Agents operating in complex software environments benefit from reasoning about the consequences of their actions, as even a single incorrect user interface (UI) operation can derail long, artifact-preserving workflows. This challenge is particularly acute for computer-using scenarios, where real execution does not support counterfactual exploration, making large-scale trial-and-error learning and planning impractical despite the environment being fully digital and deterministic. We introduce the Computer-Using World Model (CUWM), a world model for desktop software that predicts the next UI state given the current state and a candidate action. CUWM adopts a two-stage factorization of UI dynamics: it first predicts a textual description of agent-relevant state changes, and then realizes these changes visually to synthesize the next screenshot. CUWM is trained on offline UI transitions collected from agents interacting with real Microsoft Office applications, and further refined with a lightweight reinforcement learning stage that aligns textual transition predictions with the structural requirements of computer-using environments. We evaluate CUWM via test-time action search, where a frozen agent uses the world model to simulate and compare candidate actions before execution. Across a range of Office tasks, world-model-guided test-time scaling improves decision quality and execution robustness.

Chiral phonons have been identified in several chiral crystals, primarily in those with trigonal symmetry and threefold screw axes. In this study, chiral phonons in CrSi$_2$, a chiral crystal with a sixfold helical structure, were investigated. Circularly polarized Raman spectroscopy revealed a subtle splitting of doubly degenerate $E_2$ phonon modes between cross-circular polarization configurations. These observations, supported by first-principles phonon calculations, indicate the presence of chiral phonons in CrSi$_2$, expanding the scope of materials that exhibit chiral vibrational modes beyond the conventional trigonal class.

Herd immunity is shaped not only by the infection capacity of a spreading epidemic or the contact structure of the hosting population, but also by how and under what circumstances individuals acquire immunity. Immunization strategies may interact with ongoing non-pharmaceutical interventions, which commonly aim to reduce social contact numbers. We demonstrate that these interactions can induce unexpectedly strong and counterintuitive effects on herd immunity. We explore these phenomena on spatially embedded contact networks and uncover a reversal in the relative effectiveness of disease- versus vaccine-induced immunization schemes, highlighting the average number of contacts as a critical determinant of emerging herd immunity. In sparse geometric networks with limited degree heterogeneity, uniform vaccination proves most effective; however, as average contact numbers increase, naturally acquired immunity ultimately becomes the better strategy. We show that this phenomenon may emerge not only in synthetic networks but also in real-world mixing networks, observed during non-pharmaceutical intervention periods across multiple states of the United States.

Prophet inequalities compare online stopping strategies against an omniscient "prophet" using distributional knowledge. In this work, we augment this model with a conservative prediction of the maximum realized value. We quantify the quality of this prediction using a parameter $α\in [0,1]$, ranging from inaccurate to perfect. Our goal is to improve performance when predictions are accurate (consistency) while maintaining theoretical guarantees when they are not (robustness). We propose a threshold-based strategy oblivious to $α$ (i.e., with $α$ unknown to the algorithm) that matches the classic competitive ratio of $1/2$ at $α=0$ and improves smoothly to $3/4$ at $α=1$. We further prove that simultaneously achieving better than $3/4$ at $α=1$ while maintaining $1/2$ at $α=0$ is impossible. Finally, when $α$ is known in advance, we present a strategy achieving a tight competitive ratio of $\frac{1}{2-α}$.

This paper argues that existing global AI safety frameworks exhibit contextual blindness towards India's unique socio-technical landscape. With a population of 1.5 billion and a massive informal economy, India's AI integration faces specific challenges such as caste-based discrimination, linguistic exclusion of vernacular speakers, and infrastructure failures in low-connectivity rural zones, that are frequently overlooked by Western, market-centric narratives. We introduce ASTRA, an empirically grounded AI Safety Risk Database designed to categorize risks through a bottom-up, inductive process. Unlike general taxonomies, ASTRA defines AI Safety Risks specifically as hazards stemming from design flaws such as skewed training sets or lack of guardrails that can be mitigated through technical iteration or architectural changes. This framework employs a tripartite causal taxonomy to evaluate risks based on their implementation timing (development, deployment, or usage), the responsible entity (the system or the user), and the nature of the intent (unintentional vs. intentional). Central to the research is a domain-agnostic ontology that organizes 37 leaf-level risk classes into two primary meta-categories: Social Risks and Frontier/Socio-Structural Risks. By focusing initial efforts on the Education and Financial Lending sectors, the paper establishes a scalable foundation for a "living" regulatory utility intended to evolve alongside India's expanding AI ecosystem.

In this article, we define the Chern-Robinson connection on the complexify tangent bundle of an almost Robinson manifold and we study the curvature associated to. Various Bianchi identities are obtained together with an application to geometry of some Robinson manifolds.

Multimodal recommender systems (RSs) represent items in the catalog through multimodal data (e.g., product images and descriptions) that, in some cases, might be noisy or (even worse) missing. In those scenarios, the common practice is to drop items with missing modalities and train the multimodal RSs on a subsample of the original dataset. To date, the problem of missing modalities in multimodal recommendation has still received limited attention in the literature, lacking a precise formalisation as done with missing information in traditional machine learning. In this work, we first provide a problem formalisation for missing modalities in multimodal recommendation. Second, by leveraging the user-item graph structure, we re-cast the problem of missing multimodal information as a problem of graph features interpolation on the item-item co-purchase graph. On this basis, we propose four training-free approaches that propagate the available multimodal features throughout the item-item graph to impute the missing features. Extensive experiments on popular multimodal recommendation datasets demonstrate that our solutions can be seamlessly plugged into any existing multimodal RS and benchmarking framework while still preserving (or even widen) the performance gap between multimodal and traditional RSs. Moreover, we show that our graph-based techniques can perform better than traditional imputations in machine learning under different missing modalities settings. Finally, we analyse (for the first time in multimodal RSs) how feature homophily calculated on the item-item graph can influence our graph-based imputations.

Moiré semiconductors built on angle-aligned transition metal dichalcogenide (TMD) heterobilayers provide a physical realization of the Kondo lattice model, in which one TMD layer is prepared in a Mott insulating state supporting a lattice of local magnetic moments and the other layer in a metallic state supporting itinerant carriers. The artificial Kondo lattice enables the exploration of exotic states of matter near a continuously tunable Kondo breakdown. Here we report the emergence of a symmetry-broken Chern insulator at a moiré hole filling factor 4/3 in angle-aligned MoTe2/WSe2 moiré bilayers, which realize a chiral Kondo lattice. The symmetry-broken Chern insulator, which exhibits integer quantized Hall conductance at a fractional moiré filling, breaks the translational symmetry of the lattice spontaneously; it also appears only near a magnetic field-induced Kondo breakdown in the mixed-valence regime of the material. We further demonstrate that the magnetic field required to induce the Kondo breakdown and to stabilize the symmetry-broken Chern insulator is twist angle dependent. The results present new opportunities for exploring the subtle interplay between topology and Kondo interactions in moiré semiconductors.

We present and study an explicit exponential integrator for parabolic SPDEs in any dimension driven by a Gaussian noise which is white in time and with spatial correlation given by a Riesz kernel. Under assumptions on the coefficients of the SPDE, we prove strong error bounds and exhibit how the rate of convergence depends on the exponent in the Riesz kernel. Finally, numerical experiments in spatial dimensions $1$ and $2$ are provided in order to confirm our convergence results.

We investigate the connection between left exact $\infty$-functors between finitely complete quasicategories and exact functors between fibration categories, describing a procedure to approximate flat $\infty$-functors of the former type by exact functors of the latter type. As an application, we recover a proof of the DK-equivalence between the relative category of fibration categories and that of finitely complete quasicategories.

In dynamically formed binaries, the spins of the black holes tend to be misaligned with the system's orbital angular momentum. This causes the spins to precess and leads to an asymmetric emission of gravitational waves. The resulting gravitational-wave multipole asymmetries directly source the recoil of the remnant black hole and are the critical element in fully describing precession. Recoil and precession are of significant astrophysical importance, but multipole asymmetries contribute only minimally to the overall signal strength. Consequently, most current gravitational-wave models either do not incorporate asymmetries at all, or only consider the dominant ones. Here we highlight the importance of subdominant multipole asymmetries for an accurate recoil velocity calculation and discuss their detectability with third generation detectors. Neglecting subdominant asymmetries leads to velocity differences of up to 210 km/s and can, in particular, introduce systematic biases in the inference of masses and the spin geometry. We further discuss universal characteristics of subdominant multipole asymmetries in order to prepare the ground for potential future asymmetry models. In the inspiral regime, the average antisymmetric frequencies can be described by a multiple of the orbital frequency. During ringdown, however, they become equal to their corresponding symmetric frequencies.

The characterization of collective behavior and nonequilibrium phase transitions in quantum systems is typically rooted in the analysis of suitable system observables, so-called order parameters. These observables might not be known a priori, but they may in principle be identified through analyzing the quantum state of the system. Experimentally, this can be particularly demanding as estimating quantum states and expectation values of quantum observables requires a large number of projective measurements. However, open quantum systems can be probed in situ by monitoring their output, e.g. via heterodyne-detection or photon-counting experiments, which provide space-time resolved information about their dynamics. Building on this, we present a machine-learning approach to detect nonequilibrium phase transitions from the measurement time-records of continuously-monitored quantum systems. We benchmark our method using the quantum contact process, a model featuring an absorbing-state phase transition, which constitutes a particularly challenging test case for the quantum simulation of nonequilibrium processes.

LLM-assisted writing has seen rapid adoption in interpersonal communication, yet current systems often fail to capture the subtle tones essential for effectiveness. Email writing exemplifies this challenge: effective messages require careful alignment with intent, relationship, and context beyond mere fluency. Through formative studies, we identified three key challenges: articulating nuanced communicative intent, making modifications at multiple levels of granularity, and reusing effective tone strategies across messages. We developed PersonaMail, a system that addresses these gaps through structured communication factor exploration, granular editing controls, and adaptive reuse of successful strategies. Our evaluation compared PersonaMail against standard LLM interfaces, and showed improved efficiency in both immediate and repeated use, alongside higher user satisfaction. We contribute design implications for AI-assisted communication systems that prioritize interpersonal nuance over generic text generation.

We investigate the stochastic homogenization of a class of turbulent diffusions generated by non-local symmetric Lévy operators with divergence-free drift fields in ergodic random environments, where neither the drift fields nor their associated stream functions are assumed to be bounded. A pivotal step in our proof is the establishment of $W_{loc}^{1,q}$ estimates with $q\in (1,2)$ for the corresponding correctors, under mild prior regularity conditions imposed on the Lévy measure and the stream function.

The technique of symmetric extensions is derived from forcing and it is one of the most important tools for studying models without the Axiom of Choice. Despite being incredibly successful since the 1960s, our understanding of the technique remained fairly limited compared to the theory of forcing. Whereas forcing developed products and iterations, no serious attempts at developing any general framework for iterating symmetric extensions were presented before [10], where only finite support iterations are treated. In this paper we develop the theory of symmetric extensions including different types of iterations, quotients, equivalents, and the structural results that can be described in this language. In particular, we give a modern exposition to some of the important theorems of Grigorieff [3], study Kinna--Wagner Principles in symmetric extensions, and show that it is provable from $\mathsf{ZF}$ that every set lies in a symmetric extension of $\operatorname{HOD}$.

We investigate the algebraic genericity of various families of continuous functions exhibiting extreme irregularity, focusing on fractal dimensions, Hölder regularity, and fractional differentiability. Our first main result shows that for every $s \in (1,s]$, the set of continuous functions on $[0, 1]$ whose graph has Hausdorff and box dimensions equal to s is strongly $\mathfrak{c}$-algebrable, thereby tackling an open question by Bonilla et al., and complementing recent findings by Liu et. al and Carmona et al. We then extend the analysis to Hölder spaces: although the pointwise Hölder exponent of a generic function in $C^α[0, 1]$ is constant, we prove that the collection of functions realizing this behavior is $\mathfrak{c}$-lineable but cannot form an algebra. Nevertheless, we construct strongly $\mathfrak{c}$-algebrable families of functions that exhibit Hölder exponent $α$ outside a set of Hausdorff dimension zero. Finally, as a consequence of the relation between strongly monoHölder functions and fractional differentiability, we analyze the strong $\mathfrak{c}$-algebrability of nowhere (Riemann-Liouville) fractional differentiable functions.

In the present survey, we consider the classical reinforcement problem for elliptic boundary value problems originally studied by Sanchez-Palencia in 1969. We focus on the seminar papers by Brezis, Caffarelli, & Friedman, and by Acerbi & Buttazzo, and discuss the related optimisation problems proposed by Friedman and by Buttazzo.

We investigate the detection and nature of 5.6~μm MIRI-red sources in the MIRI Deep Imaging Survey (MIDIS), covering 2.4~arcmin$^2$ in the Hubble Ultra Deep Field. MIDIS is the deepest JWST/MIRI survey to date, probing faint limits and enabling studies of rare high-redshift galaxy populations. We define MIRI-red sources as those detected at 5$σ$ significance in MIRI/F560W with red colors: $m_{\rm F444W} - m_{\rm F560W} \ge 0.5$. Using an empirical methodology, we estimate the purity and completeness of MIRI detections and find that a 5-sigma detection at 28.75 mag has a purity of 92\% and completeness of 54\%. We identify seven MIRI-red galaxy candidates, including an F115W dropout consistent with a high-redshift galaxy candidate. We explore possible physical origins for the MIRI-red population, including active galactic nuclei, dust-obscured galaxies, extreme emission-line galaxies, evolved stellar populations, and Little Red Dots (LRDs). Given the proximity of the F444W and F560W filters and the depth of MIDIS, MIRI-red galaxies are consistent with emission-line galaxies with $EW_0(Hα) \ge 750$ Å or $EW_0(Hβ+ [OIII]) \ge 600$ Å, or high-redshift Balmer breaks of at least 1.6. We also discuss an extreme MIRI-red galaxy undetected in F444W, a potential MIRI-only source, for which we derive $EW_0(Hα) \sim 6000$ Å and $EW_0(Hβ+ [OIII]) \sim 4000$ Å, or high-$z$ LRD analogs with Balmer breaks of 6.3. Finally, we find fewer MIRI-red detections than expected from extrapolations of the H$α$ or H$β$+[OIII] line luminosity functions, consistent with previous deep searches, while the absence of $z>10$ LRD candidates agrees with theoretical expectations for the MIDIS volume.

This paper investigates the conditions under which the centralizer algebra $S_n(c,R)$ of a matrix $ c\in M_n(R)$ is a (separable) Frobenius extension of the base algebra $R$. For an algebra $R$ over an integral domain $\mathbb{k}$, we provide necessary and sufficient conditions for $S_n(c,R)/R$ to be a (separable) Frobenius extension when $c$ is in Jordan canonical form with eigenvalues in $\mathbb{k}$. We extend this analysis to arbitrary matrices over a field and derive conditions for matrix diagonalizability through Frobenius extensions.

Absolute cross sections for the formation of OH- from 2-propanol (CH3CH(OH)CH3) via dissociative electron attachment (DEA) are reported in the incident electron energy range of 3.5-13 eV. Four fragment anions are observed: OH-, C2H2O-, C2H4O-, and C3H7O-. The OH- yield exhibits a pronounced resonance centered at 8.2 eV together with a broader structure extending over the 8-10 eV region. Equation-of-Motion Coupled-Cluster (electron attached) calculations with Singles and Doubles combined with a Complex Absorbing Potential (CAP/EOM-EA-CCSD) assign this feature to a two-particle-one-hole (2p-1h) core-excited Feshbach resonance. Potential energy curves along the C-OH dissociation coordinate reveal that core-excited anion states in this energy range promote efficient cleavage of the hydroxyl group. Analysis of Dyson orbitals and resonance widths demonstrates that only states with repulsive antibonding sigma(C-OH) character and sufficiently long lifetimes contribute significantly to the observed OH- production. These results provide fundamental insight into the DEA dynamics of secondary alcohols and highlight the role of multi-electron-attached resonances in site-specific bond rupture induced by low-energy electrons.

Understanding the interplay between magnetic ordering and light emission is crucial for developing magneto-optical technologies. However, this phenomenon is poorly understood since observations of this coupling vary significantly across materials. In this context, hybrid organic-inorganic metal halide perovskites (HOIPs) that incorporate Mn2+ ions are a chemically and structurally tunable platform for exploring this phenomenon, since they exhibit magnetic ordering and photoluminescence (PL) emission. Here, we study two antiferromagnetic Mn-based HOIPs with different organic cations that result in distinct lattice stiffness, Mn2+-Mn2+ distance and octahedral distortion. Temperature-dependent PL excitation spectroscopy reveals changes in crystal field splitting energy and Racah parameters well above the Néel temperature (TN), indicating the emergence of Mn2+-Mn2+ magnetic interactions prior to reach long-range magnetic ordering. These variations align with the observed changes in temperature-PL evolution. The compound with a more rigid lattice shows stronger changes closer to TN, suggesting combined effects of magnetic polarons and spin-canting. In contrast, magnetic polaron-induced magnetic modifications prevail in the HOIP with a softer lattice. These results reveal the complexity of the magneto-optical coupling in Mn-based HOIPs and provide new insights into this field extensible to other 2D materials that exhibit this phenomenon with potential for advanced magneto-optical applications.

Following methods used by A. Dugas for investigating derived equivalent pairs of (weakly) symmetric algebras, we apply them in a specific situation, obtaining new deep results concerning iterated mutations of symmetric periodic algebras. More specifically, for any symmetric algebra $Λ$, and an arbitrary vertex $i$ of its Gabriel quiver, one can define mutation $μ_i(Λ)$ of $Λ$ at vertex $i$ via silting mutation of the stalk complex $\La$. Then $μ_i(Λ)$ is again symmetric, and we can iterate this process. We want to understand the order of $μ_i$, in case the vertex $i$ is $d$-periodic, i.e. the simple module $S_i$ associated to $i$ is periodic of period $d$ (with respect to the syzygy). The main result of this paper shows that then $μ_i$ has order $d-2$, that is $μ_i^{d-2}(Λ)\congΛ$ (modulo socle), under some additional assumption on the (periodic) projective-injective resolution of $S_i$. Besides, we present briefly some consequences concerning arbitrary periodic vertex and give few sugestive examples showing that this property should hold in general, i.e. without restrictions on the periodic projective resolution.

Quantum computing has gained significant attention due to its potential to solve computational problems beyond the capabilities of classical computers. With major corporations and academic institutions investing in quantum hardware and software, there has been a rise in the development of quantum-enabled systems, particularly within open-source communities. However, despite the promising nature of quantum technologies, these communities face critical socio-technical challenges, including the emergence of socio-technical anti-patterns known as community smells. These anti-patterns, prevalent in open-source environments, have the potential to negatively impact both product quality and community health by introducing technical debt and amplifying architectural and code smells. Despite the importance of these socio-technical factors, there remains a scarcity of research investigating their influence within quantum open-source communities. This work aims to address this gap by providing a first step in analyzing the socio-technical well-being of quantum communities through a cross-sectional study. By understanding the socio-technical dynamics at play, it is expected that foundational knowledge can be established to mitigate the risks associated with community smells and ensure the long-term sustainability of open-source quantum initiatives.

We consider weighted geodesic random walks in a complete Riemannian manifold $(M,g)$. We show that for almost all sequences of weights (with respect to a suitable measure), these weighted geodesic random walks satisfy, when suitably scaled, a large deviation principle with a universal rate function. This extends the results from [3], where this was shown for the real-valued case. It turns out the argument is also valid for general vector spaces. This allows us to use the methodology of [9], in which large deviations for geodesic random walks are obtained from large deviation estimates for associated random walks in tangent spaces.

Optimizing resource utilization in high-performance computing (HPC) clusters is essential for maximizing both system efficiency and user satisfaction. However, traditional rigid job scheduling often results in underutilized resources and increased job waiting times. This work evaluates the benefits of resource elasticity, where the job scheduler dynamically adjusts the resource allocation of malleable jobs at runtime. Using real workload traces from the Cori, Eagle, and Theta supercomputers, we simulate varying proportions (0-100%) of malleable jobs with the ElastiSim software. We evaluate five job scheduling strategies, including a novel one that maintains malleable jobs at their preferred resource allocation when possible. Results show that, compared to fully rigid workloads, malleable jobs yield significant improvements across all key metrics. Considering the best-performing scheduling strategy for each supercomputer, job turnaround times decrease by 37-67%, job makespan by 16-65%, job wait times by 73-99%, and node utilization improves by 5-52%. Although improvements vary, gains remain substantial even at 20% malleable jobs. This work highlights important correlations between workload characteristics (e.g., job runtimes and node requirements), malleability proportions, and scheduling strategies. These findings confirm the potential of malleability to address inefficiencies in current HPC practices and demonstrate that even limited adoption can provide substantial advantages, encouraging its integration into HPC resource management.

We consider quasilinear generalizations of the Korteweg-de Vries equation and dispersive perturbations of the Euler equations for compressible fluids, either in Lagrangian or in Eulerian coordinates. In particular, our framework includes hydrodynamic formulation of the nonlinear Schrödinger equations. The periodic waves we study exhibit on each period two pulses, one converging to a bright soliton and one converging to a dark soliton, when wavelength goes to infinity. We show that such waves, for sufficiently large periods, are spectrally unstable. To do so, we combine two approaches. The first one is to calculate the asymptotic expansion of the Hessian matrix of the action integral and concludes using arXiv:1505.01382 as in arXiv:1710.03936 . This shows instability when both limiting solitary waves are stable. The second approach studies the convergence of the spectrum when the period goes to infinity and is applied in remaining cases, when one of the solitary waves is unstable. To carry out the latter, we prove the convergence of an appropriate renormalization of the periodic Evans function as in arXiv:1802.02830 .

We review the hallmarks of orbital loop currents in various correlated electron materials and how they have been evidenced using polarized neutron diffraction. Over the last 20 years, loop current signatures have been observed in high temperature copper oxide superconductors, iridates, copper oxides spin ladders and recently kagome vanadate superconductors. Such currents induce orbital magnetic moments within the unit cell of these quantum materials that can be detected through their interaction with the neutron spin. In addition to the usual description of orbital moments using point-like local magnetic moments, we here show an alternative description of the neutron magnetic cross-section involving the microscopic currents running between different atomic orbitals. We discuss the corresponding magnetic structure factors and the resulting quantitative differences between both approaches.

A prefix code L satisfies the condition that no word of L is a proper prefix of another word of L. Recently, Ko, Han and Salomaa relaxed this condition by allowing a word of L to be a proper prefix of at most k words of L, for some `margin' k, introducing thus the class of k-prefix-free languages, as well as the similar classes of k-suffix-free and k-infix-free languages. Here we unify the definitions of these three classes of languages into one uniform definition in two ways: via the method of partial orders and via the method of transducers. Thus, for any known class of code-related languages definable via the transducer method, one gets a marginal version of that class. Building on the techniques of Ko, Han and Salomaa, we discuss the \emph{uniform} satisfaction and maximality problems for marginal classes of languages.

Quantum teleportation between polarized single-photon and phase-opposite coherent states is studied using a hybrid entangled resource and entangled coherent states. The polarized single-photon qubit represents a discrete-variable (DV) quantum system, whereas the phase-opposite coherent-state qubit constitutes a continuous-variable (CV) system. While teleportation from CV to DV can be achieved with near-unit success probability, the reverse process is usually limited to a maximum success probability of $1/2$. We demonstrate that, by employing cross-Kerr nonlinearity together with passive linear optical components such as polarizing beam splitters, beam splitters, and phase shifters, almost perfect teleportation from DV to CV encodings can also be achieved.

Consider a measure-preserving transition kernel $T$ on an arbitrary probability space $(\mathbb X,\mathcal cA,π)$. In this level of generality, we prove that a one-step hyper-contractivity estimate of the form $\|T\|_{p\to q}\le 1$ with $p< q$ implies a one-step entropy contraction estimate of the form ${\mathrm H}(μT\,|\,π)\le θ\, {\mathrm H}(μ\,|\,π)$, with $θ=p/q$. Neither reversibility, nor any sort of regularity is required. This static implication is simultaneously simpler and stronger than the celebrated dynamic relation between exponential hyper-contractivity and exponential entropy decay along continuous-time Markov semi-groups.