Skills are a key enabling component of agentic AI. While they enhance agents' capabilities, they also introduce new attack surfaces. In this work, we investigate one such attack surface by demonstrating dynamic malicious skills. By embedding malicious instructions in natural-language documentation (e.g., this http URL ), an attacker can induce an agent to dynamically inject malicious logic into an otherwise benign skill during execution. We evaluate this attack across agentic frameworks such as OpenHands and Claude Code, showing that dynamic malicious skills can successfully introduce a range of malicious behaviors at runtime with non-trivial success rates. To mitigate this vulnerability, we propose a system-level defense that prevents dynamic modification of skills using operating system kernel-enforced read-only mounts. Our evaluation demonstrates that this defense effectively blocks dynamic malicious skills while preserving the functionality of benign skills.

We study balanced subfamilies of the middle layer $\binom{[2n]}{n}$ of the Boolean lattice $2^{[2n]}$. A family $\mathcal{F}\subseteq\binom{[2n]}{n}$ is said to be balanced if every element in $[2n]$ appears in the same number of members of $\mathcal{F}$. A balanced subfamily of size 2 is exactly a complementary pair $\{A,[2n]\setminus A\}$, and therefore a family with no balanced subfamily of size $2$ has at most $\frac{1}{2}\binom{2n}{n}$ members. We show that for every $k\geq 1$ and all sufficiently large $n$, this maximum size is compatible with delaying the smallest size of a balanced subfamily until $2k+2$. More precisely, there exists a family $\mathcal{F}\subseteq\binom{[2n]}{n}$ of size $\frac{1}{2}\binom{2n}{n}$ with no balanced subfamilies of sizes $2,4,\ldots,2k$, but with a balanced subfamily of size $2k+2$. The proof is constructive and is obtained by lifting Taylor-Zwicker trade-robust magic-square games to self-dual selectors in the middle layer. This proves a recent conjecture of Moss and Pedersen.

In this paper, we introduce a new idea to study modules of logarithmic differential forms of hyperplane arrangements, which we call residue ideals. We first establish basic properties of these ideals, including their radicals and primary decompositions, and obtain applications for freeness of restrictions of arrangements. Then we apply these ideals to the study of modules of logarithmic differential $1$-forms for graphic arrangements. We give an explicit generating set for these modules and find a new connection to cover ideals of graphs studied in combinatorial commutative algebra. As a consequence we establish several new connections between arrangement theory and Stanley--Reisner theory.

Let $G=(V,E)$ be a strong biconnected graph and let $B \subseteq V$ such that for each vertex $w \in B$, the subgraph $G \setminus \lbrace w\rbrace$ is strongly connected. In this paper we study the problem of computing a subset $E_{\beta} \subseteq E$ of minimum size such that the subgraph $G_{\beta}=(V,E_{\beta})$ is strongly biconnected and for each vertex $w \in B$, the subgraph $G_{\beta} \setminus \lbrace w\rbrace$ is strongly connected. We prove that there exists a polynomial time $7$-approximation algorithm for this problem.

Asthma causes expiratory airflow limitation and is clinically assessed using spirometry, which provides the FEV1/FVC ratio representing the proportion of air exhaled in the first second relative to total forced vital capacity. Prior studies suggest that respiratory sounds recorded at posterior sites (Left Lower, Left Upper, Right Upper, Right Lower) reflect regional airflow patterns. In this study, we investigate the relationship between the expiratory-to-inspiratory (E/I) spectral power ratio and FEV1/FVC in 141 participants aged 20-60 years using Spearman correlation across frequency subbands. The 100-200 Hz and 200-400 Hz bands showed significant correlations. Overall, lower posterior sites showed stronger associations; younger adults showed stronger correlations at the Left Lower site, whereas older adults showed stronger correlations at the Left Upper site. Gender-stratified analysis showed stronger Left Lower correlations in males and stronger Left Upper correlations in females.

We introduce the notion of local pseudofunction spectrum $\sigma_{PF}(A)$ for the infinitesimal generator $A$ of a bounded $C_0$-semigroup $\mathcal{T} = (T(t))_{t \geq 0}$ on a Banach space $X$ and show it is the right spectral concept to deliver a full characterization of the strong stability of $\mathcal{T}$: $$ \forall x \in X: ~ \lim_{t \to \infty} \| T(t) x \|_X = 0 \quad \Longleftrightarrow \quad \sigma_{PF}(A) = \varnothing. $$ We demonstrate how this yields a quick proof of the well-known Arendt-Batty-Lyubich-Vũ theorem and establish novel stability results through local range density conditions for semigroups whose local pseudofunction spectra are a null subset of the imaginary axis. We also obtain similar stability characterization theorems for individual orbits and for semi-uniform stability. As an application of our results, we provide spectral characterizations of almost periodic $C_0$-semigroups with countable spectrum. In addition, we prove optimal Tauberian theorems of Katznelson-Tzafriri type and discuss connections with Wiener kernels.

The perfectly matched layer-based boundary integral equation (PML-BIE) method (Lu et al., \emph{SIAM J. Appl. Math.} 78 (2018)) has become an effective tool for wave scattering problems in unbounded domains. Despite its successful applications, a rigorous convergence theory has remained incomplete in many physically relevant settings. In this paper, we present a general framework for establishing convergence of PML-BIE methods, using acoustic scattering in an impedance half-space as the first illustrative example. The framework separates the analysis into three components: convergence of the PML truncated partial differential equation, equivalence between the PML problem and an exact PML-BIE, and convergence of a computable PML-BIE obtained by replacing the exact kernel with a stretched free-space kernel. For the impedance half-space problem, we prove convergence of both the exact and computable PML-BIE formulations. The final error bound decays exponentially as the PML absorption power increases. The resulting theory provides a rigorous foundation for the PML-BIE method and gives a reference model for more general scattering problems in layered and inhomogeneous media.

Coding agents are increasingly used to automate software engineering tasks. To guide their behavior, these agents commonly rely on configuration files, typically named " this http URL " or " this http URL ", which provide instructions about architecture, workflows, coding conventions, and testing practices. Despite their growing importance, little is known about common problems affecting the definition and maintenance of these files. In this paper, we present the first catalog of smells for coding-agent configuration files. To identify such smells, we first conducted a grey literature review and a repository mining analysis. As a result, we identified six configuration smells and proposed automated heuristics to detect them. To evaluate the prevalence of the proposed smells, we analyzed 100 popular open-source repositories containing either an " this http URL " or a " this http URL " file. Our results show that configuration smells are widespread. Lint Leakage was the most common smell, affecting 62% of the files, followed by Context Bloat (42%) and Skill Leakage (35%). We further show that several smells frequently co-occur, particularly Context Bloat, Skill Leakage, and Conflicting Instructions.

Two Scratch programs can be syntactically far apart-renamed variables, split scripts, extracted custom blocks, or reordered initialization-and still behave identically; a one-block edit, such as replacing a blocking broadcast with an asynchronous one, can create divergences visible only under specific schedules. Deciding behavioral equivalence is central to automated feedback, grading support, and repair validation, yet tree differencing is too strict and single-run dynamic comparison is unsound for concurrent, random, and timing-dependent behavior. We observe that equivalence for block-based programs is lens-parametric: final state, frame traces, monitors, event causality, and debug traces induce different observation relations. ScratchLens makes this explicit through a taxonomy of causal divergence phenomena and observation lenses. It compiles Scratch projects into a causal IR of typed resources and semantic transactions, canonicalizes renamings, guards, and procedure bodies, quotients same-trigger concurrency with Mazurkiewicz trace normal forms, separates program order from races, and handles residual frontiers through SMT obligations and VM-backed counterexample-guided refinement. Conclusive verdicts carry evidence: equivalence by bijection and trace quotient, difference by a typed witness, and unresolved cases remain unknown. On a VM-witnessed mutation corpus from real Scratch projects, ScratchLens decides all 444 validated pairs and makes 0/158 false-equivalence claims on witnessed-different pairs under strict scoring. Structural, dynamic-only, and LLM baselines fail on the classes predicted by the taxonomy; ablations quantify the contribution of partial-order reduction and lens parametricity; and targeted scenarios expose ambiguous-mutant divergences missed by random testing.

Visualizing the d-valued quantum state-space of quantum systems serves as a foundational pillar for the scientific research and practical applications in quantum computing and information science, where d >= 2. The 2-valued quantum states of a qubit are elegantly visualized on the three-dimensional Bloch sphere. In contrast, expanding this geometrical paradigm to visualize higher d-valued quantum states of a qudit (d >= 3), e.g., a qutrit (d=3), ququadit (d=4), and quintit (d=5), leads to severe structural and topological complexities. This paper introduces a new generalized three-dimensional framework to effectively visualize higher d-valued quantum states of a qudit, in the aspects of ease of illustration, structural simplicity, and natural representation for researchers and engineers. We called this new framework the "multi-axial projective sphere (MAPS)", which consists of n projectional intersecting spatial axes, where 0 <= n <= d-1. We also propose a group of novel d-valued phase axial-based gates, to swivel and shift d-valued quantum states of a qudit along these n axes. Our generalized framework could be used for visualizing high-dimensional data for practical applications, e.g., machine learning, quantum machine learning, and quantum chemistry, where every axis of the MAPS represents a single feature of such data with its corresponding distinct values.

We study families of smooth, embedded, regular planar curves $ \alpha: \left [-1,1 \right ]\times \left [0,T \right )\to \mathbb{R}^{2}$ with generalised Neumann boundary conditions inside cones, satisfying three variants of the fourth-order nonlinear curve diffusion flow: (1) curve diffusion flow with a length penalisation, (2, 3) two forms of constrained curve diffusion flow with fixed length. We prove in cases (2) and (3) for cone angle less than $\pi$, if the initial curve has small oscillation of curvature and the initial curve is sufficiently far from the cone tip, then the solution exists for all time and converges exponentially in the $C^\infty$-topology to a circular arc with the same length as the initial curve. In case (1), a similar result holds under suitable rescaling. In all cases, the limiting arc is centred at the cone tip.

We present a performance and portability evaluation of three well-established astrophysical production codes, namely iPIC3D, PLUTO, and OpenGadget3, on a Sophgo SG2044 RISC-V processor (part of the Monte Cimone cluster), with comparisons to AMD EPYC 9554 (x86) and NVIDIA GH200 Grace (ARM) systems. These applications represent memory-bound, compute-bound, and hybrid workloads, respectively. Numerical correctness is verified across all platforms, confirming portability. RISC-V shows consistently lower performance, with slowdowns of about $3-6\times$ relative to x86 and $5-9\times$ relative to ARM. The gap is mainly due to limited memory bandwidth, shared cache constraints, narrower 128-bit vector units, and lower clock frequency, but also less-mature auto-vectorization capability of the GNU compiler suite. Memory-bound kernels are the most affected, where early bandwidth saturation and L2 cache contention reduce scalability at higher thread counts. Hybrid MPI+OpenMP configurations reveal a trade-off between memory contention and communication overhead, with intermediate configurations achieving the best performance. These results suggest that RISC-V is capable of supporting scientific workloads; however, additional improvements in both hardware and compiler technology, particularly in auto-vectorization, are required to achieve competitive performance.

Periodically driven dissipative systems can settle into steady orbits - fixed loops on their dynamical manifolds. In quantum mechanics, steady orbits occur in cooling engines (used to initialise quantum devices), coherent oscillators (such as lasers and masers), precision metrology devices (atomic clocks, optical and spin magnetometers), and magnetic resonance (steady state free precession, dynamic nuclear polarisation). Steady orbits and stroboscopic steady states are a promising target for quantum optimal control, but the numerical complexity is prohibitive: the infinite loop defeats gradient ascent pulse engineering (GRAPE) which relies on explicit numerical propagation in the time domain. Here we propose an efficient quantum control strategy for stroboscopic steady states and limit cycles that are approached asymptotically when a control sequence is repeated infinitely many times. The formalism is different from Floquet-Lindblad state engineering and effective Hamiltonian theories: it finds control sequences that drive a dissipative quantum system towards a steady orbit passing through user-specified waypoints. The software implementation (same numerical complexity scaling as GRAPE) is done for the Spinach library.

We prove Gromov's Euclidean endpoint $C^0$ rigidity conjecture. Let $g$ be a smooth complete metric on $\R^3$ with non-negative scalar curvature. If $$ |g-g_{\Euc}|=o(r^{-1}),\qquad r=|x|\to\infty, $$ then $(\R^3,g)$ is isometric to Euclidean space.

The permutation flow shop scheduling problem (PFSP) is a classical NP-hard combinatorial optimization problem in intelligent manufacturing. In practice, PFSP is commonly addressed using metaheuristic algorithms, among which the iterated greedy (IG) algorithm is widely adopted due to its simplicity and strong empirical performance. However, classical IG relies on a single fixed destruction operator, which often limits exploration and leads to search stagnation on large and complex problem instances. To address this issue, this work proposes a multi-operator IG algorithm, termed IG-DOE, which enhances exploration by switching among heterogeneous destruction operators along a single search trajectory. The core mechanism, called stagnation-triggered sequential switching, activates the next destruction operator in an ordered destruction operator ensemble (DOE) when stagnation is detected, thereby enriching the perturbation behavior of classical IG. Moreover, to reduce reliance on expert-crafted operators, a large language model (LLM)-assisted framework, termed SCOE, is introduced to automatically construct a high-quality DOE through stagewise evolution, state-awareness, and cooperative evaluation. Experiments on the challenging VRF-hard-large benchmark show that the DOE evolved from smaller problem instances generalizes well to larger unseen instances. Under the same CPU-time limit, IG-DOE obtained much better average performance than QIG, a state-of-the-art IG algorithm. Additional experiments on real-world industrial-data-derived instances further show that the evolved DOE can generalize effectively to different data distributions without additional adaptation.

Warm-blooded vertebrates accumulate approximately conserved numbers of physiological cycles over a natural lifetime: of order $10^9$ heartbeats and $10^8$--$3\times10^8$ breaths. These regularities are not exact constants, but their persistence across orders-of-magnitude variation in body mass, metabolic power, physiological frequency, and lifespan suggests that biological time is not measured by chronological duration alone. We develop the Principle of Biological Time Equivalence (PBTE), a thermodynamic framework in which lifetime cycle count is determined by the ratio between total lifetime entropy production and the entropy cost of one physiological cycle. Starting from the open-system entropy balance $\dot S=\dot e_p-\dot h_d$, we define the entropy cost per cycle as $\sigma_0=d\Sigma/dN$, where $d\Sigma$ is the entropy produced as the physiological clock advances by $dN$ cycles. For an adult homeostatic regime, this gives the cycle-count relation $N_\star=\Sigma/\langle\sigma_0\rangle$, with $\Sigma=\int_0^L \dot e_p(t)\,dt$, where $N_\star$ is the lifetime cycle count, $\Sigma$ is total lifetime entropy production, and $\langle\sigma_0\rangle$ is the lifetime-averaged entropy cost per cycle. In the homeostatic limit, $\dot e_p\simeq P/T$, so direct measurement of metabolic power $P$, body temperature $T$, and physiological frequency $f$ gives $\sigma_0\simeq P/(Tf)$. PBTE converts the empirical lifetime-cycle invariants into entropy-cost invariants. Under Kleiber metabolic scaling and quarter-power physiological-frequency scaling, the mass-specific entropy cost satisfies $\bar\sigma_0=P/(TfM)\propto M^{3/4+1/4-1}=M^0$, providing a thermodynamic interpretation of allometric mass cancellation.

The polar magnetic field polarity reversal is a key signature of solar cycle evolution, and precise determination of its timing is crucial for dynamo theory validation and solar cycle prediction. We investigate the polar polarity reversal of solar cycle 25 using the vector magnetic field data from the spectropolarimeter on board the Hinode satellite. We constructed polar top-down composite maps from Hinode-view magnetograms. These maps show the year-to-year polar polarity variations, with the northern polar region gradually changing from positive to negative and the southern polar region exhibiting the reverse behavior. The polarity reversals of the northern and southern polar caps (above 70 deg latitude) likely occurred in November 2024 and October 2024, respectively. The northern polarity reversal lagged the northern hemispheric sunspot number maximum by approximately 19 months, while the southern reversal possibly coincided with the southern maximum. Moreover, polarity reversal times calculated at 5 deg latitude intervals above 70 deg reveal a trend of earlier reversal in lower latitudes consistent with that of solar cycle 24. These results offer observational references for modeling polar polarity reversal in solar cycles.

We show that every optimal transport plan for the $1$-Wasserstein distance in $\mathbb R^n$ is supported on a closed $n+1$ rectifiable set. In particular, the support of any optimal plan has Hausdorff dimension at most $n+1$.

This paper studies local controllability of nonlinear control-affine systems subject to state-dependent box constraints that strictly exclude the zero input. Such constraints arise naturally in cable-driven robots and other systems with strictly positive actuation, but fall outside classical small-time local controllability theory and existing frameworks for positive or cone-constrained controls. We introduce the admissible balancing set, an input-space object that classifies reference states without requiring the control distribution to have full rank. When an admissible balancing input lies in the interior of the input set, a locally uniform input shift recovers a symmetric-control system, allowing classical accessibility and small-time local controllability criteria to be applied. When no admissible balancing input exists, the feasible-velocity set is strictly separated from the origin. We show that the resulting separating covector defines a local barrier functional that increases at a uniform positive rate along every admissible trajectory, thereby providing a quantitative obstruction to small-time local controllability. This obstruction does not exclude finite-time reachability through trajectories leaving the barrier neighborhood, which motivates the notion of admissible excursions. The framework is illustrated on an underactuated planar cable-driven parallel robot, for which the barrier is certified numerically over a prescribed state neighborhood.

Weakest pre-expectations are the probabilistic program analogue to weakest preconditions in classical programs. Deductive verification approaches aim to establish bounds on these quantitative expectations. Their automation has been successful in analysing a variety of discrete probabilistic programs. Key routines in that automation require reasoning about (partially unrolled) loops, however, the logical representation of weakest pre-expectations on such unrollings often explodes. In this paper, we develop typed extended decision diagrams (TEDDs), inspired by various extensions to binary decision diagrams. We demonstrate computing WPs represented as TEDDs, SMT-based pruning to further shrink their representation, and we lift some proof rules to operate on TEDDs. Finally, we demonstrate that TEDDs boost the scalability of deductive probabilistic program verification by orders of magnitudes over the state of the art.

We present a discrete parametric characterization of the Mahler functional $\mathcal{V}_M$ for centrally symmetric polytopes in $\mathbb{R}^n$. By formulating the first variation of the volume with respect to the radial immersions of the vertices, we derive an exact KKT stationarity condition. Through this formalism, we demonstrate that the Hanner orbit constitutes a strict local minimum in the stratum of radial dilations modulo $GL(n, \mathbb{R})$, for all dimensions $n \ge 2$. Spectral analysis of the second variation reveals that the radial Hessian matrix is analytically equivalent to a positive semi-definite discrete Graph Laplacian. Coupling this isochoric result with a simplicial truncation analysis in the Hausdorff topology, we establish a quadratic quantitative stability bound against local polyhedral perturbations. This discrete framework eludes the degenerations of traditional smooth continuous analysis, providing an explicit algebraic resolution for the strict local minimality of this geometric configuration and its topological isolation in the subspace of polytopes.

Aims. The increasing discovery of high-redshift AGNs in recent years imposes more stringent requirements on spectral analysis tools for deriving the properties of AGNs and their host galaxies from emission-line diagnostics. To address this need, we develop a new module for the popular SED-fitting tool Code Investigating GALaxy Emission (CIGALE), the [nebular_AGN] module, which enables the efficient and flexible simulation and fitting of emission lines originating from the broad-line regions (BLRs) and narrow-line regions (NLRs) of AGNs, and allows the estimation of the physical properties of these regions. Methods. We use the spectral synthesis code Cloudy to construct the database for the new module. Based on the X-ray and accretion disk continua implemented in CIGALE, we generate the incident radiation fields of the models. We then adopt the AGN geometry and dust settings implemented in CIGALE to define a flexible set of physical parameters for the gas clouds, thereby producing a comprehensive database for the [nebular_AGN] module. Results. We benchmark the [nebular_AGN] module using a quasar composite spectrum, an empirical metallicity calibration, and observational data from X-ray-selected AGNs. Our module can approximately reproduce the majority of quasar emission-line profiles, cover the key emission-line ratios observed in AGN samples, and provide an assessment of their physical properties. For specific combinations of parameters, the metallicity derived by our module is consistent with the empirical formula. We further compare our models with other photoionization models used to simulate AGN NLR emission, and perform a line-sensitivity study to identify the most effective diagnostic lines for each parameter in our module. Finally, we confirm that the dust attenuation law plays an important role in SED fitting.

The theory of wave turbulence describes the properties of physical systems composed of a set of weak-amplitude random waves interacting nonlinearly. Here, we study odd wave turbulence, which arises in chiral media subjected to non-reciprocal stresses, notably odd viscosity and odd elasticity. In both cases, we consider simple models for which we can derive and solve analytically the kinetic equations describing the long-term statistical behavior of spectral quantities such as energy or wave action. For odd viscosity, we consider a three-dimensional model that exhibits wave turbulence involving three-wave interactions, which gives rise to a direct energy cascade characterized by an anisotropic Kolmogorov-Zakharov (KZ) spectrum. For odd elasticity, we consider a quasi-one-dimensional overdamped model that exhibits much slower dynamics involving six-wave interactions. In that case, the KZ spectrum corresponding to a forward cascade of a conserved quantity we call odd energy, is nonlocal and therefore does not constitute a physical solution. However, the other KZ solution, which describes an inverse cascade of wave action, is only marginally non-local and is therefore valid up to a logarithmic correction. These two analytical theories provide a rigorous interpretation of direct numerical simulations, where the KZ spectrum is observed both in the case of odd viscosity (forward cascade) and of odd elasticity (inverse cascade).

We investigate the motion of spinning test particles in the spacetime of a global monopole in the framework of the Mathisson-Papapetrou-Dixon equations. By making use of the symmetries of the spacetime, we obtain a general exact solution to the equations of motion. We show that the particle's trajectories, momenta, and spin can be expressed in terms of three specific functions of the polar and azimuthal angles. We also show that the system is completely integrable. We obtain the general non-geodesic trajectory of the particle, and also examine the particular cases of radial and planar motion. We compare the non-geodesic trajectories of a spinning particle with a non-spinning particle.

Holography offers unique advantages for delivering perceptual realism while preserving compact form factors in VR/AR. Its perceptual quality, however, hinges on encoding rich wavefronts of photorealistic scenes into interference patterns and then incoherently multiplexing the resulting wave fields for perception. Existing CGH paradigms decouple radiance estimation from wave propagation by pre-rendering radiance on discretized scene sectors. This separation between radiometric and wave-optical computation inherently limits the range of focus cues and visual effects that can be faithfully reproduced, including depth- and view-continuity, and physically based material behaviors such as glossy or mirror-like reflection and refraction. We present a physically accurate yet computationally efficient wave optics rendering framework leveraging path tracing to encode full 3D visual cues into phase holograms. Specifically, we employ a Monte Carlo method to solve both the rendering equation and the Rayleigh--Sommerfeld integral simultaneously. Our algorithm is fully compatible with modern graphics techniques and can generate multiple time-multiplexed random holograms with minimal additional time cost via Path Reuse. By employing a fast approximation with an ambient radiance cache, we realize an order of magnitude convergence speed improvement. The resulting coherent wave fields that inherently encode comprehensive visual effects are converted into phase-only holograms under complex-amplitude supervision. Through extensive simulations and experimental validations on a spatial light modulator-based display prototype, we demonstrate faithful holographic reconstructions of natural 3D cues and complex materials, including realistic defocus blur, view-dependent effects, as well as appearance highlights and reflections.

Driven by the massive video transmission requirements in the Internet of Everything, semantic communication holds great promise for striking a balance between transmission efficiency and quality. This paper introduces a large-model-driven generative video semantic communication (LGVSC) framework, enabling efficient video semantic transmission under extremely low bandwidth conditions. First, by decoupling the encoder and decoder as well as exposing explicit intermediate semantic representations, LGVSC maintains interpretability, avoiding the black-box behavior commonly observed in end-to-end systems. Next, we introduce a new metric, i.e., the probability-based semantic similarity score (PSSS), which quantifies semantic similarity for complex modalities within a continuous range, allowing for more precise evaluation of semantic content. Building on PSSS, we propose a semantic-guided keyframe extraction module driven by a multimodal large model. This module can enhance fine-grained semantic consistency during keyframe selection at the transmitter, optimizing transmission bandwidth without compromising semantic fidelity. Additionally, we design a generative large-model-driven dynamic semantic-adaptive decoder at the receiver, which can adapt to videos of arbitrary lengths. Simulation results demonstrate that LGVSC significantly outperforms traditional schemes, achieving a channel bandwidth ratio on the order of $10^{-4}$ to $10^{-3}$, while maintaining strong zero-shot generalization across downstream tasks.

Short-dated index options make scheduled macro-announcement risk visible in market prices, but visibility does not imply identification: a flexible no-event surface fitted to event-spanning quotes can absorb event premia, while a jump calibrated without event-spanning quotes is unidentified. To separate the continuous surface from the scheduled jump, we model Federal Open Market Committee (FOMC) decisions, Consumer Price Index (CPI) releases, and nonfarm payroll (NFP) reports as deterministic-time jumps in risk-neutral option pricing and propose a non-spanning identification protocol. Non-spanning expiries identify the no-event volatility surface, event-spanning training quotes calibrate the scheduled jump, and held-out event-spanning quotes are used only for pricing evaluation. On PM-settled S\&P 500 index (SPX) options from May 2022 to August 2025, Gaussian and two-component mixture jumps improve held-out event-spanning pricing, with the clearest gains in robust median pricing errors and in event-volatility option combinations (straddles and strangles) rather than directional risk reversals. A contaminated-surface stress test confirms the identification concern: allowing event-spanning training quotes into the no-event surface fit produces strong held-out performance by absorbing event premia rather than identifying scheduled jump risk. An amortized mixture density network (MDN) benchmark shows limited cross-event transfer: pure leave-one-event-out amortization reduces implied-volatility errors but not mean dollar or mean spread-normalized pricing errors, while the scale-calibrated variant restores Gaussian-level performance yet remains below event-specific mixture calibration. Scheduled-jump identification is strongest for CPI and FOMC and weaker for NFP.

The rapid shift toward agentic and long-context workloads in Large Language Models (LLMs) is pushing the industry beyond the capacity of individual servers toward disaggregated shared storage to handle TB-scale context states. This movement has led to the emergence of specialized shared context layers designed to externalize and share cumulative inference states across distributed clusters. While offloading to a data processing unit (DPU) within just-a-bunch-of-flash (JBOF) architectures accelerates NVMe-over-fabrics (NVMe-oF) target processing, the need for sophisticated software-level optimization and cost-efficiency burdens remain significant. Consequently, the ideal architecture for scaling this shared context infrastructure is still an active area of exploration. In this paper, we propose ITME (Inference Tiered Memory Expansion), which leverages a CXL-hybrid memory to present a massive, TB-scale byte-addressable remote memory expansion. This approach enables cost-efficient scaling and simplifies the software stack through direct byte-addressability, effectively addressing the challenges of shared context infrastructure. Our key insight is that the deterministic access patterns of voluminous model weights and prefix caches enable the system to proactively manage data movement across the memory-storage hierarchy. We validate ITME by evaluating its performance potential with production-grade SK Hynix CMM and PCIe Gen5 NVMe SSDs, while further demonstrating its functional feasibility through an FPGA-based hardware prototype. Overall, ITME enhances conventional CPU-offloading by providing additional remote memory expansion to accommodate large KV cache footprints beyond host memory limits, achieving up to a 35.7\% throughput improvement.

The $\Lambda$ global polarization indicates that hot and dense matter created in non-central heavy-ion collisions carries large orbital angular momentum. However, the relation between hadronic polarization and the medium's collective rotation remains to be validated. Using the UrQMD transport model, we calculate the thermal vorticity-induced polarization of $\Lambda$s in Ag+Ag and Au+Au collisions from $\sqrt{s_{\rm NN}}=2.24$-$7.7$ GeV and a range of centralities. Two different equations of state used in the UrQMD simulation are compared: one resembles a hadron resonance gas, while the other is based on the chiral mean field (CMF) model, providing a more realistic description of dense nuclear matter including a chiral transition that is consistent with lattice QCD expectations. The polarization is sensitive to the equation of state and a softer EoS leads to smaller values. In addition, we show that the $\Lambda$ polarization in the experimental acceptance and centrality selection does not decrease for even lower beam energies. Our results indicate that the process leading to the large vorticity is a result of the large shear in the baryon current created by its stopping.

High-mass X-ray binaries (HMXBs) provide a natural laboratory to study radiatively driven stellar winds under strong external X-ray irradiation. As the compact object moves along its orbit, the wind density and ionization structure vary with orbital phase, leaving characteristic signatures in X-ray emission and absorption features. The amplitude and morphology of this variability depend on the system geometry, including the orbital inclination (via line-of-sight and occultation effects) and the orbital eccentricity (via phase-dependent changes in the orbital separation). We present a computational framework that connects phase-resolved spectroscopic variability to the three-dimensional structure of irradiated winds, and that enables inference of physically meaningful wind--irradiation parameters within a Bayesian setting. We combine photoionization calculations with a parametric wind description and orbital geometry to construct three-dimensional maps of density and ionization. From these maps we compute orbital-phase-dependent diagnostics, accounting for geometric occultation and wind inhomogeneity through a clumping prescription. We then use Bayesian inference to compare model predictions with phase-resolved observables and to quantify parameter constraints and degeneracies. The framework reproduces the main orbital-phase-dependent trends expected for irradiated winds and yields robust constraints on the system ionization balance. While combinations of wind and luminosity parameters are well constrained, individual parameters can remain partially degenerate depending on the orbital configuration and data quality. This modular and computationally efficient approach provides a route to interpret HMXB phase variability in physical terms, and offers a foundation for future extensions toward forward spectral modeling and population-level applications.