These capabilities are sustained across five leadership supercomputers with 92-97% scaling efficiency and peak performance up to 1.27 EFLOP/s, corresponding to 48% of the Lineshine peak FP64 performance.

Current global precipitation estimates from spaceborne precipitation radars are limited by their sensitivity to light and frozen precipitation, leading to systematic underestimation of precipitation at high latitudes. Because passive microwave retrievals (PMW) are commonly trained using these radar observations as reference data, this limitation is propagated into PMW This study introduces a novel PMW oceanic precipitation retrieval, GPROF-NN eXtended Precipitation Regime (XPR), that combines reference estimates from a cloud radar and a precipitation radar to overcome the sensitivity limitations of current spaceborne precipitation radars. The retrieval is trained to estimate light precipitation from CloudSat observations and moderate-to-heavy precipitation using observations from the GPM Dual-Frequency Precipitation Radar. The two estimates are combined using a fusion scheme to obtain a consistent precipitation estimate across precipitation regimes. Validation against in situ measurements from shipborne disdrometers shows a 26% improvement in the detection skill for high-latitude precipitation in terms of the critical success index and a reduction in the underestimation of high-latitude and frozen precipitation by more than 50% compared to retrievals constrained only by precipitation radar data. However, the fused retrieval does not improve the precision of instantaneous precipitation estimates, which is likely due to significant random errors in the CloudSat-based reference estimates of liquid precipitation. These results demonstrate that PMW retrievals can leverage the complementary sensitivities of cloud and precipitation radars to provide more consistent precipitation estimates across precipitation regimes than either reference instrument alone. The proposed retrieval provides a pathway to improve the representation of oceanic precipitation in future GPM precipitation products.

We investigate the effective photon geometry associated with black holes in Kruglov nonlinear electrodynamics and its consequences for strong-field optical phenomena. This model constitutes a one-parameter generalization of Born-Infeld electrodynamics, interpolating between Maxwell theory and exponential electrodynamics through the parameter $q$. For a wide range of $q$, the spacetime geometry outside the event horizon remains close to the Reissner-Nordström solution, while photon propagation is governed by an effective geometry that depends sensitively on the nonlinear electrodynamics sector. We study the corresponding null geodesic structure through fully numerical calculations, focusing on photon spheres, light deflection, black hole shadows, and accretion-disk images. The effective geometry shows qualitatively distinct features depending on $q$. In particular, sufficiently small positive values of $q$ generate stable photon orbits outside the event horizon, together with significant modifications to the range of impact parameters supporting multiple photon trajectories. These effects produce observable modifications in the relativistic images, including systematic variations in the effective geometry. We also analyze the black hole shadow in relation to current horizon-scale constraints on Sgr~A*. Our results demonstrate that nonlinear electrodynamics can substantially modify photon propagation and relativistic image formation even when the underlying spacetime gometry remains close to the Maxwell electrodynamics case.

Preprints are essential for the timely and open dissemination of research. arXiv, the most widely used preprint service, takes the idea of open science one step further by not only publishing the actual preprints but also LaTeX sources and other files used to create them. As known from other contexts, such as GitHub repositories, and anecdotally exemplified for arXiv, making source code publicly available risks disclosing otherwise "hidden" information. Consequently, the public availability of paper sources raises the question of how much sensitive content is (unintentionally) disclosed through them. In this paper, we systematically answer this question for all 2.7M arXiv submissions with available source files across three dimensions of source file-induced information disclosure: (1) inclusion of unnecessary files, (2) metadata embedded in files, and (3) irrelevant content in files such as source code comments. Our analysis reveals that nearly every arXiv submission contains some form of "hidden" information. Notable findings range from links to editable web documents for internal coordination over API and private keys to complete Git histories. While different tools promise to remove such information from source files, we show that they fail to reliably achieve the intended cleaning functionality. To mitigate this situation, we provide ALC-NG to comprehensively remove files, metadata, and comments that are not needed to compile a LaTeX paper.

To advance from passive retrieval to creative discovery of new ideas, autonomous agents must be capable of deep, associative synthesis. However, current agentic frameworks prioritize convergent search, often resulting in derivative summaries that lack creativity. Caesar is an agentic architecture designed to bridge the gap between information gathering and synthesis of new insights. Unlike existing agents that treat the web as a flat sequence of disconnected documents, Caesar performs a deep web traversal to construct a dynamic knowledge graph. This graph then serves as a navigational scaffold, guiding the agent to diverse, non-obvious information that flat retrieval would never encounter. Caesar thus consists of two components: (1) exploration driven by a dynamic context-aware policy that maximizes information coverage across the web's topological structure, and (2) synthesis through adversarial refinement that actively seeks novel perspectives rather than confirming established priors. Caesar demonstrates the ability to generate artifacts and answers characterized by high novelty and structural coherence, achieving 13% to 23% improvement over state-of-the-art deep research agents in creative synthesis challenges, with strong dominance across all output formats.

The movable antenna (MA) technology enables flexible reconfiguration of wireless channels through adaptive antenna deployment, offering significant potential for enhancing communication performance. However, antenna movement requires a certain duration within which communication may be compromised due to factors such as channel fluctuation and Doppler effect. This leads to a fundamental tradeoff: A longer movement duration allows antennas to reach more favorable positions for better channel conditions, but it inevitably reduces the time available for data transmission. To characterize the aforementioned tradeoff, we focus on the MAs-enabled multiuser downlink scenario, and jointly optimize the movement duration and antenna deployment at the base station to maximize the effective throughput. The formulated problem is highly non-convex. The general solutions require an one-dimensional search over movement durations, each with optimized antenna deployment. To reduce complexity, we propose a fitting method that samples only a few rate-duration pairs, yielding a closed-form expression that captures the rate trend and enables a favorable solution immediately. We further derive a closed-form condition on the maximum antenna movement speed: When the speed is below a certain threshold, the optimal strategy is to keep antennas stationary throughout the transmission period. The fundamental tradeoff and the effectiveness of the proposed solutions are examined in a special case with two MAs and two users. Finally, numerical simulations validate the efficacy of the proposed schemes.